![Python supports a broad range of arithmetic operations,
including addition (+), subtraction (-), multiplication (*), and
division (/).
```python # Addition result = 7 + 3
# Subtraction
difference = 10 - 2
# Multiplication
product = 4 * 5
# Division
quotient = 20 / 4
```
Collections
Python provides several useful data structures to store
collections of items. The most common are lists, tuples,
sets, and dictionaries.
Lists
Lists are ordered collections that are mutable, meaning you
can change their contents after creation.
```python # Create a list of mineral samples samples =
["Quartz", "Feldspar", "Mica"] # Access elements by index
first_sample = samples[0] # Add a new sample
samples.append("Amphibole")
```
Tuples
Tuples are similar to lists but are immutable – once created,
their contents cannot be changed.](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-21-320.jpg)
![```python # Create a tuple of geographical coordinates
coordinates = (49.2827, -123.1207) # Latitude and
Longitude for Vancouver # Access elements by index
latitude = coordinates[0]
```
Sets
Sets are unordered collections of unique elements, useful
for storing elements without duplicates.
```python # Create a set of survey areas survey_areas =
{"Area A", "Area B", "Area C"} # Add a new area
survey_areas.add("Area D")
```
Dictionaries
Dictionaries store key-value pairs, enabling rapid access to
an item's value based on its key.
```python # Create a dictionary to store equipment status
equipment_status = { "Drill_1": "Operational",
"Excavator_3": "Maintenance", "Truck_2": "In Transit" } #
Access the status of a specific piece of equipment
drill_status = equipment_status["Drill_1"]
```
Control Flow
Control flow structures allow you to dictate the order in
which statements are executed in your program.
Conditional Statements](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-22-320.jpg)
![efficiency = (extracted_amount / total_capacity) * 100
return efficiency
# Call the function
extracted = 500 # Tons extracted
capacity = 1000 # Total capacity in tons
efficiency = calculate_efficiency(extracted, capacity)
print(f"Extraction Efficiency: {efficiency}%")
```
Importing Modules and Libraries
Python’s vast ecosystem of modules and libraries allows you
to leverage existing code to solve complex problems.
```python # Import the math module import math
# Use the math module to perform a calculation
angle = 45 # Angle in degrees
radians = math.radians(angle)
sin_value = math.sin(radians)
print(f"Sin({angle}°) = {sin_value}")
```
Practical Example: Analyzing Resource Data
To illustrate the power of Python syntax in a real-world
context, let's consider a practical example. We'll write a
script to analyze a set of mineral samples and determine
the average purity level.
```python # List of sample purities sample_purities = [85.5,
90.3, 78.8, 92.1, 88.4]
# Function to calculate average purity
def calculate_average_purity(purities):
total_purity = sum(purities)
number_of_samples = len(purities)
average_purity = total_purity / number_of_samples
return average_purity](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-24-320.jpg)
![mineral extracted
- **Floating-point (`float`)**: Numbers with decimal points.python
ore_density = 2.65 # Density in grams per cubic centimeter
- **Complex (`complex`)**: Numbers with real and imaginary parts.python
complex_number = 3 + 5j # Represents 3 + 5i
```
String Data Type
Strings are sequences of characters, used to store text.
They can be enclosed in single quotes ('), double quotes ("),
or triple quotes for multi-line strings (''' or """).
```python # Single-line string mineral_name = "Quartz"
# Multi-line string (useful for longer descriptions)
description = """Quartz is a hard, crystalline mineral
composed of silicon and oxygen atoms."""
```
String operations include concatenation, slicing, and
formatting, providing powerful tools for text manipulation.
```python # Concatenation full_description = mineral_name
+ " - " + description
# Slicing
short_description = description[:20] # First 20 characters
# Formatting
formatted_string = f"Extracting {mineral_name} with density {ore_density}
g/cm³."
```
Boolean Data Type](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-27-320.jpg)
![Booleans represent one of two values: True or False. They are
primarily used in conditional statements and logical
operations.
```python # Example of boolean values is_mine_operational
= True is_survey_completed = False
```
None Data Type
The None type is a special type in Python that represents the
absence of value or a null value.
```python # Example of None unknown_value = None
```
Collection Data Types
Python provides several built-in collection types for storing
multiple items. These include lists, tuples, sets, and
dictionaries.
Lists
Lists are ordered collections of items, which are mutable
(can be changed).
```python # Creating a list minerals = ["Quartz", "Feldspar",
"Mica"]
# Accessing elements
first_mineral = minerals[0] # "Quartz"
# Modifying elements
minerals[1] = "Gypsum" # Changing "Feldspar" to "Gypsum"
# Adding elements
minerals.append("Amphibole")](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-28-320.jpg)
![# Removing elements
minerals.remove("Mica")
```
Tuples
Tuples are similar to lists but immutable (cannot be
changed).
```python # Creating a tuple coordinates = (49.2827,
-123.1207)
# Accessing elements
latitude = coordinates[0]
```
Sets
Sets are unordered collections of unique items. They are
useful for membership tests and eliminating duplicates.
```python # Creating a set unique_samples = {"Quartz",
"Feldspar", "Mica"}
# Adding elements
unique_samples.add("Gypsum")
# Removing elements
unique_samples.discard("Mica")
```
Dictionaries
Dictionaries store key-value pairs, allowing fast retrieval of
values based on keys.](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-29-320.jpg)
![```python # Creating a dictionary sample_data = {
"sample_1": {"type": "Quartz", "purity": 95.4}, "sample_2":
{"type": "Feldspar", "purity": 88.1} }
# Accessing values
sample_1_type = sample_data["sample_1"]["type"] # "Quartz"
# Modifying values
sample_data["sample_1"]["purity"] = 96.0
```
Type Conversion
Sometimes, it's necessary to convert values from one type
to another. Python provides several built-in functions for
type conversion:
int(): Convert to integer.
float(): Convert to float.
str(): Convert to string.
bool(): Convert to boolean.
```python # Examples of type conversion raw_data = "100"
converted_data = int(raw_data) # Convert string to integer
raw_density = "2.65"
density = float(raw_density) # Convert string to float
valid = bool(1) # Convert integer to boolean (True)
```
Practical Example: Managing Mineral Data
Let's apply these concepts to a practical example of
managing mineral data. Imagine you've collected data on
different minerals, including their names, types, and
purities. We'll use various data types and structures to store
and manipulate this data.](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-30-320.jpg)
![```python # List of mineral names mineral_names =
["Quartz", "Feldspar", "Mica"]
# Dictionary to store mineral data
mineral_data = {
"Quartz": {"type": "Silicate", "purity": 95.4},
"Feldspar": {"type": "Silicate", "purity": 88.1},
"Mica": {"type": "Silicate", "purity": 90.2}
}
# Function to calculate average purity of minerals
def calculate_average_purity(mineral_dict):
total_purity = sum(mineral["purity"] for mineral in mineral_dict.values())
number_of_minerals = len(mineral_dict)
average_purity = total_purity / number_of_minerals
return average_purity
# Calculate average purity
average_purity = calculate_average_purity(mineral_data)
print(f"Average Purity: {average_purity}%")
```
Mastering data types and variables is pivotal to your journey
in Python programming for natural resource extraction. From
handling numeric data and text to leveraging collections for
managing complex datasets, each element plays a crucial
role in building robust analytical solutions.
With a solid understanding of these fundamentals, you're
well-prepared to dive deeper into Python's capabilities. The
upcoming chapters will build upon this knowledge, guiding
you through data preprocessing, advanced visualization,
and machine learning techniques tailored to the unique
challenges of environmental science and resource
management. Embrace these tools, and set forth on your
path to becoming an adept Python programmer in the ever-
evolving field of natural resource extraction.](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-31-320.jpg)
![```
In this example, the nested if statement checks the humidity
level only if the temperature is greater than 20 degrees.
Introduction to Loops
Loops are fundamental in programming for performing
repetitive tasks efficiently. In Python, there are primarily two
types of loops: for loops and while loops. These structures
help automate repetitive processes, reducing manual effort
and the likelihood of errors.
For Loops
The for loop iterates over a sequence (such as a list, tuple, or
string) and executes a block of code for each item in the
sequence. This is particularly useful for processing datasets
in natural resource extraction.
```python # Example of a for loop minerals = ["Quartz",
"Feldspar", "Mica"] for mineral in minerals: print(mineral)
```
In this example, each item in the minerals list is printed.
Using the range() Function
The range() function generates a sequence of numbers, which
is often used with for loops.
```python # Example of a for loop with range() for i in
range(5): print(i)
```
This loop prints numbers from 0 to 4.
While Loops](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-34-320.jpg)
![The while loop continues executing a block of code as long as
a specified condition is true. This allows for more flexible
and complex looping behavior.
```python # Example of a while loop count = 0 while count
< 5: print(count) count += 1 # Increment the count
```
Here, the loop prints numbers from 0 to 4, incrementing
count each time until the condition count < 5 is no longer true.
Practical Example: Analyzing Mineral Data
Let's combine conditional statements and loops in a
practical example. Imagine you're working with mineral data
and need to categorize minerals based on their purity
levels.
```python # List of minerals with their purity levels minerals
= [ {"name": "Quartz", "purity": 95.4}, {"name": "Feldspar",
"purity": 88.1}, {"name": "Mica", "purity": 90.2}, {"name":
"Amphibole", "purity": 76.5} ]
# Categorize minerals based on purity
for mineral in minerals:
if mineral["purity"] > 90:
category = "High purity"
elif mineral["purity"] > 80:
category = "Medium purity"
else:
category = "Low purity"
print(f"{mineral['name']} is categorized as {category}.")
```
In this example, each mineral is categorized based on its
purity level, and the result is printed.
Mastering conditional statements and loops is essential for
performing more sophisticated and automated tasks in](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-35-320.jpg)
![```
Using Aliases
Aliases can be assigned to modules or functions to simplify
usage.
```python # Using aliases import mymodule as mm from
mymodule import greet as g
# Calling the aliased functions
mm.greet("Reef") # Outputs: Hello, Reef!
g("Reef") # Outputs: Hello, Reef!
```
Practical Example: Building a Rainfall Analysis Module
Imagine you are tasked with analyzing rainfall data to
identify patterns and predict future trends. You can
encapsulate this functionality in a module named rainfall.py.
```python # rainfall.py def average_rainfall(data): return
sum(data) / len(data)
def max_rainfall(data):
return max(data)
def min_rainfall(data):
return min(data)
```
You can then import and use this module in your script.
```python # Main script import rainfall
# Sample rainfall data
rainfall_data = [23.4, 45.6, 12.1, 34.5, 22.3, 31.4]
# Calling functions from the rainfall module
avg = rainfall.average_rainfall(rainfall_data)](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-40-320.jpg)
![Key Libraries for Natural
Resource Extraction
Several Python libraries are particularly valuable for natural
resource extraction, each serving a unique purpose. We will
explore some of the most critical libraries and provide
practical examples to illustrate their applications.
NumPy: Numerical Operations
NumPy provides support for arrays, matrices, and numerous
mathematical functions. It forms the foundation for many
higher-level scientific libraries.
```python import numpy as np
# Creating a NumPy array
data = np.array([1, 2, 3, 4, 5])
# Performing operations on arrays
mean = np.mean(data)
std_dev = np.std(data)
print(f"Mean: {mean}, Standard Deviation: {std_dev}")
```
NumPy’s n-dimensional array object is akin to the glistening
glass towers that define Vancouver’s skyline — versatile,
robust, and foundational.
Pandas: Data Manipulation
Pandas is indispensable for data manipulation and analysis,
providing data structures like DataFrames, which are perfect
for handling heterogeneous data.
```python import pandas as pd](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-43-320.jpg)
![# Creating a DataFrame
data = {'Year': [2018, 2019, 2020],
'Rainfall': [1005.8, 1036.1, 987.6]}
df = pd.DataFrame(data)
# Performing operations on DataFrame
mean_rainfall = df['Rainfall'].mean()
print(f"Mean Rainfall: {mean_rainfall} mm")
```
Pandas empowers you to manage data as efficiently as
Vancouver’s public transport system navigates its streets.
Matplotlib and Seaborn: Data
Visualization
Matplotlib and Seaborn are powerful libraries for data
visualization. While Matplotlib provides comprehensive 2D
plotting capabilities, Seaborn builds on Matplotlib to provide
a high-level interface for drawing attractive and informative
statistical graphics.
```python import matplotlib.pyplot as plt import seaborn as
sns
# Creating a plot with Matplotlib
plt.plot([1, 2, 3], [4, 5, 6])
plt.title('Simple Plot')
plt.show()
# Creating a plot with Seaborn
sns.set(style="whitegrid")
data = sns.load_dataset("iris")
sns.boxplot(x=data["species"], y=data["sepal_length"])
plt.show()
```](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-44-320.jpg)
![These libraries help visualize data patterns, much like the
iconic Capilano Suspension Bridge offers breathtaking views
of Vancouver’s natural beauty.
GeoPandas: Geospatial Data
GeoPandas extends Pandas to handle geospatial data,
essential for tasks involving map projections and geometry
operations.
```python import geopandas as gpd
# Reading a shapefile
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
# Plotting the geospatial data
world.plot()
plt.show()
```
GeoPandas turns complex geospatial data into insightful
visualizations, akin to how Vancouver’s Seawall offers a
panoramic view of the city’s picturesque landscape.
Scikit-learn: Machine Learning
Scikit-learn is a robust library for implementing machine
learning algorithms. It provides tools for model selection,
preprocessing, and various supervised and unsupervised
learning algorithms.
```python from sklearn.linear_model import
LinearRegression
# Sample data
X = [[1], [2], [3], [4]]
y = [2, 3, 5, 7]](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-45-320.jpg)
![# Creating and fitting the model
model = LinearRegression()
model.fit(X, y)
# Making predictions
predictions = model.predict([[5]])
print(f"Prediction for input 5: {predictions[0]}")
```
Scikit-learn enables powerful machine learning applications,
much like how Vancouver’s tech scene is driving innovation
with AI and data science.
Creating and Using Custom
Packages
Creating custom packages allows you to organize your code
logically, making it reusable and easier to maintain.
Consider an example where you create a package named
resource_analysis with modules for different types of analysis.
