Pandas DataFrame.shape

Pandas DataFrame.shape

The DataFrame.shape property in pandas is used to retrieve the dimensions of a DataFrame. It returns a tuple containing the number of rows and columns in the DataFrame.

Syntax

The syntax for accessing the shape property is:

DataFrame.shape

Here, DataFrame refers to the pandas DataFrame whose dimensions are being accessed.

Returns

A tuple of two integers:

  • The first integer represents the number of rows.
  • The second integer represents the number of columns.

Examples

Getting the Shape of a DataFrame

You can use the shape property to get the number of rows and columns in a DataFrame.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Priya'],
    'Age': [25, 30, 35],
    'Salary': [70000.5, 80000.0, 90000.0]
}
df = pd.DataFrame(data)

# Get the shape of the DataFrame
print("Shape of the DataFrame:")
print(df.shape)

Output

Shape of the DataFrame:
(3, 3)

Using the Shape to Access Rows and Columns

You can use the shape property to dynamically access rows and columns.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Priya'],
    'Age': [25, 30, 35],
    'Salary': [70000.5, 80000.0, 90000.0]
}
df = pd.DataFrame(data)

# Use shape to access the number of rows and columns
num_rows, num_columns = df.shape
print("Number of Rows:", num_rows)
print("Number of Columns:", num_columns)

Output

Number of Rows: 3
Number of Columns: 3

Working with an Empty DataFrame

For an empty DataFrame, the shape property returns (0, 0) if there are no rows and columns.

Python Program

import pandas as pd

# Create an empty DataFrame
df_empty = pd.DataFrame()

# Get the shape of the empty DataFrame
print("Shape of the Empty DataFrame:")
print(df_empty.shape)

Output

Shape of the Empty DataFrame:
(0, 0)

Filtering Data and Checking Shape

You can use the shape property to check the size of a DataFrame after filtering rows.

Python Program

import pandas as pd

# Create a DataFrame
data = {
    'Name': ['Arjun', 'Ram', 'Priya'],
    'Age': [25, 30, 35],
    'Salary': [70000.5, 80000.0, 90000.0]
}
df = pd.DataFrame(data)

# Filter rows where Age > 25
filtered_df = df[df['Age'] > 25]

# Get the shape of the filtered DataFrame
print("Shape of the Filtered DataFrame:")
print(filtered_df.shape)

Output

Shape of the Filtered DataFrame:
(2, 3)

Summary

In this tutorial, we explored the DataFrame.shape property in pandas. Key points include:

  • Using shape to get the dimensions of a DataFrame
  • Understanding its usage for dynamic operations
  • Working with empty or filtered DataFrames

The DataFrame.shape property is a quick and efficient way to understand the size of your data and its structure.

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