Pandas and NumPy connection

Introduction

Pandas and NumPy work together to help you handle and analyze data easily. Pandas uses NumPy arrays inside to store data efficiently.

When you want to perform fast calculations on table data.

When you need to convert data between Pandas DataFrames and NumPy arrays.

When you want to use NumPy functions on Pandas data.

When you want to create Pandas objects from NumPy arrays.

When you want to access the raw data inside a Pandas DataFrame or Series.

Syntax

Pandas

import pandas as pd
import numpy as np

# Convert NumPy array to Pandas DataFrame
pd.DataFrame(arr)

# Convert Pandas DataFrame to NumPy array
dataframe.values

# Use NumPy functions on Pandas data
np.mean(dataframe['column'])

Pandas DataFrames and Series store data as NumPy arrays internally.

You can easily switch between Pandas and NumPy formats for flexibility.

Examples

This creates a Pandas DataFrame from a NumPy array.

Pandas

import numpy as np
import pandas as pd

arr = np.array([[1, 2], [3, 4]])
df = pd.DataFrame(arr)
print(df)

This extracts the NumPy array from a Pandas DataFrame.

Pandas

import pandas as pd

df = pd.DataFrame({'A': [10, 20], 'B': [30, 40]})
arr = df.values
print(arr)

This uses a NumPy function to calculate the mean of a DataFrame column.

Pandas

import numpy as np
import pandas as pd

df = pd.DataFrame({'A': [1, 2, 3]})
mean_val = np.mean(df['A'])
print(mean_val)

Sample Program

This program shows how to convert between NumPy arrays and Pandas DataFrames and use NumPy functions on Pandas data.

Pandas

import numpy as np
import pandas as pd

# Create a NumPy array
arr = np.array([[5, 10], [15, 20], [25, 30]])

# Convert NumPy array to Pandas DataFrame
df = pd.DataFrame(arr, columns=['X', 'Y'])

# Show the DataFrame
print('DataFrame from NumPy array:')
print(df)

# Convert DataFrame back to NumPy array
arr_back = df.values
print('\nNumPy array from DataFrame:')
print(arr_back)

# Use NumPy function on DataFrame column
mean_x = np.mean(df['X'])
print(f'\nMean of column X: {mean_x}')

Important Notes

Using df.values returns the underlying NumPy array of a DataFrame.

Many NumPy functions work directly on Pandas Series and DataFrames.

When converting, column names and indexes are lost if you only use NumPy arrays.

Summary

Pandas DataFrames use NumPy arrays to store data efficiently.

You can convert between Pandas and NumPy easily for flexible data analysis.

NumPy functions can be applied directly to Pandas data.