Directory Structure
resource_analysis/ __init__.py rainfall.py geological.py
rainfall.py
```python def average_rainfall(data): return sum(data) /
len(data)
def max_rainfall(data):
return max(data)
def min_rainfall(data):
return min(data)
```](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-46-320.jpg)
![geological.py
```python def analyze_rock_composition(data): return
{'Silicon': 60, 'Oxygen': 25, 'Iron': 15}
```
Using the Custom Package
```python # Main script from resource_analysis import
rainfall, geological
# Sample data
rainfall_data = [23.4, 45.6, 12.1, 34.5, 22.3, 31.4]
# Using functions from the custom package
avg = rainfall.average_rainfall(rainfall_data)
rock_comp = geological.analyze_rock_composition(None)
print(f"Average Rainfall: {avg} mm")
print(f"Rock Composition: {rock_comp}")
```
Practical Example:
Automating Data Analysis
with Libraries
To demonstrate the real-world application of libraries and
packages, let’s build a script that combines functionalities
from NumPy, Pandas, and Matplotlib to analyze and
visualize rainfall data trends over several years.
```python import numpy as np import pandas as pd import
matplotlib.pyplot as plt](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-47-320.jpg)
![# Sample data: Yearly rainfall in mm
years = np.arange(2000, 2021)
rainfall = np.random.rand(21) * 800 + 200 # Random data for illustration
# Creating a DataFrame
df = pd.DataFrame({'Year': years, 'Rainfall': rainfall})
# Calculating rolling mean
df['RollingMean'] = df['Rainfall'].rolling(window=3).mean()
# Plotting the data
plt.plot(df['Year'], df['Rainfall'], label='Annual Rainfall')
plt.plot(df['Year'], df['RollingMean'], label='3-Year Rolling Mean', linestyle='--')
plt.xlabel('Year')
plt.ylabel('Rainfall (mm)')
plt.title('Yearly Rainfall Trends')
plt.legend()
plt.show()
```
Working with libraries and packages in Python is akin to
navigating the multifaceted, vibrant culture of Vancouver.
Each library brings unique capabilities, much like the city's
diverse neighborhoods, from the historical charm of
Gastown to the modern ethos of Yaletown. By mastering
these tools, you amplify the power of your Python programs,
making it possible to tackle complex challenges in natural
resource extraction efficiently and effectively.
As you continue on this journey, remember that just like the
interconnected streets and communities of Vancouver,
Python libraries and packages work best when integrated
harmoniously to create a seamless, powerful analytical
toolkit.
Input and Output Handling](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-48-320.jpg)
![NoSQL Databases with
MongoDB
MongoDB is a popular NoSQL database suited for handling
large volumes of unstructured data. The pymongo library
facilitates interaction with MongoDB.
```python from pymongo import MongoClient
# Connecting to MongoDB
client = MongoClient('localhost', 27017)
db = client['resource_db']
collection = db['resources']
# Inserting a document
collection.insert_one({'name': 'Silver', 'quantity': 50})
# Querying documents
documents = collection.find()
for doc in documents:
print(doc)
```
Handling NoSQL databases with MongoDB is akin to
exploring the eclectic mix of exhibits at the Museum of
Anthropology, where each document reveals its unique
story.
Practical Example:
Comprehensive I/O Handling
To encapsulate the concepts discussed, let’s develop a
script that reads a CSV file containing resource extraction
data, processes it, and writes the results to a JSON file.
```python import pandas as pd import json](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-54-320.jpg)
![“Alas! must I say it, fare-farewell to thee,
Mysterious Egypt, great land of the flea,
And thy Thebaic temples, Luxor and Karnac,
Where the natives change slowly from yellow to black.
Shall I ne’er see thy plain, so fraught with renown,
Where the shadoofs go up and the shadoofs go down,
Which two stalwart natives bend over and sing,
While their loins are concealed by a simple shoe string.”
This verse, in spite of the reference to the lack of clothes of the
stalwart natives, evidently did not shock my sensibilities as much as
the motions of the dancing-girls. Farther on in the letter I describe the
New Year’s Eve party, and how Mr. Merriam sang a song which I
(Conie) liked very much, and which was called “She’s Naughty But So
Nice.” “Teedie,” however, did not care for that song, but preferred one
called “Aunt Dinah,” because one verse ran: “My love she am a giraffe,
a two-humped camamile.” [Music had apparently only charms to
soothe him when suggestive of his beloved animal studies.] From
Thebes also my brother writes to his aunt one of the most interesting
letters of his boyhood:
Near Kom Obos, Jan. 26th, 1873.
Dear Aunt Annie:
My right hand having recovered from the imaginary attack
from which it did not suffer, I proceed to thank you for your
kind present, which very much delighted me. We are now on
the Nile and have been on that great and mysterious river for
over a month. I think I have never enjoyed myself so much as
in this month. There has always been something to do, for we
could always fall back upon shooting when everything else
failed us. And then we had those splendid and grand old ruins
to see, and one of them will stock you with thoughts for a
month. The temple that I enjoyed most was Karnak. We saw it
by moonlight. I never was impressed by anything so much. To
wander among those great columns under the same moon that](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-58-320.jpg)
![had looked down on them for thousands of years was awe-
inspiring; it gave rise to thoughts of the ineffable, the
unutterable; thoughts which you cannot express, which cannot
be uttered, which cannot be answered until after The Great
Sleep.
[Here the little philosopher breaks off and continues in less
serious mood on February 9.]
I have had great enjoyment from the shooting here, as I
have procured between one and two hundred skins. I expect to
procure some more in Syria. Inform Emlen of this. As you are
probably aware, Father presented me on Christmas with a
double-barrelled breech loading shot gun, which I never move
on shore without, excepting on Sundays. The largest bird I
have yet killed is a Crane which I shot as it rose from a lagoon
near Thebes.
The sporting is injurious to my trousers....
Now that I am on the subject of dress I may as well
mention that the dress of the inhabitants up to ten years of age
is nothing. After that they put on a shirt descended from some
remote ancestor, and never take it off till the day of their death.
Mother is recovering from an attack of indigestion, but the
rest are all well and send love to you and our friends, in which I
join sincerely, and remain,
Your Most Affectionate Nephew,
T. Roosevelt, Jr.
The adoration of his little sister for the erudite “Teedie” is shown in
every letter, especially in the letters to their mutual little friend “Edie.”
On January 25 this admiration is summed up in a postscript which
says: “Teedie is out shooting now. He is quite professionist [no higher
praise could apparently be given than this remarkable word] in
shooting, skinning and stuffing, and he is so satisfied.” This expression
seems to sum up the absolute sense of well-being during that](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-59-320.jpg)
![beautiful, I did not like them as much as either Karnak or Baalbek.
Having dutifully made these architectural criticisms, I turn with gusto
to the fact that Tom and Fannie Lawrence, “Teedie,” “Ellie,” and I have
such splendid games of tag on the different steamers, and that I know
my aunt would have enjoyed seeing us. The tag was “con amore,”
while the interest in the temples was, I fear, somewhat induced. Our
comprehending mother and father, however, always allowed us joyous
moments between educational efforts. In a letter from Constantinople
written by “Ellie” on April 7, he says: “We have had Tom and Frank
Lawrence here to dinner, and we had a splendid game of ‘muggins’
and tried to play eucre (I don’t know that this is rightly spelled) with
five, but did not suceede, Teedie did make such mistakes. [Not such
an expert in cards, you see, as in tarsi and mandibles!] But we were in
such spirits that it made no difference, and we did nothing but shout
at the top of our voices the battle cry of freedom; and the playing of a
game of slapjack helped us get off our steam with hard slaps, but
even then there was enough (steam) left in Teedie and Tom to have a
candle fight and grease their clothes, and poor Frank’s and mine, who
were doing nothing at all!” As one can see by this description, the
learned and rather delicate “Teedie” was only a normal, merry boy
after all. “Ellie” describes also the wonderful rides in Constantinople,
and many other joys planned by our indulgent parents. From that
same city, called because of its many steeples The City of Minarets,
“Teedie” writes to his little friend Edith:
I think I have enjoyed myself more this winter than I ever
did before. Much to add to my enjoyment Father gave me a
gun at Christmas, which rendered me happy and the rest of the
family miserable.
I killed several hundred birds with it, and then went and
lost it! I think I enjoyed the time in Egypt most, and after that I
had the most fun while camping out in Syria.
While camping out we were on horseback for several hours
of each day, and as I like riding ever so much, and as the
Syrian horses are very good, we had a splendid time. While](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-65-320.jpg)
![“Teedie” not only indulged in the free play of fancy such as the
above, but wrote with extraordinary system and regularity for a boy of
fourteen to his mother and father, and perhaps these letters, written in
the far-away Dresden atmosphere, show more conclusively than almost
any others the character, the awakening mind, the forceful mentality of
the young and delicate boy. On May 29, in a letter to his mother, a very
parental letter about his homesick little sister who had not yet been
taken from the elderly family in which she was so unhappy, he drops
into a lighter vein and says: “I have overheard a good deal of Minckwitz
conversation which they did not think I understood; Father was
considered ‘very pretty’ (sehr hübsch) and his German ‘exceedingly
beautiful,’ neither of which statements I quite agree with.” And a week
or two later, writing to his father, he describes, after referring casually to
a bad attack of asthma, an afternoon of tag and climbing trees, supper
out in the open air, and long walks through the green fields dotted with
the blue cornflowers and brilliant red poppies. True to his individual
tastes, he says: “When I am not studying my lessons or out walking I
spend all my time in translating natural history, wrestling with Richard, a
young cousin of the Minckwitz’ whom I can throw as often as he throws
me, and I also sometimes cook, although my efforts in the culinary art
are really confined to grinding coffee, beating eggs or making hash, and
such light labors.” Later he writes again: “The boxing gloves are a
source of great amusement; you ought to have seen us after our
‘rounds’ yesterday.” The foregoing “rounds” were described even more
graphically by “Ellie” in a letter to our uncle, Mr. Gracie, as follows:
“Father, you know, sent us a pair of boxing gloves apiece and Teedie,
Johnnie, and I have had jolly fun with them. Last night in a round of
one minute and a half with Teedie, he got a bloody nose and I got a
bloody mouth, and in a round with Johnnie, I got a bloody mouth again
and he a pair of purple eyes. Then Johnnie gave Teedie another bloody
nose. [The boys by this time seemed to have multiplied their features
indefinitely with more purple eyes!] We do enjoy them so! Boxing is one
of Teedie’s and my favorite amusements; it is such a novelty to be made
to see stars when it is not night.” No wonder that later “Ellie”
contributed what I called in one of my later letters a “tragical” article
called “Bloody Hand” for the D. L. A. C., perhaps engendered by the
memory of all those bloody mouths and noses!](https://image.slidesharecdn.com/28906692-250521134045-a8e4bb4a/85/Python-For-Natural-Resource-Extraction-A-Comprehensive-Programming-Guide-For-2024-Van-Der-Post-76-320.jpg)
Python For Natural Resource Extraction A Comprehensive Programming Guide For 2024 Van Der Post
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- 6. PYTHON For Natural Resource Extraction Hayden Van Der Post Reactive Publishing
- 7. CONTENTS Title Page Preface Chapter 1:Introduction to Python Programming Chapter 2: Data Handling with Python Chapter 3: Data Visualization for Natural Resources Chapter 4: Geospatial Data Analysis Chapter 5: Time Series Analysis for Resource Monitoring Chapter 6: Machine Learning for Resource Extraction Chapter 7: Automation of Data Processing Chapter 8: Remote Sensing Data Analysis Chapter 9: Environmental Impact Assessment through Data Analytics Chapter 10: Building a Complete Analytics Solution Appendix A: Index Appendix B: Tutorials Appendix C: Glossary of Terms Appendix D: Additional Resources Epilogue
- 8. © Reactive Publishing. All rights reserved. This book and its entire contents, including all text, illustrations, and code samples, are protected under copyright law. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the publisher, except in the case of brief quotations included in reviews or other non-commercial uses permitted by copyright law. The information contained in this book is for educational purposes only. While every effort has been made to ensure accuracy, the publisher and its affiliates assume no responsibility for errors or omissions, nor do they offer warranties, either express or implied, related to the contents of this book. Any references to specific software, websites, or companies are for informational purposes only and do not imply endorsement or affiliation. The publisher cannot guarantee the accuracy or completeness of any information conveyed during this publication’s validity, given the ever-evolving nature of technology and data analytics.
- 9. W PREFACE elcome to a journey that marries the power of Python programming with the critical and fascinating world of natural resource extraction. If you’ve picked up this book, it's likely because you share our interest in harnessing the capabilities of modern technology for meaningful, impactful work. Whether you are a student, a professional in the natural resources sector, or an avid data enthusiast, this book is designed with you in mind. Empowering Through Knowledge The world of natural resource extraction is undergoing a transformation. With increasing global demands and the pressing need for sustainable practices, being able to analyze, visualize, and interpret data efficiently has never been more important. This book aims to equip you with the skills necessary to excel in this dynamic field by leveraging the robust capabilities of Python programming. A Journey Of Discovery From setting up your Python development environment to building complex analytics solutions, this book serves as a comprehensive guide. Each chapter is crafted to build your expertise step-by-step, ensuring that you not only understand the theory but also gain practical, hands-on experience. Our approach intertwines foundational
- 10. programming concepts with specialized techniques, tailored to the nuances of natural resource extraction. Real-World Relevance Throughout the book, you will find numerous real-world examples and case studies that are directly applicable to scenarios you might encounter in your career or research. Whether it's analyzing geospatial data to assess environmental impact or using machine learning algorithms to predict resource availability, each topic is presented with a focus on practical utility and real-world relevance. Why This Book? Our aim is not just to teach you Python, but to build a toolkit that you can draw from to tackle complex problems and drive meaningful insights in the natural resources sector. This is not merely a programming manual—it's a holistic guide that demonstrates the application of data analytics to real-world problems, pushing you to think critically and innovate solutions that can make a significant impact. Support And Community Understanding that learning is a continuous process, we have designed this book to be more than just a static resource. You'll find links to supplementary materials, access to code repositories, and invitations to join our community of learners and professionals. Engaging with peers who share your interests will provide additional perspectives and support, enhancing your learning experience. Your Path To Mastery Each chapter has been included with careful consideration, aiming to provide a logical progression that builds upon
- 11. what you've learned previously. Starting with the essentials of Python programming and advancing through data handling, visualization, machine learning, and automation, we culminate in the creation of a complete analytics solution. Along the way, special attention is given to domain-specific needs such as geospatial data analysis and remote sensing. Acknowledgements This book would not have been possible without the insights and feedback from numerous experts in the field. We extend our deepest gratitude to those who have contributed their knowledge and expertise to ensure this book is as comprehensive and practical as possible. Embrace The Challenge As you turn the pages and dive into the world of analytics with Python, you’ll find that each new concept opens up vast possibilities for innovation and problem-solving in natural resource extraction. Embrace the challenge, dive deep, and let this book be your guide toward becoming not just a proficient programmer, but a skilled data analyst who makes a difference. Happy coding and analyzing! Warmest regards, Hayden Van Der Post
- 12. P CHAPTER 1:INTRODUCTION TO PYTHON PROGRAMMING ython, a versatile and powerful programming language, has become an indispensable tool across numerous fields, from web development to artificial intelligence. In the realm of natural resource extraction, Python's impact is nothing short of transformative. It opens the door to advanced data analytics, automation, and visualization techniques that are essential for modern environmental science and resource management. The Rise Of Python In Data Science Python's rise to prominence in data science is driven by several key factors. Firstly, it boasts a simple, readable syntax that allows both beginners and seasoned programmers to quickly grasp and utilize its capabilities. This aspect is particularly valuable in multidisciplinary fields like environmental science, where professionals may not have extensive programming backgrounds but need to harness the power of data analytics. Moreover, Python is renowned for its extensive ecosystem of libraries and frameworks, which facilitate a wide range of tasks from numerical computations to machine learning.
