Pandas DataFrame: Count the number of rows and columns of a DataFrame

Last update on April 03 2025 13:08:12 (UTC/GMT +8 hours)

8. Counting Rows and Columns

Write a Pandas program to count the number of rows and columns of a DataFrame.

Sample DataFrame:
exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']

Sample Solution :-

Python Code :

import pandas as pd
import numpy as np
exam_data  = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
        'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
        'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
        'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
df = pd.DataFrame(exam_data , index=labels)
total_rows=len(df.axes[0])
total_cols=len(df.axes[1])
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Sample Output:

Number of Rows: 10                                                     
Number of Columns: 4                

Explanation:

The above code creates a pandas dataframe ‘df’ with the given data in ‘exam_data’ dictionary and assigns the labels to rows using labels list. Then it calculates the number of rows and columns in the dataframe using len(df.axes[0]) and len(df.axes[1]) respectively, and stores them in total_rows and total_cols variables.

Finally, it prints the number of rows and columns using these variables.

For more Practice: Solve these Related Problems:

• Write a Pandas program to count the number of rows and columns of a DataFrame and then print a formatted string showing both counts.
• Write a Pandas program to count rows and columns, then verify that the product equals the total number of elements in the DataFrame.
• Write a Pandas program to count the number of rows and columns and then check if any column has zero non-NaN values.
• Write a Pandas program to count rows and columns and then add these counts as new columns to an existing DataFrame.

Python-Pandas Code Editor:

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