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Count the number of rows and columns of Pandas dataframe

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  • Last Updated : 01 Aug, 2020
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In this article, we’ll see how we can get the count of the total number of rows and columns in a Pandas DataFrame. There are different methods by which we can do this. Let’s see all these methods with the help of examples.

Example 1: We can use the dataframe.shape to get the count of rows and columns. dataframe.shape[0] and dataframe.shape[1] gives count of rows and columns respectively.




# importing the module
import pandas as pd
  
# creating a DataFrame
dict = {'Name' : ['Martha', 'Tim', 'Rob', 'Georgia'],
        'Marks' : [87, 91, 97, 95]}
df = pd.DataFrame(dict)
  
# displaying the DataFrame
display(df)
  
# fetching the number of rows and columns
rows = df.shape[0]
cols = df.shape[1]
  
# displaying the number of rows and columns
print("Rows: " + str(rows))
print("Columns: " + str(cols))

Output :

Example 2 : We can use the len() method to get the count of rows and columns. dataframe.axes[0] represents rows and dataframe.axes[1] represents columns. So, dataframe.axes[0] and dataframe.axes[1] gives the count of rows and columns respectively.




# importing the module
import pandas as pd
  
# creating a DataFrame
dict = {'Name':['Martha', 'Tim', 'Rob', 'Georgia'],
        'Marks':[87, 91, 97, 95]}
df = pd.DataFrame(dict)
  
# displaying the DataFrame
display(df)
  
# fetching the number of rows and columns
rows = len(df.axes[0])
cols = len(df.axes[1])
  
# displaying the number of rows and columns
print("Rows: " + str(rows))
print("Columns: " + str(cols))

Output :

Example 3 : Similar to the example 2, dataframe.index represents rows and dataframe.columns represents columns. So, len(dataframe.index) and len(dataframe.columns) gives count of rows and columns respectively.




# importing the module
import pandas as pd
  
# creating a DataFrame
dict = {'Name':['Martha', 'Tim', 'Rob', 'Georgia'],
        'Marks':[87, 91, 97, 95]}
df = pd.DataFrame(dict)
  
# displaying the DataFrame
display(df)
  
# fetching the number of rows and columns
rows = len(df.index)
cols = len(df.columns)
  
# displaying the number of rows and columns
print("Rows: " + str(rows))
print("Columns: " + str(cols))

Output :


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