- 13. Libraries such as Pandas, NumPy, SciPy, and Matplotlib provide powerful tools for data manipulation, analysis, and visualization. In the context of natural resource extraction, these tools enable scientists and engineers to process large datasets, uncover insights, and make data-driven decisions. The Role of Python in Natural Resource Extraction Natural resource extraction involves complex processes, from exploration and assessment to extraction and environmental management. Each stage generates vast amounts of data that must be meticulously analyzed to optimize operations and minimize environmental impact. Here is where Python's capabilities shine: 1. Data Collection and Cleaning: Data derived from various sources, such as geological surveys, sensor networks, and satellite imagery, often require extensive preprocessing. Python's Pandas library provides robust functions for cleaning, transforming, and organizing data, ensuring that datasets are accurate and ready for analysis. 2. Exploratory Data Analysis (EDA): EDA is crucial in understanding the characteristics and underlying patterns within a dataset. Python's visualization libraries, like Matplotlib and Seaborn, allow users to create detailed plots and charts, making it easier to identify trends and anomalies in resource data. 3. Geospatial Analysis: Python's GeoPandas library extends the capabilities of Pandas to handle geospatial data. This is particularly important for mapping and analyzing the spatial distribution of resources, understanding land use changes, and evaluating environmental impacts. 4. Machine Learning and Predictive Modelling: Python's Scikit-learn library offers a comprehensive
- 14. suite of machine learning algorithms that can be used to build predictive models. For instance, one can predict the location of mineral deposits, forecast resource consumption trends, or classify land cover types using remote sensing data. 5. Automation and Workflow Management: Python's scripting capabilities enable the automation of repetitive tasks, such as data extraction and cleaning, thereby increasing efficiency. Libraries like Airflow facilitate the creation of complex data pipelines that can handle large-scale data processing workflows. Practical Examples of Python Applications Let's delve into some practical examples that highlight Python's utility in natural resource extraction: Example 1: Predicting Mineral Deposits Geologists can use machine learning models to predict the likelihood of finding mineral deposits in unexplored regions. By integrating data from geological surveys, historical mining records, and remote sensing imagery, a predictive model can be trained to identify promising locations for further exploration. Python's Scikit-learn library provides the tools to build, train, and evaluate such models, while GeoPandas can be used to visualize the spatial predictions on a map. Example 2: Monitoring Deforestation
- 15. Forestry management agencies often rely on satellite imagery to monitor deforestation activities. Using Python, one can automate the process of downloading and analyzing satellite images. By applying image processing techniques available in libraries like OpenCV and scikit- image, changes in forest cover can be detected over time. These changes can then be visualized using Matplotlib to create informative maps and graphs that aid in decision- making. Example 3: Optimizing Drilling Operations In the oil and gas industry, optimizing drilling schedules is critical to reducing operational costs and environmental impact. Python can be employed to analyze sensor data from drilling rigs, modeling various parameters such as drilling speed, pressure, and temperature. By applying advanced statistical methods and optimization algorithms, engineers can determine the most efficient drilling strategies. The results can then be visualized using interactive plots created with Plotly, helping stakeholders to make informed decisions. Python's versatility and powerful libraries make it an ideal choice for tackling the multifaceted challenges of natural resource extraction. Its ability to handle large datasets, perform complex analyses, and create compelling visualizations empowers environmental scientists and resource managers to optimize their operations while prioritizing sustainability. As we journey through this book, we will explore these applications in greater detail, equipping you with the skills and knowledge to harness Python for innovative solutions in natural resource extraction.
- 16. Embracing Python, we can unlock new possibilities in data- driven decision-making, paving the way for a more sustainable and efficient approach to managing our planet's precious resources. Setting up Python Development Environment Installing Python The first step in setting up your environment is to install Python. Python is available for various operating systems, including Windows, macOS, and Linux. For Windows: 1. Visit the official Python website at python.org. 2. Download the latest version of Python suitable for your system. 3. Run the installer. During the installation process, make sure to check the box that says "Add Python to PATH." This option allows you to run Python from the command line. For macOS: 1. macOS usually comes with Python pre- installed. However, it might be an outdated version. It’s recommended to install the latest version via Homebrew. 2. Install Homebrew by running the following command in Terminal: ```bash /bin/bash -c "((curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/i nstall.sh)" 3. Once Homebrew is installed, you can install Python by running:bash brew install python ``` For Linux: 1. Python is typically pre-installed on most Linux distributions. However, to install or upgrade to the latest version, open the terminal and enter: ```bash sudo apt-get update sudo apt-get install python3 ``` Setting Up a Virtual Environment
- 17. A virtual environment is essential for managing dependencies and ensuring that your projects remain isolated from one another. This prevents potential conflicts between different versions of libraries used in various projects. Creating a Virtual Environment: 1. First, ensure you have the virtualenv package installed. You can install it via pip: ```bash pip install virtualenv 2. Navigate to your project directory and create a new virtual environment:bash cd path/to/your/project virtualenv venv 3. Activate the virtual environment: - For Windows:cmd venvScriptsactivate - For macOS/Linux:bash source venv/bin/activate ``` When the virtual environment is active, any libraries you install using pip will be contained within this environment, ensuring a clean workspace for your project. Installing Essential Libraries Python’s true power lies in its extensive range of libraries. For natural resource extraction, some key libraries include Pandas, NumPy, SciPy, Matplotlib, and GeoPandas. Let's install these libraries within your virtual environment to set the stage for our projects: ```bash pip install pandas numpy scipy matplotlib geopandas ``` These libraries will provide the tools necessary for data manipulation, numerical computation, and visualization. Setting Up Jupyter Notebooks
- 18. Jupyter Notebooks offer an interactive coding environment, ideal for data analysis and visualization. They allow you to combine code, text, and visualizations in a single document, making your workflow more seamless and intuitive. Installing Jupyter Notebook: 1. With your virtual environment activated, install Jupyter Notebook: ```bash pip install notebook 2. Start Jupyter Notebook by running:bash jupyter notebook ``` This command will launch the Jupyter Notebook interface in your default web browser, allowing you to create and manage notebooks for your projects. Integrating Integrated Development Environments (IDEs) An Integrated Development Environment (IDE) can significantly enhance your productivity by offering advanced features like code completion, debugging tools, and version control integration. Popular IDEs for Python development include PyCharm, Visual Studio Code, and JupyterLab. Setting up PyCharm: 1. Download PyCharm from the official website at jetbrains.com/pycharm. 2. Install PyCharm and configure it to use the virtual environment you created earlier. 3. Open your project in PyCharm and navigate to File > Settings > Project: <project_name> > Project Interpreter, then select the interpreter located in your virtual environment. Setting up Visual Studio Code: 1. Download Visual Studio Code (VS Code) from code.visualstudio.com. 2. Install the Python extension for VS Code by going to the Extensions view by clicking the Extensions icon in the Activity Bar on the side of VS Code. Search for “Python” and install the extension provided by Microsoft. 3. Open your project folder and select the Python interpreter by pressing Ctrl+Shift+P and typing Python: Select Interpreter. Choose the interpreter from your virtual environment.
- 19. Version Control with Git Version control is essential for tracking changes to your code and collaborating with others. Git, a distributed version control system, paired with platforms like GitHub, provides a robust solution for managing your project’s codebase. Setting up Git: 1. Install Git from git-scm.com. 2. Configure Git by setting your username and email: ```bash git config -- global user.name "Your Name" git config --global user.email "[email protected]" 3. Initialize a new Git repository in your project directory:bash git init ``` Setting up your Python development environment is an investment in your productivity and the quality of your work. With Python installed, a virtual environment configured, essential libraries at your disposal, and tools like Jupyter Notebooks and IDEs, you are well-prepared to embark on complex data analytics tasks. Additionally, integrating version control with Git ensures that your projects are well-managed and collaborative. Armed with this environment, you're now ready to dive into the intricate world of data science for natural resource extraction, leveraging Python's full potential to make impactful, data-driven decisions. Basic Python Syntax The Basics of Python Syntax Python's simplicity and readability are perhaps its most beloved features. Designed with an emphasis on code clarity, Python allows developers to express complex ideas with minimal code. Below, we’ll explore some of the core elements of Python syntax, each explained through practical examples that relate directly to the challenges faced in the field of natural resource extraction.
- 20. Comments and Documentation Comments are annotations in the code that help explain what the code does. They are crucial for making your code understandable both to yourself and to others who may read it. In Python, single-line comments start with a #, while multi-line comments are enclosed in triple quotes (''' or """). ```python # This is a single-line comment explaining the code below print("Hello, World!") ''' This is a multi-line comment. It can span multiple lines. Useful for longer explanations or documentation. ''' ``` Variables and Data Types In Python, you don't need to explicitly declare the type of a variable. Variable types are assigned dynamically based on the value you assign to them. Integer ```python count = 10 - **Float**python temperature = 23.5 - **String**python location = "Vancouver" - **Boolean**python is_available = True ``` Basic Operations
- 21. Python supports a broad range of arithmetic operations, including addition (+), subtraction (-), multiplication (*), and division (/). ```python # Addition result = 7 + 3 # Subtraction difference = 10 - 2 # Multiplication product = 4 * 5 # Division quotient = 20 / 4 ``` Collections Python provides several useful data structures to store collections of items. The most common are lists, tuples, sets, and dictionaries. Lists Lists are ordered collections that are mutable, meaning you can change their contents after creation. ```python # Create a list of mineral samples samples = ["Quartz", "Feldspar", "Mica"] # Access elements by index first_sample = samples[0] # Add a new sample samples.append("Amphibole") ``` Tuples Tuples are similar to lists but are immutable – once created, their contents cannot be changed.
