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:
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)