Get the number of rows and number of columns in Pandas Dataframe

Last Updated : 02 Jul, 2020

Pandas provide data analysts a variety of pre-defined functions to Get the number of rows and columns in a data frame. In this article, we will learn about the syntax and implementation of few such functions.

Method 1: Using df.axes() Method

axes() method in pandas allows to get the number of rows and columns in a go. It accepts the argument ‘0’ for rows and ‘1’ for columns.

Syntax: df.axes[0 or 1]

Parameters:
0: for number of Rows
1: for number of columns

Example:

   # import pandas library 
import pandas as pd 
    
# dictionary with list object in values 
details = { 
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'], 
    'Age' : [23, 21, 22, 21], 
    'University' : ['BHU', 'JNU', 'DU', 'BHU'], 
} 
    
# creating a Dataframe object  
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'],\ 
                  index = ['a', 'b', 'c', 'd']) 
    
# Get the number of rows and columns 
rows = len(df.axes[0]) 
cols = len(df.axes[1]) 
  
# Print the number of rows and columns 
print("Number of Rows: " + str(rows)) 
print("Number of Columns: " + str(cols)) 
 
  

Output:

  Number of Rows: 4  Number of Columns: 3

Method 2: Using df.info() Method

df.info() method provides all the information about the data frame, including the number of rows and columns.

Syntax:

df.info

Example:

   # import pandas library 
import pandas as pd 
    
# dictionary with list object in values 
details = { 
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'], 
    'Age' : [23, 21, 22, 21], 
    'University' : ['BHU', 'JNU', 'DU', 'BHU'], 
} 
    
# creating a Dataframe object  
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'], 
                  index = ['a', 'b', 'c', 'd']) 
    
# Get the info of data frame 
df.info() 
 
  

Output:

python-pandas-rows-and-number-of-columns

Here in the above code, the value in the Index gives the number of rows and the value in Data columns gives the number of columns.

Method 3: Using len() Method

len() method is used to get the number of rows and number of columns individually.

Syntax:

len(df)  and  len(df.columns)

Example 1: Get the number of rows

   # import pandas library 
import pandas as pd 
    
# dictionary with list object in values 
details = { 
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'], 
    'Age' : [23, 21, 22, 21], 
    'University' : ['BHU', 'JNU', 'DU', 'BHU'], 
} 
    
# creating a Dataframe object  
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'], 
                  index = ['a', 'b', 'c', 'd']) 
    
# Get the number of rows 
print("Number of Rows:", len(df)) 
 
  

Output:

  Number of Rows: 4

Example 2: Get the number of columns

   # import pandas library 
import pandas as pd 
    
# dictionary with list object in values 
details = { 
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'], 
    'Age' : [23, 21, 22, 21], 
    'University' : ['BHU', 'JNU', 'DU', 'BHU'], 
} 
    
# creating a Dataframe object  
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'], 
                  index = ['a', 'b', 'c', 'd']) 
    
# Get the number of columns 
print("Number of Columns:", len(df.columns)) 
 
  

Output:

  Number of Columns: 3

Method 4: Using df.shape() Method

df.shape() method returns the number of rows and columns in the form of a tuple.

Example:

   # import pandas library 
import pandas as pd 
    
# dictionary with list object in values 
details = { 
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'], 
    'Age' : [23, 21, 22, 21], 
    'University' : ['BHU', 'JNU', 'DU', 'BHU'], 
} 
    
# creating a Dataframe object  
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'], 
                  index = ['a', 'b', 'c', 'd']) 
    
# Get the number of Rows and columns 
df.shape 
 
  

Output:

(4, 3)

Count the number of rows and columns of Pandas dataframe

Akanksha_Rai

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Get the number of rows and number of columns in Pandas Dataframe

Method 1: Using df.axes() Method

Method 2: Using df.info() Method

Method 3: Using len() Method

Method 4: Using df.shape() Method

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