- 22. ```python # Create a tuple of geographical coordinates coordinates = (49.2827, -123.1207) # Latitude and Longitude for Vancouver # Access elements by index latitude = coordinates[0] ``` Sets Sets are unordered collections of unique elements, useful for storing elements without duplicates. ```python # Create a set of survey areas survey_areas = {"Area A", "Area B", "Area C"} # Add a new area survey_areas.add("Area D") ``` Dictionaries Dictionaries store key-value pairs, enabling rapid access to an item's value based on its key. ```python # Create a dictionary to store equipment status equipment_status = { "Drill_1": "Operational", "Excavator_3": "Maintenance", "Truck_2": "In Transit" } # Access the status of a specific piece of equipment drill_status = equipment_status["Drill_1"] ``` Control Flow Control flow structures allow you to dictate the order in which statements are executed in your program. Conditional Statements
- 23. Conditional statements (if, elif, else) enable decision-making in code. ```python # Determine if sample is metallic sample_type = "Metallic" if sample_type == "Metallic": print("Sample is metallic.") elif sample_type == "Non-metallic": print("Sample is non-metallic.") else: print("Sample type is unknown.") ``` Loops Loops allow you to execute a block of code repeatedly. The two primary types of loops in Python are for and while. For Loop ```python # Iterate through list of samples for sample in samples: print(f"Analyzing sample: {sample}") ``` While Loop ```python # Loop using a counter count = 0 while count < 5: print(f"Count is {count}") count += 1 ``` Functions Functions are reusable blocks of code that perform a specific task. Defining functions helps organize and modularize code. Defining and Calling Functions ```python # Define a function to calculate resource extraction efficiency def calculate_efficiency(extracted_amount, total_capacity):
- 24. efficiency = (extracted_amount / total_capacity) * 100 return efficiency # Call the function extracted = 500 # Tons extracted capacity = 1000 # Total capacity in tons efficiency = calculate_efficiency(extracted, capacity) print(f"Extraction Efficiency: {efficiency}%") ``` Importing Modules and Libraries Python’s vast ecosystem of modules and libraries allows you to leverage existing code to solve complex problems. ```python # Import the math module import math # Use the math module to perform a calculation angle = 45 # Angle in degrees radians = math.radians(angle) sin_value = math.sin(radians) print(f"Sin({angle}°) = {sin_value}") ``` Practical Example: Analyzing Resource Data To illustrate the power of Python syntax in a real-world context, let's consider a practical example. We'll write a script to analyze a set of mineral samples and determine the average purity level. ```python # List of sample purities sample_purities = [85.5, 90.3, 78.8, 92.1, 88.4] # Function to calculate average purity def calculate_average_purity(purities): total_purity = sum(purities) number_of_samples = len(purities) average_purity = total_purity / number_of_samples return average_purity
- 25. # Calculate average purity average_purity = calculate_average_purity(sample_purities) print(f"Average Purity: {average_purity}%") ``` Understanding Python syntax is the first step in harnessing Python’s full potential for natural resource extraction analytics. From defining variables and managing collections to controlling the flow of your program and creating reusable functions, these basics lay the groundwork for more advanced analyses. As you progress through this book, you'll build upon this foundation, integrating these elements into comprehensive data-driven solutions that address the challenges of resource extraction. With your Python environment set up and a solid grasp of basic syntax, you are now ready to delve deeper into data handling, visualization, machine learning, and more. Embark on this journey with confidence, knowing that each line of code brings you closer to optimizing resource extraction and promoting sustainable practices. Data Types and Variables In the city of Vancouver, there's a constant interplay of dynamic forces—just like the world of programming where a myriad of data types and variables interact to solve complex problems. Understanding the core concepts of data types and variables is crucial for anyone venturing into Python programming, especially in the domain of natural resource extraction and environmental science. Understanding Variables A variable in Python is akin to a container in your lab where you store different samples. It holds data that can be manipulated and modified throughout your program. Variables in Python are dynamically typed, meaning you
- 26. don't need to declare their type explicitly—Python infers the type based on the assigned value. Naming Variables Naming your variables sensibly is vital for clarity and maintainability of your code. Effective variable names should be descriptive, indicating the variable's role or contents. The following rules and conventions help in naming variables: Must begin with a letter (a-z, A-Z) or an underscore (_). Followed by letters, digits (0-9), or underscores. Case-sensitive, so Temperature and temperature are different variables. Use snake_case (e.g., sample_count) for naming variables to enhance readability. ```python # Example of naming variables latitude = 49.2827 longitude = -123.1207 is_active = True ``` Core Data Types in Python Python provides a range of data types to handle various kinds of data. These include numbers, strings, booleans, lists, tuples, sets, and dictionaries. Understanding these types is crucial for data manipulation and analysis. Numeric Data Types Numeric types are used to store numbers. Python supports integers, floating-point numbers, and complex numbers. Integer (int): Whole numbers, positive or negative. ```python resource_quantity = 1000 # Tons of
- 27. mineral extracted - **Floating-point (`float`)**: Numbers with decimal points.python ore_density = 2.65 # Density in grams per cubic centimeter - **Complex (`complex`)**: Numbers with real and imaginary parts.python complex_number = 3 + 5j # Represents 3 + 5i ``` String Data Type Strings are sequences of characters, used to store text. They can be enclosed in single quotes ('), double quotes ("), or triple quotes for multi-line strings (''' or """). ```python # Single-line string mineral_name = "Quartz" # Multi-line string (useful for longer descriptions) description = """Quartz is a hard, crystalline mineral composed of silicon and oxygen atoms.""" ``` String operations include concatenation, slicing, and formatting, providing powerful tools for text manipulation. ```python # Concatenation full_description = mineral_name + " - " + description # Slicing short_description = description[:20] # First 20 characters # Formatting formatted_string = f"Extracting {mineral_name} with density {ore_density} g/cm³." ``` Boolean Data Type
- 28. Booleans represent one of two values: True or False. They are primarily used in conditional statements and logical operations. ```python # Example of boolean values is_mine_operational = True is_survey_completed = False ``` None Data Type The None type is a special type in Python that represents the absence of value or a null value. ```python # Example of None unknown_value = None ``` Collection Data Types Python provides several built-in collection types for storing multiple items. These include lists, tuples, sets, and dictionaries. Lists Lists are ordered collections of items, which are mutable (can be changed). ```python # Creating a list minerals = ["Quartz", "Feldspar", "Mica"] # Accessing elements first_mineral = minerals[0] # "Quartz" # Modifying elements minerals[1] = "Gypsum" # Changing "Feldspar" to "Gypsum" # Adding elements minerals.append("Amphibole")
- 29. # Removing elements minerals.remove("Mica") ``` Tuples Tuples are similar to lists but immutable (cannot be changed). ```python # Creating a tuple coordinates = (49.2827, -123.1207) # Accessing elements latitude = coordinates[0] ``` Sets Sets are unordered collections of unique items. They are useful for membership tests and eliminating duplicates. ```python # Creating a set unique_samples = {"Quartz", "Feldspar", "Mica"} # Adding elements unique_samples.add("Gypsum") # Removing elements unique_samples.discard("Mica") ``` Dictionaries Dictionaries store key-value pairs, allowing fast retrieval of values based on keys.
- 30. ```python # Creating a dictionary sample_data = { "sample_1": {"type": "Quartz", "purity": 95.4}, "sample_2": {"type": "Feldspar", "purity": 88.1} } # Accessing values sample_1_type = sample_data["sample_1"]["type"] # "Quartz" # Modifying values sample_data["sample_1"]["purity"] = 96.0 ``` Type Conversion Sometimes, it's necessary to convert values from one type to another. Python provides several built-in functions for type conversion: int(): Convert to integer. float(): Convert to float. str(): Convert to string. bool(): Convert to boolean. ```python # Examples of type conversion raw_data = "100" converted_data = int(raw_data) # Convert string to integer raw_density = "2.65" density = float(raw_density) # Convert string to float valid = bool(1) # Convert integer to boolean (True) ``` Practical Example: Managing Mineral Data Let's apply these concepts to a practical example of managing mineral data. Imagine you've collected data on different minerals, including their names, types, and purities. We'll use various data types and structures to store and manipulate this data.
- 31. ```python # List of mineral names mineral_names = ["Quartz", "Feldspar", "Mica"] # Dictionary to store mineral data mineral_data = { "Quartz": {"type": "Silicate", "purity": 95.4}, "Feldspar": {"type": "Silicate", "purity": 88.1}, "Mica": {"type": "Silicate", "purity": 90.2} } # Function to calculate average purity of minerals def calculate_average_purity(mineral_dict): total_purity = sum(mineral["purity"] for mineral in mineral_dict.values()) number_of_minerals = len(mineral_dict) average_purity = total_purity / number_of_minerals return average_purity # Calculate average purity average_purity = calculate_average_purity(mineral_data) print(f"Average Purity: {average_purity}%") ``` Mastering data types and variables is pivotal to your journey in Python programming for natural resource extraction. From handling numeric data and text to leveraging collections for managing complex datasets, each element plays a crucial role in building robust analytical solutions. With a solid understanding of these fundamentals, you're well-prepared to dive deeper into Python's capabilities. The upcoming chapters will build upon this knowledge, guiding you through data preprocessing, advanced visualization, and machine learning techniques tailored to the unique challenges of environmental science and resource management. Embrace these tools, and set forth on your path to becoming an adept Python programmer in the ever- evolving field of natural resource extraction.
- 32. Conditional Statements and Loops Nestled within the vibrant streets of Vancouver, where the ebb and flow of people resonate with the rhythm of the city, we draw a parallel to the concept of control flow in programming. In Python, control flow structures like conditional statements and loops govern the execution of code, similar to how traffic lights and signals guide the movement of vehicles and pedestrians. Understanding Conditional Statements Conditional statements enable your program to make decisions and execute different blocks of code based on specified conditions. This powerful feature allows your program to adapt to varying scenarios, making it more dynamic and responsive. The if Statement The if statement is the cornerstone of conditional logic in Python. It evaluates a condition, and if the condition is true, it executes the block of code indented under it. ```python # Example of an if statement temperature = 25 if temperature > 20: print("It's a warm day.") ``` In this example, the message "It's a warm day." is printed only if the temperature exceeds 20 degrees. The else Statement Sometimes, you need to execute a different block of code when the condition is false. This is where the else statement
- 33. comes into play. ```python # Example of if-else statement temperature = 15 if temperature > 20: print("It's a warm day.") else: print("It's a cool day.") ``` In this case, if the temperature is 15, the message "It's a cool day." will be printed. The elif Statement When multiple conditions need to be checked, the elif (short for else if) statement can be used. It allows for more complex decision-making by chaining together multiple conditions. ```python # Example of if-elif-else statement temperature = 30 if temperature > 30: print("It's a hot day.") elif temperature > 20: print("It's a warm day.") else: print("It's a cool day.") ``` Here, the conditions are evaluated in sequence. If none of the conditions are true, the else block is executed. Nested Conditional Statements It's also possible to nest conditional statements within each other to handle more complex scenarios. ```python # Example of nested if statements temperature = 25 humidity = 80 if temperature > 20: if humidity > 50: print("It's a warm and humid day.") else: print("It's a warm and dry day.") else: print("It's a cool day.")
- 34. ``` In this example, the nested if statement checks the humidity level only if the temperature is greater than 20 degrees. Introduction to Loops Loops are fundamental in programming for performing repetitive tasks efficiently. In Python, there are primarily two types of loops: for loops and while loops. These structures help automate repetitive processes, reducing manual effort and the likelihood of errors. For Loops The for loop iterates over a sequence (such as a list, tuple, or string) and executes a block of code for each item in the sequence. This is particularly useful for processing datasets in natural resource extraction. ```python # Example of a for loop minerals = ["Quartz", "Feldspar", "Mica"] for mineral in minerals: print(mineral) ``` In this example, each item in the minerals list is printed. Using the range() Function The range() function generates a sequence of numbers, which is often used with for loops. ```python # Example of a for loop with range() for i in range(5): print(i) ``` This loop prints numbers from 0 to 4. While Loops
- 35. The while loop continues executing a block of code as long as a specified condition is true. This allows for more flexible and complex looping behavior. ```python # Example of a while loop count = 0 while count < 5: print(count) count += 1 # Increment the count ``` Here, the loop prints numbers from 0 to 4, incrementing count each time until the condition count < 5 is no longer true. Practical Example: Analyzing Mineral Data Let's combine conditional statements and loops in a practical example. Imagine you're working with mineral data and need to categorize minerals based on their purity levels. ```python # List of minerals with their purity levels minerals = [ {"name": "Quartz", "purity": 95.4}, {"name": "Feldspar", "purity": 88.1}, {"name": "Mica", "purity": 90.2}, {"name": "Amphibole", "purity": 76.5} ] # Categorize minerals based on purity for mineral in minerals: if mineral["purity"] > 90: category = "High purity" elif mineral["purity"] > 80: category = "Medium purity" else: category = "Low purity" print(f"{mineral['name']} is categorized as {category}.") ``` In this example, each mineral is categorized based on its purity level, and the result is printed. Mastering conditional statements and loops is essential for performing more sophisticated and automated tasks in
- 36. Python programming. These control flow constructs enable your code to make decisions, repeat actions, and handle complex scenarios effortlessly. As you progress in your journey through Python, these skills will prove invaluable, allowing you to build robust and efficient solutions for natural resource extraction and beyond. Functions and Modules In the tranquil embrace of Vancouver’s urban gardens, where the buzzing of bees and the rustling of leaves create a melody of nature’s own, we find a metaphor for the structure and organization in Python programming: functions and modules. Much like how each plant and insect has a particular role in the ecosystem, functions and modules in Python serve unique purposes, streamlining code, enhancing reusability, and fostering maintainability. Understanding Functions Functions in Python are blocks of reusable code that perform a specific task. They encapsulate logic, allowing you to call them multiple times throughout your program without rewriting the same code. This not only reduces redundancy but also enhances clarity and efficiency. Defining a Function A function is defined using the def keyword, followed by the function name and parentheses. The code block within the function is indented. ```python # Example of defining a function def greet(name): print(f"Hello, {name}!") ```
- 37. In this example, the greet function takes one parameter, name, and prints a greeting message. Calling a Function To execute a function, you call it by its name followed by parentheses, passing any required arguments. ```python # Calling the greet function greet("Reef") ``` This will output: Hello, Reef! Function Parameters and Arguments Functions can accept multiple parameters, which are specified within the parentheses in the function definition. Arguments are the actual values passed to these parameters when calling the function. ```python # Function with multiple parameters def add(a, b): return a + b # Calling the add function result = add(5, 3) print(result) # Outputs: 8 ``` Default Parameters You can assign default values to parameters, making them optional when calling the function. ```python # Function with a default parameter def greet(name, greeting="Hello"): print(f"{greeting}, {name}!")
- 38. # Calling the greet function with and without the default parameter greet("Reef") # Outputs: Hello, Reef! greet("Reef", "Hi") # Outputs: Hi, Reef! ``` Returning Values Functions can return values using the return statement, allowing you to capture and use the result in your code. ```python # Function returning a value def multiply(a, b): return a * b # Calling the function and using the returned value result = multiply(4, 5) print(result) # Outputs: 20 ``` Lambda Functions Lambda functions, also known as anonymous functions, are small, single-expression functions defined using the lambda keyword. These are often used for short operations or as arguments to higher-order functions. ```python # Example of a lambda function square = lambda x: x ** 2 # Using the lambda function print(square(5)) # Outputs: 25 ``` Modules in Python Modules are files containing Python code — variables, functions, classes — which can be imported into other Python programs. They help in organizing code into manageable sections, promoting modularity.
- 39. Creating a Module A module is simply a Python file with a .py extension. For example, let's create a module named mymodule.py. ```python # mymodule.py def greet(name): print(f"Hello, {name}!") def add(a, b): return a + b ``` Importing a Module To use a module, you import it into your script using the import statement. ```python # Example of importing a module import mymodule # Calling functions from the module mymodule.greet("Reef") # Outputs: Hello, Reef! result = mymodule.add(5, 3) print(result) # Outputs: 8 ``` Importing Specific Functions You can import specific functions or variables from a module using the from...import statement. ```python # Importing specific functions from a module from mymodule import greet, add # Calling the imported functions greet("Reef") # Outputs: Hello, Reef! result = add(5, 3) print(result) # Outputs: 8
- 40. ``` Using Aliases Aliases can be assigned to modules or functions to simplify usage. ```python # Using aliases import mymodule as mm from mymodule import greet as g # Calling the aliased functions mm.greet("Reef") # Outputs: Hello, Reef! g("Reef") # Outputs: Hello, Reef! ``` Practical Example: Building a Rainfall Analysis Module Imagine you are tasked with analyzing rainfall data to identify patterns and predict future trends. You can encapsulate this functionality in a module named rainfall.py. ```python # rainfall.py def average_rainfall(data): return sum(data) / len(data) def max_rainfall(data): return max(data) def min_rainfall(data): return min(data) ``` You can then import and use this module in your script. ```python # Main script import rainfall # Sample rainfall data rainfall_data = [23.4, 45.6, 12.1, 34.5, 22.3, 31.4] # Calling functions from the rainfall module avg = rainfall.average_rainfall(rainfall_data)
- 41. max_rf = rainfall.max_rainfall(rainfall_data) min_rf = rainfall.min_rainfall(rainfall_data) print(f"Average Rainfall: {avg} mm") print(f"Maximum Rainfall: {max_rf} mm") print(f"Minimum Rainfall: {min_rf} mm") ``` Functions and modules are the building blocks of efficient Python programming. They enable you to write clean, modular, and reusable code, essential for tackling the complex challenges of natural resource extraction. With functions, you can encapsulate and reuse logic, while modules allow you to organize your code into logical sections, making it easier to manage and maintain. By mastering these concepts, you’re not just writing code; you’re crafting well-structured programs that can evolve and scale with your projects. As we move forward in this journey, these skills will underpin our efforts, whether we are predicting resource availability, analyzing environmental impacts, or optimizing extraction processes. Embrace the power of functions and modules, and you’ll be well- equipped to create innovative, sustainable solutions in natural resource management. Working with Libraries and Packages As the fog rolls in over Vancouver's Coal Harbour, shrouding the skyline in a grey mist, the city’s vibrant spirit remains undeterred. Just like the diverse and dynamic ecosystem of this coastal city, Python’s libraries and packages offer a rich and versatile toolkit for solving a myriad of challenges in natural resource extraction. These libraries and packages are essential for extending Python’s capabilities, providing specialized functions, and streamlining complex processes.
