Python For Data Science Cheat Sheet
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The document serves as a cheat sheet for Python basics, covering variable assignments, data types, list operations, and NumPy array functionalities. It includes syntax examples for string and list manipulation, as well as mathematical operations using NumPy. Additionally, it emphasizes the use of libraries and provides a variety of methods for data handling and analysis.
![Selecting List Elements
Import libraries
>>> import numpy
>>> import numpy as np
Selective import
>>> from math import pi
>>> help(str)
PythonForDataScience Cheat Sheet
Python Basics
Learn More Python for Data Science Interactively at www.datacamp.com
Variable Assignment
Strings
>>> x=5
>>> x
5
>>> x+2 Sum of two variables
7
>>> x-2 Subtraction of two variables
3
>>> x*2 Multiplication of two variables
10
>>> x**2 Exponentiation of a variable
25
>>> x%2 Remainder of a variable
1
>>> x/float(2) Division of a variable
2.5
Variables and Data Types
str() '5', '3.45', 'True'
int() 5, 3, 1
float() 5.0, 1.0
bool() True, True, True
Variables to strings
Variables to integers
Variables to floats
Variables to booleans
Lists
>>> a = 'is'
>>> b = 'nice'
>>> my_list = ['my', 'list', a, b]
>>> my_list2 = [[4,5,6,7], [3,4,5,6]]
Subset
>>> my_list[1]
>>> my_list[-3]
Slice
>>> my_list[1:3]
>>> my_list[1:]
>>> my_list[:3]
>>> my_list[:]
Subset Lists of Lists
>>> my_list2[1][0]
>>> my_list2[1][:2]
Also see NumPy Arrays
>>> my_list.index(a)
>>> my_list.count(a)
>>> my_list.append('!')
>>> my_list.remove('!')
>>> del(my_list[0:1])
>>> my_list.reverse()
>>> my_list.extend('!')
>>> my_list.pop(-1)
>>> my_list.insert(0,'!')
>>> my_list.sort()
Get the index of an item
Count an item
Append an item at a time
Remove an item
Remove an item
Reverse the list
Append an item
Remove an item
Insert an item
Sort the list
Index starts at 0
Select item at index 1
Select 3rd last item
Select items at index 1 and 2
Select items after index 0
Select items before index 3
Copy my_list
my_list[list][itemOfList]
Libraries
>>> my_string.upper()
>>> my_string.lower()
>>> my_string.count('w')
>>> my_string.replace('e', 'i')
>>> my_string.strip()
>>> my_string = 'thisStringIsAwesome'
>>> my_string
'thisStringIsAwesome'
Numpy Arrays
>>> my_list = [1, 2, 3, 4]
>>> my_array = np.array(my_list)
>>> my_2darray = np.array([[1,2,3],[4,5,6]])
>>> my_array.shape
>>> np.append(other_array)
>>> np.insert(my_array, 1, 5)
>>> np.delete(my_array,[1])
>>> np.mean(my_array)
>>> np.median(my_array)
>>> my_array.corrcoef()
>>> np.std(my_array)
Asking For Help
>>> my_string[3]
>>> my_string[4:9]
Subset
>>> my_array[1]
2
Slice
>>> my_array[0:2]
array([1, 2])
Subset 2D Numpy arrays
>>> my_2darray[:,0]
array([1, 4])
>>> my_list + my_list
['my', 'list', 'is', 'nice', 'my', 'list', 'is', 'nice']
>>> my_list * 2
['my', 'list', 'is', 'nice', 'my', 'list', 'is', 'nice']
>>> my_list2 > 4
True
>>> my_array > 3
array([False, False, False, True], dtype=bool)
>>> my_array * 2
array([2, 4, 6, 8])
>>> my_array + np.array([5, 6, 7, 8])
array([6, 8, 10, 12])
>>> my_string * 2
'thisStringIsAwesomethisStringIsAwesome'
>>> my_string + 'Innit'
'thisStringIsAwesomeInnit'
>>> 'm' in my_string
True DataCamp
Learn Python for Data Science Interactively
Scientific computing
Data analysis
2D plotting
Machine learning
Also see Lists
Get the dimensions of the array
Append items to an array
Insert items in an array
Delete items in an array
Mean of the array
Median of the array
Correlation coefficient
Standard deviation
String to uppercase
String to lowercase
Count String elements
Replace String elements
Strip whitespace from ends
Select item at index 1
Select items at index 0 and 1
my_2darray[rows, columns]
Install Python
Calculations With Variables
Leading open data science platform
powered by Python
Free IDE that is included
with Anaconda
Create and share
documents with live code,
visualizations, text, ...
