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Count the number of rows and columns of a Pandas dataframe
  • Last Updated : 28 Jul, 2020

Pandas allow us to get the shape of the dataframe by counting the numbers of rows and columns in the dataframe. You can try various approaches to get the number of rows and columns of the dataframe. All of them have been discussed below.

Example: Let’s take an example of a dataframe which consists of data of exam result of students.

# importing pandas 
import pandas as pd
result_data = {'name': ['Katherine', 'James', 'Emily',
                        'Michael', 'Matthew', 'Laura'],
        'score': [98, 80, 60, 85, 49, 92],
        'age': [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no',
                          'yes', 'no', 'yes']}
# creating dataframe
df = pd.DataFrame(result_data, index = None)
# computing number of rows
rows = len(df.axes[0])
# computing number of columns
cols = len(df.axes[1])
print("Number of Rows: ", rows)
print("Number of Columns: ", cols)

Output :

Example: Let’s take an example of a dataframe that consists of data on product sales.

# importing pandas 
import pandas as pd
# creating dataframe
df = pd.DataFrame({'Product' : ['Carrots', 'Broccoli', 'Banana'
                                'Banana', 'Beans', 'Orange',
                                'Broccoli', 'Banana'],
                   'Category' : ['Vegetable', 'Vegetable', 'Fruit'
                                 'Fruit', 'Vegetable', 'Fruit'
                                 'Vegetable', 'Fruit'],
                   'Quantity' : [8, 5, 3, 4, 5, 9, 11, 8],
                   'Amount' : [270, 239, 617, 384, 626, 610, 62, 90]})
# getting number of rows
print("Number of Rows: ", len(df.axes[0]))
# getting number of columns
print("Number of Columns: ", len(df.axes[1]))

Output :

Example: Here, we will try a different approach for calculating rows and columns of a dataframe of imported csv file.

# importing pandas
import pandas as pd
# importing csv file
# obtaining the shape
print("shape of dataframe", df.shape)
# obtaining the number of rows
print("number of rows : ", df.shape[0])
# obtaining the number of columns
print("number of columns : ", df.shape[1])

Output :

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