- 42. Understanding Libraries and Packages In Python, a library is a collection of pre-written code that you can use to perform common tasks. Libraries can consist of modules, which are single Python files containing classes, functions, and variables, and packages, which are directories containing multiple modules and a special __init__.py file to treat the directory as a unit. Packages can further include sub-packages, creating a nested structure that mimics Vancouver's intricate urban layout. This modular approach makes it easier to manage, maintain, and scale your codebase. Installing Libraries and Packages Python’s package manager, pip, is the go-to tool for installing libraries and packages. Using pip, you can install, upgrade, and uninstall packages from the Python Package Index (PyPI), a repository of software for Python programming. Installing with pip To install a package, you use the pip install command followed by the package name. ```bash pip install numpy ``` This command will download and install the latest version of NumPy, a fundamental package for numerical computations.
- 43. Key Libraries for Natural Resource Extraction Several Python libraries are particularly valuable for natural resource extraction, each serving a unique purpose. We will explore some of the most critical libraries and provide practical examples to illustrate their applications. NumPy: Numerical Operations NumPy provides support for arrays, matrices, and numerous mathematical functions. It forms the foundation for many higher-level scientific libraries. ```python import numpy as np # Creating a NumPy array data = np.array([1, 2, 3, 4, 5]) # Performing operations on arrays mean = np.mean(data) std_dev = np.std(data) print(f"Mean: {mean}, Standard Deviation: {std_dev}") ``` NumPy’s n-dimensional array object is akin to the glistening glass towers that define Vancouver’s skyline — versatile, robust, and foundational. Pandas: Data Manipulation Pandas is indispensable for data manipulation and analysis, providing data structures like DataFrames, which are perfect for handling heterogeneous data. ```python import pandas as pd
- 44. # Creating a DataFrame data = {'Year': [2018, 2019, 2020], 'Rainfall': [1005.8, 1036.1, 987.6]} df = pd.DataFrame(data) # Performing operations on DataFrame mean_rainfall = df['Rainfall'].mean() print(f"Mean Rainfall: {mean_rainfall} mm") ``` Pandas empowers you to manage data as efficiently as Vancouver’s public transport system navigates its streets. Matplotlib and Seaborn: Data Visualization Matplotlib and Seaborn are powerful libraries for data visualization. While Matplotlib provides comprehensive 2D plotting capabilities, Seaborn builds on Matplotlib to provide a high-level interface for drawing attractive and informative statistical graphics. ```python import matplotlib.pyplot as plt import seaborn as sns # Creating a plot with Matplotlib plt.plot([1, 2, 3], [4, 5, 6]) plt.title('Simple Plot') plt.show() # Creating a plot with Seaborn sns.set(style="whitegrid") data = sns.load_dataset("iris") sns.boxplot(x=data["species"], y=data["sepal_length"]) plt.show() ```
- 45. These libraries help visualize data patterns, much like the iconic Capilano Suspension Bridge offers breathtaking views of Vancouver’s natural beauty. GeoPandas: Geospatial Data GeoPandas extends Pandas to handle geospatial data, essential for tasks involving map projections and geometry operations. ```python import geopandas as gpd # Reading a shapefile world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres')) # Plotting the geospatial data world.plot() plt.show() ``` GeoPandas turns complex geospatial data into insightful visualizations, akin to how Vancouver’s Seawall offers a panoramic view of the city’s picturesque landscape. Scikit-learn: Machine Learning Scikit-learn is a robust library for implementing machine learning algorithms. It provides tools for model selection, preprocessing, and various supervised and unsupervised learning algorithms. ```python from sklearn.linear_model import LinearRegression # Sample data X = [[1], [2], [3], [4]] y = [2, 3, 5, 7]
- 46. # Creating and fitting the model model = LinearRegression() model.fit(X, y) # Making predictions predictions = model.predict([[5]]) print(f"Prediction for input 5: {predictions[0]}") ``` Scikit-learn enables powerful machine learning applications, much like how Vancouver’s tech scene is driving innovation with AI and data science. Creating and Using Custom Packages Creating custom packages allows you to organize your code logically, making it reusable and easier to maintain. Consider an example where you create a package named resource_analysis with modules for different types of analysis. Directory Structure resource_analysis/ __init__.py rainfall.py geological.py rainfall.py ```python def average_rainfall(data): return sum(data) / len(data) def max_rainfall(data): return max(data) def min_rainfall(data): return min(data) ```
- 47. geological.py ```python def analyze_rock_composition(data): return {'Silicon': 60, 'Oxygen': 25, 'Iron': 15} ``` Using the Custom Package ```python # Main script from resource_analysis import rainfall, geological # Sample data rainfall_data = [23.4, 45.6, 12.1, 34.5, 22.3, 31.4] # Using functions from the custom package avg = rainfall.average_rainfall(rainfall_data) rock_comp = geological.analyze_rock_composition(None) print(f"Average Rainfall: {avg} mm") print(f"Rock Composition: {rock_comp}") ``` Practical Example: Automating Data Analysis with Libraries To demonstrate the real-world application of libraries and packages, let’s build a script that combines functionalities from NumPy, Pandas, and Matplotlib to analyze and visualize rainfall data trends over several years. ```python import numpy as np import pandas as pd import matplotlib.pyplot as plt
- 48. # Sample data: Yearly rainfall in mm years = np.arange(2000, 2021) rainfall = np.random.rand(21) * 800 + 200 # Random data for illustration # Creating a DataFrame df = pd.DataFrame({'Year': years, 'Rainfall': rainfall}) # Calculating rolling mean df['RollingMean'] = df['Rainfall'].rolling(window=3).mean() # Plotting the data plt.plot(df['Year'], df['Rainfall'], label='Annual Rainfall') plt.plot(df['Year'], df['RollingMean'], label='3-Year Rolling Mean', linestyle='--') plt.xlabel('Year') plt.ylabel('Rainfall (mm)') plt.title('Yearly Rainfall Trends') plt.legend() plt.show() ``` Working with libraries and packages in Python is akin to navigating the multifaceted, vibrant culture of Vancouver. Each library brings unique capabilities, much like the city's diverse neighborhoods, from the historical charm of Gastown to the modern ethos of Yaletown. By mastering these tools, you amplify the power of your Python programs, making it possible to tackle complex challenges in natural resource extraction efficiently and effectively. As you continue on this journey, remember that just like the interconnected streets and communities of Vancouver, Python libraries and packages work best when integrated harmoniously to create a seamless, powerful analytical toolkit. Input and Output Handling
- 49. The Essentials of Input and Output Handling I/O handling in Python involves the transfer of data to and from the external environment of your program. This can include reading data from files, writing data to files, and interacting with user input or external databases. Vancouver'smarkets, where goods are constantly exchanged, mirror the critical flows of data and information in a Python program. Reading from Files Reading data from external files is a common task in natural resource extraction workflows. Python’s built-in functions allow you to read data from various formats, including text files, CSV files, and JSON files. Reading Text Files Text files are straightforward and often used for storing simple data or logs. The open function is used to open a file and the read method reads its contents. ```python # Opening and reading a text file with open('example.txt', 'r') as file: data = file.read() print(data) ``` Using the with statement ensures that the file is properly closed after its suite finishes, similar to how the winding paths of Stanley Park always lead you back to where you started. Reading CSV Files
- 50. CSV (Comma-Separated Values) files are widely used for tabular data. The Pandas library simplifies the process of reading and manipulating CSV files. ```python import pandas as pd # Reading a CSV file df = pd.read_csv('data.csv') print(df.head()) ``` Just as the vibrant Granville Island Market organizes its myriad offerings, DataFrames in Pandas provide a clear structure to complex datasets. Reading JSON Files JSON (JavaScript Object Notation) is a popular format for structured data. Python's built-in json module facilitates reading JSON files. ```python import json # Reading a JSON file with open('data.json', 'r') as file: data = json.load(file) print(data) ``` Handling JSON data in Python can be equated to navigating through the intricate trails of the North Shore Mountains — detailed and structured. Writing to Files Writing data to files is equally important for saving processed information, logs, or outputs of analyses.
- 51. Writing Text Files Similar to reading, writing to text files uses the open function with the write method. ```python # Writing to a text file with open('output.txt', 'w') as file: file.write("Hello, world!") ``` This operation can be likened to the serene act of writing postcards at a café in Kitsilano, capturing the essence of your work to share with others. Writing CSV Files Pandas also streamlines the process of writing DataFrames to CSV files. ```python # Writing a DataFrame to a CSV file df.to_csv('output.csv', index=False) ``` The CSV file's clean, tabular format is as inviting as a well- laid-out plan of Queen Elizabeth Park. Writing JSON Files Using the json module, you can write structured data to JSON files. ```python # Writing to a JSON file with open('output.json', 'w') as file: json.dump(data, file) ``` Creating JSON files is like assembling a detailed guidebook on Vancouver’s cultural festivals — organized and informative.
- 52. Handling Standard Input and Output Beyond files, Python allows interaction with the user through standard input and output (stdin and stdout). This is often used in scripts requiring user prompts or command- line utilities that process parameters. Using input for User Interaction The input function reads a line of input from the user. ```python # User input example name = input("Enter your name: ") print(f"Hello, {name}!") ``` Interacting with users through command-line inputs is reminiscent of engaging conversations with locals at the Trout Lake Farmers Market — direct and personal. Redirecting Standard Output Standard output can be redirected to a file for logging purposes, useful in long-running scripts or data pipelines. ```python import sys # Redirecting stdout to a file with open('log.txt', 'w') as file: sys.stdout = file print("Logging this message to a file.") sys.stdout = sys.__stdout__ # Reset stdout back to console ``` This technique is like keeping a journal of your exploratory hikes through Pacific Spirit Regional Park — documenting every step of the journey.
- 53. Interacting with Databases In natural resource extraction, data often resides in databases. Python’s libraries enable seamless interaction with both SQL and NoSQL databases. SQL Databases with SQLite SQLite is a lightweight, disk-based database. The sqlite3 module in Python provides tools to manage SQLite databases. ```python import sqlite3 # Connecting to SQLite database connection = sqlite3.connect('example.db') cursor = connection.cursor() # Creating a table cursor.execute('''CREATE TABLE IF NOT EXISTS resources (id INTEGER PRIMARY KEY, name TEXT, quantity INTEGER)''') # Inserting data cursor.execute("INSERT INTO resources (name, quantity) VALUES ('Gold', 100)") # Querying data cursor.execute("SELECT * FROM resources") rows = cursor.fetchall() for row in rows: print(row) # Committing changes and closing the connection connection.commit() connection.close() ``` Interacting with SQLite is like organizing the records at the Vancouver Maritime Museum — precise and historical.