Types and Type Conversion
String Operations
List Operations
List Methods
Index starts at 0
String Methods
String Operations
Selecting Numpy Array Elements Index starts at 0
Numpy Array Operations
Numpy Array Functions](https://image.slidesharecdn.com/pythonfordatascience-161122115831/85/Python-For-Data-Science-Cheat-Sheet-1-320.jpg)
Python For Data Science Cheat Sheet
- 1. Selecting List Elements Import libraries >>> import numpy >>> import numpy as np Selective import >>> from math import pi >>> help(str) PythonForDataScience Cheat Sheet Python Basics Learn More Python for Data Science Interactively at www.datacamp.com Variable Assignment Strings >>> x=5 >>> x 5 >>> x+2 Sum of two variables 7 >>> x-2 Subtraction of two variables 3 >>> x*2 Multiplication of two variables 10 >>> x**2 Exponentiation of a variable 25 >>> x%2 Remainder of a variable 1 >>> x/float(2) Division of a variable 2.5 Variables and Data Types str() '5', '3.45', 'True' int() 5, 3, 1 float() 5.0, 1.0 bool() True, True, True Variables to strings Variables to integers Variables to floats Variables to booleans Lists >>> a = 'is' >>> b = 'nice' >>> my_list = ['my', 'list', a, b] >>> my_list2 = [[4,5,6,7], [3,4,5,6]] Subset >>> my_list[1] >>> my_list[-3] Slice >>> my_list[1:3] >>> my_list[1:] >>> my_list[:3] >>> my_list[:] Subset Lists of Lists >>> my_list2[1][0] >>> my_list2[1][:2] Also see NumPy Arrays >>> my_list.index(a) >>> my_list.count(a) >>> my_list.append('!') >>> my_list.remove('!') >>> del(my_list[0:1]) >>> my_list.reverse() >>> my_list.extend('!') >>> my_list.pop(-1) >>> my_list.insert(0,'!') >>> my_list.sort() Get the index of an item Count an item Append an item at a time Remove an item Remove an item Reverse the list Append an item Remove an item Insert an item Sort the list Index starts at 0 Select item at index 1 Select 3rd last item Select items at index 1 and 2 Select items after index 0 Select items before index 3 Copy my_list my_list[list][itemOfList] Libraries >>> my_string.upper() >>> my_string.lower() >>> my_string.count('w') >>> my_string.replace('e', 'i') >>> my_string.strip() >>> my_string = 'thisStringIsAwesome' >>> my_string 'thisStringIsAwesome' Numpy Arrays >>> my_list = [1, 2, 3, 4] >>> my_array = np.array(my_list) >>> my_2darray = np.array([[1,2,3],[4,5,6]]) >>> my_array.shape >>> np.append(other_array) >>> np.insert(my_array, 1, 5) >>> np.delete(my_array,[1]) >>> np.mean(my_array) >>> np.median(my_array) >>> my_array.corrcoef() >>> np.std(my_array) Asking For Help >>> my_string[3] >>> my_string[4:9] Subset >>> my_array[1] 2 Slice >>> my_array[0:2] array([1, 2]) Subset 2D Numpy arrays >>> my_2darray[:,0] array([1, 4]) >>> my_list + my_list ['my', 'list', 'is', 'nice', 'my', 'list', 'is', 'nice'] >>> my_list * 2 ['my', 'list', 'is', 'nice', 'my', 'list', 'is', 'nice'] >>> my_list2 > 4 True >>> my_array > 3 array([False, False, False, True], dtype=bool) >>> my_array * 2 array([2, 4, 6, 8]) >>> my_array + np.array([5, 6, 7, 8]) array([6, 8, 10, 12]) >>> my_string * 2 'thisStringIsAwesomethisStringIsAwesome' >>> my_string + 'Innit' 'thisStringIsAwesomeInnit' >>> 'm' in my_string True DataCamp Learn Python for Data Science Interactively Scientific computing Data analysis 2D plotting Machine learning Also see Lists Get the dimensions of the array Append items to an array Insert items in an array Delete items in an array Mean of the array Median of the array Correlation coefficient Standard deviation String to uppercase String to lowercase Count String elements Replace String elements Strip whitespace from ends Select item at index 1 Select items at index 0 and 1 my_2darray[rows, columns] Install Python Calculations With Variables Leading open data science platform powered by Python Free IDE that is included with Anaconda Create and share documents with live code, visualizations, text, ... Types and Type Conversion String Operations List Operations List Methods Index starts at 0 String Methods String Operations Selecting Numpy Array Elements Index starts at 0 Numpy Array Operations Numpy Array Functions