Reading Rows from a CSV File in Python

CSV stands for Comma Separated Values. This file format is a delimited text file that uses a comma as a delimiter to separate the text present in it. Or in other words, CSV files are used to store data in tabular form. As per the name suggested, this file contains the data which is separated by a comma and every line of a file is considered a record. We can create the CSV file either from notepad or using excel. 

Example:

Geeks,for,geeks
one,of,the,
top,learning,platform

We can create a CSV file using the following ways:

1. Using Notepad: We can create a CSV file using Notepad. In the Notepad, open a new file in which separate the values by comma and save the file with .csv extension.

2. Using Excel: We can also create a CSV file using Excel. In Excel, open a new file in which specify each value in a different cell and save it with filetype CSV.

To read data row-wise from a CSV file in Python, we can use reader and DictReader which are present in the CSV module allows us to fetch data row-wise.

Using reader

Using reader we can iterate between rows of a CSV file as a list of values. It iterates over all rows in a CSV file and fetches data in each row as a list. reader() method is present in CSV library. So to use this reader method, first we need to import the CSV library. reader object accepts a single parameter called fileObject (a variable that holds the CSV file). 

Syntax:

csv.reader(fileobject)

Steps to read CSV file:

Step 1: In order to read rows in Python, First, we need to load the CSV file in one object. So to load the csv file into an object use open() method.

with open('filename') as fileObject

While loading the file by specifying path along with filename, if you got any unicode error then append r before path of filename

with open(r'path/filename') as fileObject 

Step 2: Create a reader object by passing the above-created file object to the reader function.

reader_obj = csv.reader(file_obj)

Step 3: Use for loop on reader object to get each row.

Example:

Consider a CSV file named "samplecsv.csv". This file contains the following data:

Id,Name,Rating
1,Akhil,4
2,Babu,3
3,Nikhil,5

# Python program to read CSV file line by line
# import necessary packages
import csv

# Open file 
with open('samplecsv.csv') as file_obj:
    
    # Create reader object by passing the file 
    # object to reader method
    reader_obj = csv.reader(file_obj)
    
    # Iterate over each row in the csv 
    # file using reader object
    for row in reader_obj:
        print(row)

Output:

['Id', 'Name', 'Rating']
['1', 'Akhil', '4']
['2', 'Babu', '3']
['3', 'Nikhil', '5']

Reading CSV file without header

Everything is fine with the above example but if we don't want column names to fetch or we can say we don't want to read the header of the file, then we use the next() method on the file object before creating the reader object so that it skips the headings.

# Python program to read CSV file without header

# Import necessary packages
import csv

# Open file
with open('samplecsv.csv') as file_obj:
    
    # Skips the heading
    # Using next() method
    heading = next(file_obj)
    
    # Create reader object by passing the file 
    # object to reader method
    reader_obj = csv.reader(file_obj)
    
    # Iterate over each row in the csv file 
    # using reader object
    for row in reader_obj:
        print(row)

Output:

['1', 'Akhil', '4']
['2', 'Babu', '3']
['3', 'Nikhil', '5']

Explanation: The above code is almost the same as the code in the above example but a slight change is we use the next function here that helps us to skip the column names while accessing data from a CSV file i.e. first row. If column names are required then we access them from the heading object i.e. return the result of the next method.

Using DictReader

When using a reader() method we can iterate over a CSV file as a list but using the DictReader class object we can iterate over a CSV file row by row as a dictionary. This DictReader method is present in the csv library. So to use it first we need to import the csv library. DictReader() accepts a single parameter called fileObject (a variable that holds the csv file). 

Syntax

csv.DictReader(fileobject)

Steps to read CSV file:

Step 1: Load the CSV file using the open method in a file object.

with open('filename') as fileObject

Step 2: Create a reader object with the help of DictReader method using fileobject.

reader_obj = csv.DictReader(file_obj)

This reader object is also known as an iterator can be used to fetch row-wise data.

Step 3: Use for loop on reader object to get each row.

Example:

# Python3 program to read CSV file using DictReader

# Import necessary packages
import csv

# Open file
with open('samplecsv.csv') as file_obj:
    
    # Create reader object by passing the file
    # object to DictReader method
    reader_obj = csv.DictReader(file_obj)
    
    # Iterate over each row in the csv file
    # using reader object
    for row in reader_obj:
        print(row)

Output:

OrderedDict([('Id', '1'), ('Name', 'Akhil'), ('Rating', '4')])
OrderedDict([('Id', '2'), ('Name', 'Babu'), ('Rating', '3')])
OrderedDict([('Id', '3'), ('Name', 'Nikhil'), ('Rating', '5')])

Explanation: In the code, first we loaded the CSV file named samplecsv.csv and then created a reader_object that can be iterated to fetch each row. The returned result is in the form of Key-Value pair indicates it as a dictionary. So using DictReader we read data row by row as a Dictionary.