- 54. NoSQL Databases with MongoDB MongoDB is a popular NoSQL database suited for handling large volumes of unstructured data. The pymongo library facilitates interaction with MongoDB. ```python from pymongo import MongoClient # Connecting to MongoDB client = MongoClient('localhost', 27017) db = client['resource_db'] collection = db['resources'] # Inserting a document collection.insert_one({'name': 'Silver', 'quantity': 50}) # Querying documents documents = collection.find() for doc in documents: print(doc) ``` Handling NoSQL databases with MongoDB is akin to exploring the eclectic mix of exhibits at the Museum of Anthropology, where each document reveals its unique story. Practical Example: Comprehensive I/O Handling To encapsulate the concepts discussed, let’s develop a script that reads a CSV file containing resource extraction data, processes it, and writes the results to a JSON file. ```python import pandas as pd import json
- 55. Random documents with unrelated content Scribd suggests to you:
- 56. The boy of fourteen, with his indomitable energy, was already leading his equally indomitable father into different fields of action. He never rested from his studies in natural history. When not walking through quivering bogs or actually shooting bird and beast, he, surrounded by the brown-faced and curious sailors, would seat himself on the deck of the dahabeah and skin and stuff the products of his sport. I well remember the excitement, and, be it confessed, anxiety and fear inspired in the hearts of the four young college men who, on another dahabeah, accompanied us on the Nile, when the ardent young sportsman, mounted on an uncontrollable donkey, would ride unexpectedly into their midst, his gun slung across his shoulders in such a way as to render its proximity distinctly dangerous as he bumped absent-mindedly against them. When not actually hunting he was willing to take part in exploration of the marvellous old ruins. In a letter to “Edie” I say: “The other day we arrived at Edfoo, and we all went to see the temple together. While we were there Teedie, Ellie, Iesi (one of our sailors), and I started to explore. We went into a little dark room and climbed in a hole which was in the middle of the wall. The boys had candles. It was dark, crawling along the passage doubled up. At last we came to a deep hole, into which Teedie dropped, and we found out it was a mummy pit. It didn’t go very far in, but it all seemed very exciting to us to be exploring mummy pits. Sometimes we sail head foremost and sometimes the current turns us all the way around—and I wish you could hear the cries of the sailors when anything happens.” They were busy days, for our wise parents insisted upon regularity of a certain kind, and my older sister, only just eighteen, gave us lessons in both French and English in the early morning before we went on the wonderful excursions to the great temples, or before “Teedie” was allowed to escape for his shooting expeditions. I do not think the three months’ absence from school was any detriment, and I am very grateful for the stimulating interest which that trip on the Nile gave to my brothers and me. I can still see in retrospect, as if it were yesterday, the great temple of Karnak as we visited it by moon-light; the majestic colossi at Medinet Haboo; and the more beautiful and delicate ruins of Philæ. Often my father would read Egyptian history to
- 57. us or explain the kind of architecture which we were seeing; but always interspersed with more serious instruction were merry walks and games and wonderful picnic excursions, so that the winter on the Nile comes back to me as one of romantic interest mixed with the usual fun and cheerful intercourse of our ordinary family life. The four young men who had chartered the dahabeah Rachel were Messrs. Nathaniel Thayer and Frank Merriam of Boston, Augustus Jay of New York, and Harry Godey of Philadelphia, and these four friends, with the addition of other acquaintances whom we frequently met, made for my sister and my parents a delightful circle, into which we little ones were welcomed in a most gracious way. In spite of the fact of the charms of the Nile and the fun we frequently had, I write on February 1, from Thebes, to my little playmate “Edie,” with rather melancholy reminiscence of a more congenial past: “My own darling Edie,” I say, “don’t you remember what fun we used to have out in the country, and don’t you remember the day we got Pony Grant up in the Chauncey’s summer house and couldn’t get him down again, and how we always were losing Teedie’s india rubber shoes? I remember it so perfectly, and what fun it was!” I evidently feel that such adventures were preferable to those in which we were indulging in far-away Egypt, although I conscientiously describe the ear on one of the colossi at Medinet Haboo as being four feet high, and the temple, I state, with great accuracy, has twelve columns at the north and ten on either side! I seem, however, to be glad to come back from that expedition to Medinet Haboo, for I state that I wish she could see our dahabeah, which is a regular little home. I don’t approve—in this same letter—of the dancing-girls, which my parents allowed me to see one evening. With early Victorian criticism I state that “there is not a particle of grace in their motions, for they only wriggle their bodies like a snake,” and that I really felt they were “very unattractive”—thus proving that the little girl of eleven in 1873 was more or less prim in her tastes. I delight, however, in a poem which I copy for “Edie,” the first phrase of which has rung in my ears for many a long day.
- 58. “Alas! must I say it, fare-farewell to thee, Mysterious Egypt, great land of the flea, And thy Thebaic temples, Luxor and Karnac, Where the natives change slowly from yellow to black. Shall I ne’er see thy plain, so fraught with renown, Where the shadoofs go up and the shadoofs go down, Which two stalwart natives bend over and sing, While their loins are concealed by a simple shoe string.” This verse, in spite of the reference to the lack of clothes of the stalwart natives, evidently did not shock my sensibilities as much as the motions of the dancing-girls. Farther on in the letter I describe the New Year’s Eve party, and how Mr. Merriam sang a song which I (Conie) liked very much, and which was called “She’s Naughty But So Nice.” “Teedie,” however, did not care for that song, but preferred one called “Aunt Dinah,” because one verse ran: “My love she am a giraffe, a two-humped camamile.” [Music had apparently only charms to soothe him when suggestive of his beloved animal studies.] From Thebes also my brother writes to his aunt one of the most interesting letters of his boyhood: Near Kom Obos, Jan. 26th, 1873. Dear Aunt Annie: My right hand having recovered from the imaginary attack from which it did not suffer, I proceed to thank you for your kind present, which very much delighted me. We are now on the Nile and have been on that great and mysterious river for over a month. I think I have never enjoyed myself so much as in this month. There has always been something to do, for we could always fall back upon shooting when everything else failed us. And then we had those splendid and grand old ruins to see, and one of them will stock you with thoughts for a month. The temple that I enjoyed most was Karnak. We saw it by moonlight. I never was impressed by anything so much. To wander among those great columns under the same moon that
- 59. had looked down on them for thousands of years was awe- inspiring; it gave rise to thoughts of the ineffable, the unutterable; thoughts which you cannot express, which cannot be uttered, which cannot be answered until after The Great Sleep. [Here the little philosopher breaks off and continues in less serious mood on February 9.] I have had great enjoyment from the shooting here, as I have procured between one and two hundred skins. I expect to procure some more in Syria. Inform Emlen of this. As you are probably aware, Father presented me on Christmas with a double-barrelled breech loading shot gun, which I never move on shore without, excepting on Sundays. The largest bird I have yet killed is a Crane which I shot as it rose from a lagoon near Thebes. The sporting is injurious to my trousers.... Now that I am on the subject of dress I may as well mention that the dress of the inhabitants up to ten years of age is nothing. After that they put on a shirt descended from some remote ancestor, and never take it off till the day of their death. Mother is recovering from an attack of indigestion, but the rest are all well and send love to you and our friends, in which I join sincerely, and remain, Your Most Affectionate Nephew, T. Roosevelt, Jr. The adoration of his little sister for the erudite “Teedie” is shown in every letter, especially in the letters to their mutual little friend “Edie.” On January 25 this admiration is summed up in a postscript which says: “Teedie is out shooting now. He is quite professionist [no higher praise could apparently be given than this remarkable word] in shooting, skinning and stuffing, and he is so satisfied.” This expression seems to sum up the absolute sense of well-being during that
- 60. wonderful winter of the delicate boy, who, in spite of his delicacy, always achieved his heart’s desire. In the efforts of his little sister to be a worthy companion, I find in my diary, written that same winter of the Nile, one abortive struggle on my own part to become a naturalist. On the page at the end of my journal I write in large letters: NATURAL HISTORY “QUAIL “Ad. near Alexandria, Egypt, November 27th, 1872. Length 5—Expanse 13.0 Wings 5 Tail 1.3—Bill 5. Tarsus 1.2 Middle Toe 1.1 Hind Toe .3.” Under these mystic signs is a more elaborate and painstaking description of the above bird. I can see my brother now giving me a serious lecture on the subject, and trying to inspire a mind at that time securely closed to all such interests—to open at least a crack of its reluctant door, for “Teedie” felt that to walk with blind eyes in a world of such fluttering excitement as was made for him by the birds of the air showed an innate depravity which he wished with all his soul to cure in his beloved little sister. At the end of my description of the quail I fall by the wayside, and only once again make an excursion into the natural history of the great land of Egypt; only once more do I struggle with the description of a bird called this time by the curious name of “Ziczac.” (Could this be “Zigzag,” or was it simply my childish mind that zigzagged in its painful efforts to follow the impossible trail of my elder brother?) In my account of this, to say the least, unusual bird I remark: “Tarsus not finished.” Whether I have not finished the tarsus, or whether the bird itself had an arrested development of some kind, I do not explain; and on the blank page opposite this final effort in scientific adventure I finish, as I began, by the words “Natural History,” and underneath them, to explain my own unsuccessful efforts, I write: “My Brother, Theodore Roosevelt, Esq.” Whether I had decided that all natural history was summed up in that magic name, or
- 61. whether from that time on I was determined to leave all natural history to my brother, Theodore Roosevelt, Esq., I do not know; but the fact remains that from that day to this far distant one I have never again dipped into the mystery of mandibles and tarsi. * * * * * And so the sunny, happy days on the great river passed away. A merry eighteenth-birthday party in January for my sister Anna took the form of a moonlight ride to the great temple of Karnak, and, although we younger ones, naturally tired frequently of the effort to understand history and hieroglyphics, and turned with joy even in the shadow of the grand columns of Abydos to the game of “Buzz,” still I can say with truth that the easily moulded and receptive minds of the three little children responded to the atmosphere of the great river with its mighty past, and all through the after-years the interest aroused in those early days stimulated their craving for knowledge about the land of the Pharaohs. On our way down the river an incident occurred which, in a sense, was also memorable. At Rhoda on our return from the tombs of Beni Hasan we found that a dahabeah had drawn up near ours, on which were the old sage Ralph Waldo Emerson and his daughter. My father, who never lost a chance of bringing into the lives of his children some worth-while memory, took us all to see the old poet, and I often think with pleasure of the lovely smile, somewhat vacant, it is true, but very gentle, with which he received the little children of his fellow countryman. It was at this time that the story was told in connection with Mr. Emerson that some sentimental person said: “How wonderful to think of Emerson looking at the Sphinx! What a message the Sphinx must have had for Emerson.” Whereupon an irreverent wit replied: “The only message the Sphinx could possibly have had for Emerson must have been ‘You’re another.’” I can quite understand now, remembering the mystic, dreamy face of the old philosopher, how this witticism came about.
- 62. * * * * * And now the Nile trip was over and we were back again in Cairo, and planning for the further interest of a trip through the Holy Land. Mr. Thayer and Mr. Jay, two of the young friends who had accompanied us on the Nile, decided to join our party, and after a short stay in Cairo we again left for Alexandria and thence sailed for Jaffa. In my diary I write at the Convent of Ramleh between Jaffa and Jerusalem, where we spent our first night: “In Jaffa we chose our horses, which was very exciting, and started on our long ride. After three hours of delightful riding through a great many green fields, we reached this convent and found they had no room for ladies, because they were not allowed to go into one part of the building as it was against the rules, but at last Father got the old monks to allow us to come into another part of the convent for just one night.” “Father,” like his namesake, almost always got what he wanted. From that time on one adventure after another followed. I write of many nice gallops, and of my horse lying down in the middle of streams; and, incidentally with less interest, of the Mount of Olives and the Church of the Holy Sepulchre! Antonio Sapienza proved to be an admirable dragoman, and always the practical part of the tenting cavalcade started early in the morning, and therefore as the rest of us rode over the hills in the later afternoon we would see arranged cosily in some beautiful valley the white tents, with the curling smoke from the kitchen-tent already rising with the promise of a delightful dinner. Over Jordan we went, and what a very great disappointment Jordan was to our childish minds, which had always pictured a broad river and great waves parting for the Ark of the Covenant to pass. This Jordan was a little stream hardly more impressive than the brook at our old home at Madison, and we could not quite accustom ourselves to the disappointment. But Jerusalem with its narrow streets and gates, its old churches, the high Mount of Olives, and the little town of Bethlehem not far away, and, even more interesting from the standpoint of beauty, the vision of the Convent of Mar Saba on the high hill not far from Hebron, and beyond all else the blue sparkling
- 63. waters of the Dead Sea, all remain in my memory as a wonderful panorama of romance and delight. Arab sheiks visited us frequently in the evening and brought their followers to dance for us, and wherever my father went he accumulated friends of all kinds and colors, and we, his children, shared in the marvellous atmosphere he created. I remember, in connection with the Dead Sea, that “Teedie” and Mr. Jay decided that they could sink in it, although the guides had warned them that the salt was so buoyant that it was impossible for any living thing to sink in the waters (the Dead Sea was about the most alive sea that I personally have ever seen), and so the two adventurous ones undertook to dive, and tried to remain under water. “Teedie” fortunately relinquished the effort almost immediately, but Mr. Jay, who in a spirit of bravado struggled to remain at the bottom, suffered the ill effects from crusted salt in eyes and ears for many hours after leaving the water. For about three weeks we rode through the Holy Land, and my memory of many flowers remains as one of the charms of that trip. Later, led in the paths of botany by a beloved friend, I often longed to go back to that land of flowers; but then to my childish eyes they meant nothing but beauty and delight. After returning to Jerusalem and Jaffa we took ship again and landed this time at Beyrout, and started on another camping-trip to Damascus, through perhaps the most beautiful scenery which we had yet enjoyed. During that trip also we had various adventures. I describe in my diary how my father, at one of our stopping-places, brought to our tents some beautiful young Arab girls, how they gave us oranges and nuts, and how cordially they begged us, when a great storm came up and our tents were blown away, to come for shelter to their quaint little houses. Even to the minds of the children of eleven and fourteen years of age, the great Temple of Baalbek proved a lure of beauty, and the diary sagely remarks that “It is quite as beautiful as Karnak, although in an entirely different way, as Baalbek has delicate columns, and Karnak great, massive columns.” The beauty, however, is not a matter
- 64. of such interest as the mysterious little subterranean passages, and I tell how “Teedie” helped me to climb the walls and little tower, and to crawl through these same unexplored dark places. The ride into Damascus itself remains still an expedition of glamour, for we reached the vicinity of the city by a high cliff, and the city burst upon us with great suddenness, its minarets stretching their delicate, arrow-like spires to the sky in so Oriental a fashion that even the practical hearts of the little American children responded with a thrill of excitement. Again, after an interesting stay in Damascus, we made our way back to Beyrout. While waiting for the steamer there my brother Elliott was taken ill, and writes in a homesick fashion to the beloved aunt to whom we confided all our joys and woes. Poor little boy! He says pathetically: “Oh, Auntie, you don’t know how I long for a finishing-up of this ever-lasting traveling, when we can once more sit down to breakfast, dinner and lunch in our own house. Since I have been sick and only allowed rice and chicken,—and very little of them— I have longed for one of our rice puddings, and a pot of that strawberry jam, and one of Mary’s sponge cakes, and I have thought of when I would go to your rooms for dinner and what jolly chops and potatoes and dessert I would get there, and when I would come to breakfast we would have buckwheat cakes. Perhaps I am a little homesick.” I am not so sure but what many an intelligent traveller, could his or her heart be closely examined, would find written upon it “lovely potatoes, chops and hot buckwheat cakes.” But all the same, in spite of “Ellie’s” rhapsody, off we started on another steamer, and my father writes on March 28, 1873: Steamer off Rhodes. Teedie is in great spirits, as the sailors have caught for him numerous specimens, which he stuffs on deck, to the edification of a large audience. I write during the same transit, after stopping at Athens, that “It is a very lovely town, and that I should have liked to stay there longer, but that was not to be.” I also decided that although the ruins were
- 65. beautiful, I did not like them as much as either Karnak or Baalbek. Having dutifully made these architectural criticisms, I turn with gusto to the fact that Tom and Fannie Lawrence, “Teedie,” “Ellie,” and I have such splendid games of tag on the different steamers, and that I know my aunt would have enjoyed seeing us. The tag was “con amore,” while the interest in the temples was, I fear, somewhat induced. Our comprehending mother and father, however, always allowed us joyous moments between educational efforts. In a letter from Constantinople written by “Ellie” on April 7, he says: “We have had Tom and Frank Lawrence here to dinner, and we had a splendid game of ‘muggins’ and tried to play eucre (I don’t know that this is rightly spelled) with five, but did not suceede, Teedie did make such mistakes. [Not such an expert in cards, you see, as in tarsi and mandibles!] But we were in such spirits that it made no difference, and we did nothing but shout at the top of our voices the battle cry of freedom; and the playing of a game of slapjack helped us get off our steam with hard slaps, but even then there was enough (steam) left in Teedie and Tom to have a candle fight and grease their clothes, and poor Frank’s and mine, who were doing nothing at all!” As one can see by this description, the learned and rather delicate “Teedie” was only a normal, merry boy after all. “Ellie” describes also the wonderful rides in Constantinople, and many other joys planned by our indulgent parents. From that same city, called because of its many steeples The City of Minarets, “Teedie” writes to his little friend Edith: I think I have enjoyed myself more this winter than I ever did before. Much to add to my enjoyment Father gave me a gun at Christmas, which rendered me happy and the rest of the family miserable. I killed several hundred birds with it, and then went and lost it! I think I enjoyed the time in Egypt most, and after that I had the most fun while camping out in Syria. While camping out we were on horseback for several hours of each day, and as I like riding ever so much, and as the Syrian horses are very good, we had a splendid time. While
- 66. riding I bothered the family somewhat by carrying the gun over my shoulder, and on the journey to the Jordan, when I was on the most spirited horse I ever rode, I bothered the horse too, as was evidenced by his running away several times when the gun struck him too hard. Our tent life had a good many adventures in it. Once it rained very hard and the rain went into our open trunks. Another time our tents were almost blown away in a rough wind, and once I hunted a couple of jackals for two or three miles as fast as the horse could go. Yours truly, T. Roosevelt, Jr. This little missive sums up the joy of “Teedie’s” winter in Egypt and Syria, and so it seems a fitting moment to turn to other interests and occupations, leaving the mysterious land of the pyramids and that sacred land of mountains and flowers behind us in a glow of child memories, which as year followed year became brighter rather than dimmer.
- 67. I III THE DRESDEN LITERARY AMERICAN CLUB MOTTO “W. A. N. A.” t was a sad change to the three young American children to settle in Dresden in two German families, after the care-free and stimulating experiences of Egypt and the Holy Land. Our wise parents, however, realized that a whole year of irregularity was a serious mistake in that formative period of our lives, and they also wished to leave no stone unturned to give us every educational advantage during our twelve months’ absence from home and country. It was decided, therefore, that the two boys should be placed in the family of Doctor and Mrs. Minckwitz, while I, a very lone and homesick small girl, was put with some kind but far too elderly people, Professor and Mrs. Wackernagel. This last arrangement was supposed to be advantageous, so that the brothers and sister should not speak too much English together. The kind old professor and his wife and the daughters, who seemed to the little girl of eleven years on the verge of the grave (although only about forty years of age), did all that was in their power to lighten the agonized longing in the child’s heart for her mother and sister, but to no avail, for I write to my mother, who had gone to Carlsbad for a cure: “I was perfectly miserable and very much unstrung when Aunt Lucy wrote to you that no one could mention your name or I would instantly begin to cry. Oh! Mother darling, sometimes I feel that I cannot stand it any longer but I am going to try to follow a motto which Father wrote to me, ‘Try to have the best time you can.’ I should be very sorry to disappoint Father but sometimes I feel as if I
- 68. could not stand it any longer. We will talk it over when you come. Your own little Conie.” Poor little girl! I was trying to be noble; for my father, who had been obliged to return to America for business reasons, had impressed me with the fact that to spend part of the summer in a German family and thus learn the language was an unusual opportunity, and one that must be seized upon. My spirit was willing, but my flesh was very, very weak, and the age of the kind people with whom I had been placed, the strange, dreadful, black bread, the meat that was given only as a great treat after it had been boiled for soup—everything, in fact, conduced to a feeling of great distance from the lovely land of buckwheat cakes and rare steak, not to mention the separation from the beloved brothers whom I was allowed to see only at rare intervals during the week. The consequence was that very soon my mother came back to Dresden in answer to the pathos of my letters, for I found it impossible to follow that motto, so characteristic of my father, “Try to have the best time you can.” I began to sicken very much as the Swiss mountaineers are said to lose their spirits and appetites when separated from their beloved mountains; so my mother persuaded the kind Minckwitz family to take me under their roof, as well as my brothers, and from that time forth there was no more melancholy, no bursting into poetic dirges constantly celebrating the misery of a young American in a German family. From the time that I was allowed to be part of the Minckwitz family everything seemed to be fraught with interest and many pleasures as well as with systematic good hard work. In these days, when the word “German” has almost a sinister sound in the ears of an American, I should like to speak with affectionate respect of that German family in which the three little American children passed several happy months. The members of the family were typically Teutonic in many ways: the Herr Hofsrath was the kindliest of creatures, and his rubicund, smiling wife paid him the most loving court; the three daughters—gay, well- educated, and very temperamental young women—threw themselves into the work of teaching us with a hearty good will, which met with real response from us, as that kind of effort invariably does. Our two cousins, the same little cousins who had shared the happy summer memories of Madison, New Jersey, when we were much younger, were
- 69. also in Dresden with their mother, Mrs. Stuart Elliott, the “Aunt Lucy” referred to frequently in our letters. Aunt Lucy was bravely facing the results of the sad Civil War, and her only chance of giving her children a proper education was to take them to a foreign country where the possibility of good schools, combined with inexpensive living, suited her depleted income. Her little apartment on Sunday afternoons was always open to us all, and there we, five little cousins formed the celebrated “D. L. A. C.” (Dresden Literary American Club!) On June 2 I wrote to my friend “Edie”: “We five children have gotten up a club and meet every Sunday at Aunt Lucy’s, and read the poetry and stories that we have written during the week. When the book is all done, we will sell the book either to mother or Aunt Annie and divide the money; (although on erudition bent, still of commercial mind!) I am going to write poetry all the time. My first poem was called ‘A Sunny Day in June.’ Next time I am going to give ‘The Lament of an American in a German Family.’ It is an entirely different style I assure you.” The “different style” is so very poor that I refrain from quoting that illustrious poem.
- 70. The Dresden Literary American Club—Motto, “W. A. N. A.” (“We Are No Asses”). From left to right: Theodore Roosevelt, aged 14¾ years; Elliott Roosevelt, aged 13½ years; Maud Elliott, aged 12¾ years; Corinne Roosevelt, aged 11¾ years; John Elliott, aged 14½ years. July 1, 1873. The work for the D. L. A. C. proved to be a very entertaining pastime, and great competition ensued. A motto was chosen by “Johnnie” and “Ellie,” who were the wits of the society. The motto was spoken of with bated breath and mysteriously inscribed W. A. N. A. underneath the mystic signs of D. L. A. C. For many a long year no one but those in our strictest confidence were allowed to know that “W. A. N. A.” stood for “We Are No Asses.” This, perhaps somewhat untruthful statement, was objected to originally by “Teedie,” who firmly maintained that the mere making of such a motto showed that “Johnnie” and “Ellie” were certainly exceptions that proved that rule. “Teedie” himself, struggling as usual with terrible attacks of asthma that perpetually undermined his health and strength, was all the same,
- 71. between the attacks, the ringleader in fun and gaiety and every imaginable humorous adventure. He was a slender, overgrown boy at the time, and wore his hair long in true German student fashion, and adopted a would-be philosopher type of look, effectively enhanced by trousers that were outgrown, and coat sleeves so short that they gave him a “Smike”-like appearance. His contributions to the immortal literary club were either serious and very accurate from a natural-historical standpoint, or else they showed, as comparatively few of his later writings have shown, the delightful quality of humor which, through his whole busy life, lightened for him every load and criticism. I cannot resist giving in full the fascinating little story called “Mrs. Field Mouse’s Dinner Party,” in which the personified animals played social parts, in the portrayal of which my brother divulged (my readers must remember he was only fourteen) a knowledge of “society” life, its acrid jealousies and hypocrisies, of which he never again seemed to be conscious. MRS. FIELD MOUSE’S DINNER PARTY By Theodore Roosevelt—Aged Fourteen “My Dear,” said Mrs. M. to Mr. M. one day as they were sitting on an elegant acorn sofa, just after breakfast, “My Dear, I think that we really must give a dinner party.” “A What, my love?” exclaimed Mr. M. in a surprised tone. “A Dinner Party”; returned Mrs. M. firmly, “you have no objections I suppose?” “Of course not, of course not,” said Mr. M. hastily, for there was an ominous gleam in his wife’s eye. “But—but why have it yet for a while, my love?” “Why indeed! A pretty question! After that odious Mrs. Frog’s great tea party the other evening! But that is just it, you never have any proper regard for your station in life, and on me involves all the duty of keeping up appearances, and after all this is the gratitude I get for it!” And Mrs. M. covered her eyes and fell into hysterics of 50 flea power. Of course, Mr. M. had to promise to have it whenever she liked. “Then the day after tomorrow would not be too early, I suppose?” “My Dear,” remonstrated the unfortunate Mr. M., but Mrs. M. did not heed him and continued: “You could get the
- 72. cheese and bread from Squeak, Nibble & Co. with great ease, and the firm of Brown House and Wood Rats, with whom you have business relations, you told me, could get the other necessaries.” “But in such a short time,” commenced Mr. M. but was sharply cut off by the lady; “Just like you, Mr. M.! Always raising objections! and when I am doing all I can to help you!” Symptoms of hysterics and Mr. M. entirely convinced, the lady continues: “Well, then we will have it the day after tomorrow. By the way, I hear that Mr. Chipmunck has got in a new supply of nuts, and you might as well go over after breakfast and get them, before they are bought by someone else.” “I have a business engagement with Sir Butterfly in an hour,” began Mr. M. but stopped, meekly got his hat and went off at a glance from Mrs. M.’s eye. When he was gone, the lady called down her eldest daughter, the charming Miss M. and commenced to arrange for the party. “We will use the birch bark plates,”—commenced Mrs. M. “And the chestnut ‘tea set,’” put in her daughter. “With the maple leaf vases, of course,” continued Mrs. M. “And the eel bone spoons and forks,” added Miss M. “And the dog tooth knives,” said the lady. “And the slate table cloth,” replied her daughter. “Where shall we have the ball anyhow,” said Mrs. M. “Why, Mr. Blind Mole has let his large subterranean apartments and that would be the best place,” said Miss M. “Sir Lizard’s place, ‘Shady Nook,’ which we bought the other day, is far better I think,” said Mrs. M. “But I don’t,” returned her daughter. “Miss M. be still,” said her mother sternly, and Miss M. was still. So it was settled that the ball was to be held at ‘Shady Nook.’
- 73. “As for the invitations, Tommy Cricket will carry them around,” said Mrs. M. “But who shall we have?” asked her daughter. After some discussion, the guests were determined on. Among them were all the Family of Mice and Rats, Sir Lizard, Mr. Chipmunck, Sir Shrew, Mrs. Shrew, Mrs. Bullfrog, Miss Katydid, Sir Grasshopper, Lord Beetle, Mr. Ant, Sir Butterfly, Miss Dragonfly, Mr. Bee, Mr. Wasp, Mr. Hornet, Madame Maybug, Miss Lady Bird, and a number of others. Messrs. Gloworm and Firefly agreed to provide lamps as the party was to be had at night. Mr. M., by a great deal of exertion, got the provisions together in time, and Miss M. did the same with the furniture, while Mrs. M. superintended generally, and was a great bother. Water Bug & Co. conveyed everything to Shady Nook, and so at the appointed time everything was ready, and the whole family, in their best ball dresses, waited for the visitors. * * * * * The fisrt visitor to arrive was Lady Maybug. “Stupid old thing; always first,” muttered Mrs. M., and then aloud, “How charming it is to see you so prompt, Mrs. Maybug; I can always rely on your being here in time.” “Yes Ma’am, oh law! but it is so hot—oh law! and the carriage, oh law! almost broke down; oh law! I did really think I never should get here—oh law!” and Mrs. Maybug threw herself on the sofa; but the sofa unfortunately had one weak leg, and as Mrs. Maybug was no light weight, over she went. While Mrs. M. (inwardly swearing if ever a mouse swore) hastened to her assistance, and in the midst of the confusion caused by this accident, Tommy Cricket (who had been hired for waiter and dressed in red trousers accordingly) threw open the door and announced in a shrill pipe, “Nibble Squeak & Co., Mum,” then hastily correcting himself, as he received a dagger like glance from Mrs. M., “Mr. Nibble and Mr. Squeak, Ma’am,” and precipitately retreated through the door. Meanwhile the unfortunate Messrs. Nibble and Squeak, who while trying to look easy in their new clothes, had luckily not heard the introduction,
- 74. were doing their best to bow gracefully to Miss Maybug and Miss Mouse, the respective mamas of these young ladies having pushed them rapidly forward as each of the ladies was trying to get up a match between the rich Mr. Squeak and her daughter, although Miss M. preferred Mr. Woodmouse and Miss Maybug, Mr. Hornet. In the next few minutes the company came pouring in (among them Mr. Woodmouse, accompanying Miss Katydid, at which sight Miss M. turned green with envy), and after a very short period the party was called in to dinner, for the cook had boiled the hickory nuts too long and they had to be sent up immediately or they would be spoiled. Mrs. M. displayed great generalship in the arrangement of the people, Mr. Squeak taking in Miss M., Mr. Hornet, Miss Maybug, and Mr. Woodmouse, Miss Katydid. But now Mr. M. had invited one person too many for the plates, and so Mr. M. had to do without one. At first this was not noticed, as each person was seeing who could get the most to eat, with the exception of those who were love-making, but after a while, Sir Lizard, (a great swell and a very high liver) turned round and remarked, “Ee-aw, I say, Mr. M., why don’t you take something more to eat?” “Mr. M. is not at all hungry tonight, are you my dear?” put in Mrs. M. smiling at Sir Lizard, and frowning at Mr. M. “Not at all, not at all,” replied the latter hastily. Sir Lizard seemed disposed to continue the subject, but Mr. Moth, (a very scientific gentleman) made a diversion by saying, “Have you seen my work on ‘Various Antenae’? In it I demonstrated clearly the superiority of feathered to knobbed Antenae and”—“Excuse me, Sir,” interrupted Sir Butterfly, “but you surely don’t mean to say—” “Excuse me, if you please,” replied Mr. Moth sharply, “but I do mean it, and if you read my work, you will perceive that the rays of feather-like particles on the trunk of the Antenae deriving from the center in straight or curved lines generally”—at this moment Mr. Moth luckily choked himself and seizing the lucky instant, Mrs. M. rang for the desert. There was a sort of struggling noise in the pantry, but that was the only answer. A second ring, no answer. A third ring; and
- 75. Mrs. M. rose in majestic wrath, and in dashed the unlucky Tommy Cricket with the cheese, but alas, while half way in the room, the beautiful new red trousers came down, and Tommy and cheese rolled straight into Miss Dragon Fly who fainted without any unnecessary delay, while the noise of Tommy’s howls made the room ring. There was great confusion immediately, and while Tommy was being kicked out of the room, and while Lord Beetle was emptying a bottle of rare rosap over Miss Dragon Fly, in mistake for water, Mrs. M. gave a glance at Mr. M., which made him quake in his shoes, and said in a low voice, “Provoking thing! now you see the good of no suspenders”—“But my dear, you told me not to”—began Mr. M., but was interrupted by Mrs. M. “Don’t speak to me, you—” but here Miss Katydid’s little sister struck in on a sharp squeak. “Katy kissed Mr. Woodmouse!” “Katy didn’t,” returned her brother. “Katy did,” “Katy didn’t,” “Katy did,” “Katy didn’t.” All eyes were now turned on the crimsoning Miss Katydid, but she was unexpectedly saved by the lamps suddenly commencing to burn blue! “There, Mr. M.! Now you see what you have done!” said the lady of the house, sternly. “My dear, I told you they could not get enough oil if you had the party so early. It was your own fault,” said Mr. M. worked up to desperation. Mrs. M. gave him a glance that would have annihilated three millstones of moderate size, from its sharpness, and would have followed the example of Miss Dragon Fly, but was anticipated by Madame Maybug, who, as three of the lamps above her went out, fell into blue convulsions on the sofa. As the whole room was now subsiding into darkness, the company broke up and went off with some abruptness and confusion, and when they were gone, Mrs. M. turned (by the light of one bad lamp) an eagle eye on Mr. M. and said—, but we will now draw a curtain over the harrowing scene that ensued and say, “Good Bye.”
- 76. “Teedie” not only indulged in the free play of fancy such as the above, but wrote with extraordinary system and regularity for a boy of fourteen to his mother and father, and perhaps these letters, written in the far-away Dresden atmosphere, show more conclusively than almost any others the character, the awakening mind, the forceful mentality of the young and delicate boy. On May 29, in a letter to his mother, a very parental letter about his homesick little sister who had not yet been taken from the elderly family in which she was so unhappy, he drops into a lighter vein and says: “I have overheard a good deal of Minckwitz conversation which they did not think I understood; Father was considered ‘very pretty’ (sehr hübsch) and his German ‘exceedingly beautiful,’ neither of which statements I quite agree with.” And a week or two later, writing to his father, he describes, after referring casually to a bad attack of asthma, an afternoon of tag and climbing trees, supper out in the open air, and long walks through the green fields dotted with the blue cornflowers and brilliant red poppies. True to his individual tastes, he says: “When I am not studying my lessons or out walking I spend all my time in translating natural history, wrestling with Richard, a young cousin of the Minckwitz’ whom I can throw as often as he throws me, and I also sometimes cook, although my efforts in the culinary art are really confined to grinding coffee, beating eggs or making hash, and such light labors.” Later he writes again: “The boxing gloves are a source of great amusement; you ought to have seen us after our ‘rounds’ yesterday.” The foregoing “rounds” were described even more graphically by “Ellie” in a letter to our uncle, Mr. Gracie, as follows: “Father, you know, sent us a pair of boxing gloves apiece and Teedie, Johnnie, and I have had jolly fun with them. Last night in a round of one minute and a half with Teedie, he got a bloody nose and I got a bloody mouth, and in a round with Johnnie, I got a bloody mouth again and he a pair of purple eyes. Then Johnnie gave Teedie another bloody nose. [The boys by this time seemed to have multiplied their features indefinitely with more purple eyes!] We do enjoy them so! Boxing is one of Teedie’s and my favorite amusements; it is such a novelty to be made to see stars when it is not night.” No wonder that later “Ellie” contributed what I called in one of my later letters a “tragical” article called “Bloody Hand” for the D. L. A. C., perhaps engendered by the memory of all those bloody mouths and noses!
- 77. “Teedie” himself, in writing to his Aunt Annie, describes himself as a “bully boy with a black eye,” and in the same letter, which seems to be in answer to one in which this devoted aunt had described an unusual specimen to interest him, he says: “Dear darling little Nancy: I have received your letter concerning the wonderful animal and although the fact of your having described it as having horns and being carnivorous has occasioned me grave doubts as to your veracity, yet I think in course of time a meeting may be called by the Roosevelt Museum and the matter taken into consideration, although this will not happen until after we have reached America. The Minckwitz family are all splendid but very superstitious. My scientific pursuits cause the family a good deal of consternation. “My arsenic was confiscated and my mice thrown (with the tongs) out of the window. In cases like this I would approach a refractory female, mouse in hand, corner her, and bang the mouse very near her face until she was thoroughly convinced of the wickedness of her actions. Here is a view of such a scene.
- 78. I am getting along very well with German and studying really hard. Your loving T. R., Secretary and Librarian of Roosevelt Museum. (Shall I soon hail you as a brother, I mean sister member of the Museum?)” Evidently the carnivorous animal with horns was a stepping-stone to membership in the exclusive Roosevelt Museum! The Dresden memories include many happy excursions, happy in spite of the fact that they were sometimes taken because of poor “Teedie’s” severe attacks of asthma. On June 29th he writes his father: “I have a conglomerate of good news and bad news to report to you; the former far outweighs the latter, however. I am at present suffering from a slight attack of asthma. However, it is only a small attack and except for the fact that I cannot speak without blowing like an abridged hippopotamus, it does not inconvenience me very much. We are now studying hard and everything is systematized. Excuse my writing, the
- 79. asthma has made my hand tremble awfully.” The asthma of which he makes so light became unbearable, and the next letter, on June 30 from the Bastei in Saxon Switzerland, says: “You will doubtless be surprised at the heading of this letter, but as the asthma did not get any better, I concluded to come out here. Elliott and Corinne and Fräulein Anna and Fräulein Emma came with me for the excursion. We started in the train and then got out at a place some distance below these rocks where we children took horses and came up here, the two ladies following on foot. The scenery on the way and all about here was exceedingly bold and beautiful. All the mountains, if they deserve the name of mountains, have scarcely any gradual decline. They descend abruptly and precipitously to the plain. In fact, the sides of the mountains in most parts are bare while the tops are covered with pine forests with here and there jagged conical peaks rising from the foliage. There are no long ranges, simply a number of sharp high hills rising from a green fertile plain through which the river Elbe wanders. You can judge from this that the scenery is really magnificent. I have been walking in the forests collecting butterflies. I could not but be struck with the difference between the animal life of these forests and the palm groves of Egypt, (auld lang syne now). Although this is in one of the wildest parts of Saxony and South Germany, yet I do not think the proportion is as much as one here for twenty there or around Jericho, and the difference in proportion of species is even greater,—still the woods are by no means totally devoid of inhabitants. Most of these I had become acquainted with in Syria, and a few in Egypt. The only birds I had not seen before were a jay and a bullfinch.” The above letter shows how true the boy was to his marked tastes and his close observation of nature and natural history! After his return from the Bastei my brother’s asthma was somewhat less troublesome, and, to show the vital quality which could never be downed, I quote a letter from “Ellie” to his aunt: “Suddenly an idea has got hold of Teedie that we did not know enough German for the time that we have been here, so he has asked Miss Anna to give him larger lessons and of course I could not be left behind so we are working harder than ever in our lives.” How unusual the evidence of leadership is in this young boy of not yet fifteen, who already inspires his pleasure-
- 80. loving little brother to work “harder than ever before in our lives.” Many memories crowd back upon me as I think of those days in the kind German family. The two sons, Herr Oswald and Herr Ulrich, would occasionally return from Leipsig where they were students, and always brought with them an aroma of duels and thrilling excitement. Ulrich, in college, went by the nickname of “Der Rothe Herzog,” The Red Duke, the appellation being applied to him on account of his scarlet hair, his equally rubicund face, and a red gash down the left side of his face from the sword of an antagonist. Oswald had a very extraordinary expression due to the fact that the tip end of his nose had been nearly severed from his face in one of these same, apparently, every-day affairs, and the physician who had restored the injured feature to its proper environment had made the mistake of sewing it a little on the bias, which gave this kind and gentle young man a very sinister expression. In spite of their practice in the art of duelling and a general ferocity of appearance, they were sentimental to the last extent, and many a time when I have been asked by Herr Oswald and Herr Ulrich to read aloud to them from the dear old books “Gold Elsie” or “Old Mam’selle’s Secret,” they would fall upon the sofa beside me and dissolve in tears over any melancholy or romantic situation. Their sensibilities and sentimentalities were perfectly incomprehensible to the somewhat matter-of-fact and distinctly courageous trio of young Americans, and while we could not understand the spirit which made them willing, quite casually, to cut off each other’s noses, we could even less understand their lachrymose response to sentimental tales and their genuine terror should a thunder-storm occur. “Ellie” describes in another letter how all the family, in the middle of the night, because of a sudden thunder-storm, crawled in between their mattresses and woke the irrelevant and uninterested small Americans from their slumbers to incite them to the same attitude of mind and body. His description of “Teedie” under these circumstances is very amusing, for he says: “Teedie woke up only for one minute, turned over and said, ‘Oh—it’s raining and my hedgehog will be all spoiled.’” He was speaking of a hedgehog that he had skinned the day before and hung out of his window, but even his hedgehog did not keep him awake and, much to the surprise of the frightened Minckwitz family, he fell back into a heavy sleep.
- 81. In spite of the sentimentalities, in spite of the racial differences of attitude about many things, the American children owe much to the literary atmosphere that surrounded the family life of their kind German friends. In those days in Dresden the most beautiful representations of Shakespeare were given in German, and, as the hour for the theatre to begin was six o’clock in the evening, and the plays were finished by nine o’clock, many were the evenings when we enjoyed “Midsummer Night’s Dream,” “Twelfth Night,” “The Taming of the Shrew,” and many more of Shakespeare’s wonderful fanciful creations, given as they were with unusual sympathy and ability by the actors of the German Theatre. Perhaps because of our literary studies and our ever-growing interest in our own efforts in the famous Dresden Literary American Club, we decided that the volume which became so precious to us should, after all, have no commercial value, and in July I write to my aunt the news which I evidently feel will be a serious blow to her—that we have decided that we cannot sell the poems and stories gathered into that immortal volume! About the middle of the summer there was an epidemic of smallpox in Dresden and my mother hurriedly took us to the Engadine, and there, at Samaden, we lived somewhat the life of our beloved Madison and Hudson River days. Our cousin John Elliott accompanied us, and the three boys and their ardent little follower, myself, spent endless happy hours in climbing the surrounding mountains, only occasionally recalled by the lenient “Fräulein Anna” to what were already almost forgotten Teutonic studies. Later we returned to Dresden, and in spite of the longing in our patriotic young hearts to be once more in the land of the Stars and Stripes, I remember that we all parted with keen regret from the kind family who had made their little American visitors so much at home.
- 83. FACSIMILE OF THEODORE ROOSEVELT’S LETTER OF SEPTEMBER 21, 1873, TO HIS OLDER SISTER A couple of letters from Theodore, dated September 21 and October 5, bring to a close the experiences in Dresden, and show in a special way the boy’s humor and the original inclination to the quaint drawings which have become familiar to the American people through the book, lately published, called “Theodore Roosevelt’s Letters to His Children.” On September 21, 1873, he writes to his older sister: “My dear darling Bamie,—I wrote a letter on the receipt of yours, but Corinne lost it and
- 84. so I write this. Health; good. Lessons; good. Play hours; bad. Appetite; good. Accounts; good. Clothes; greasy. Shoes; holey. Hair; more ‘a-la- Mop’ than ever. Nails; dirty, in consequence of having an ink bottle upset over them. Library; beautiful. Museum; so so. Club; splendid. Our journey home from Samaden was beautiful, except for the fact that we lost our keys but even this incident was not without its pleasing side. I reasoned philosophically on the subject; I said: ‘Well, everything is for the best. For example, if I cannot use my tooth brush tonight, at least, I cannot forget it to-morrow morning. Ditto with comb and night shirt.’ In these efforts of high art, I have taken particular care to imitate truthfully the Chignons, bustles, grease-spots, bristles, and especially my own mop of hair. The other day I much horrified the female portion of the Minckwitz Tribe by bringing home a dead bat. I strongly suspect that they thought I intended to use it as some sorcerer’s charm to injure a foe’s constitution, mind and appetite. As I have no more news to write, I will close with some illustrations on the Darwinian theory. Your brother —Teedie.” The last letter, on October 5, was to his mother, and reads in part as follows: “Corinne has been sick but is now well, at least, she does not have the same striking resemblance to a half-starved raccoon as she did in the severe stages of the disease.” After a humorous description of a German conversation between several members of his aunt’s family, he proceeds to “further illustrations of the Darwinian theory” and closes his letter by signing himself “Your affectionate son, Cranibus Giraffinus.”
- 85. FACSIMILE OF “SOME ILLUSTRATIONS ON THE DARWINIAN THEORY,” CONTAINED IN THE LETTER OF SEPTEMBER 21, 1873 Shortly before leaving Dresden I had my twelfth birthday and the Minckwitz clan made every effort to make it a gay festival, but perhaps the gift which I loved best was a letter received that very morning from my beloved father; and in closing this brief account of those days spent in Germany, because of his wise decision to broaden our young horizons
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