How to create a DataFrame in Python?

A DataFrame is a 2D data structure in Pandas used to represent data in tabular format with rows and columns. It is similar to a spreadsheet or SQL table and is one of the most important data structures for data analysis in Python.

To create a DataFrame, we need to import pandas. A DataFrame can be created using the DataFrame() constructor function, which accepts data in various formats like dictionaries, lists, or arrays.

Create DataFrame from Dictionary of Lists

When using a dictionary, the keys become column names and values become the data ?

import pandas as pd

data = {'Name': ['Karan', 'Rohit', 'Sahil', 'Aryan'], 'Age': [23, 22, 21, 24]}

df = pd.DataFrame(data)

print(df)

    Name  Age
0  Karan   23
1  Rohit   22
2  Sahil   21
3  Aryan   24

Create DataFrame from List of Lists

When using a list of lists, you need to specify column names explicitly ?

import pandas as pd

data = [['Karan', 23], ['Rohit', 22], ['Sahil', 21], ['Aryan', 24]]

df = pd.DataFrame(data, columns=['Name', 'Age'])

print(df)

    Name  Age
0  Karan   23
1  Rohit   22
2  Sahil   21
3  Aryan   24

Create DataFrame with Custom Index

You can specify custom row labels using the index parameter ?

import pandas as pd

data = {'Name': ['Karan', 'Rohit', 'Sahil', 'Aryan'], 'Age': [23, 22, 21, 24]}

df = pd.DataFrame(data, index=['No.1', 'No.2', 'No.3', 'No.4'])

print(df)

      Name  Age
No.1  Karan   23
No.2  Rohit   22
No.3  Sahil   21
No.4  Aryan   24

Create DataFrame from NumPy Array

You can also create a DataFrame from NumPy arrays ?

import pandas as pd
import numpy as np

data = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

df = pd.DataFrame(data, columns=['A', 'B', 'C'])

print(df)

   A  B  C
0  1  2  3
1  4  5  6
2  7  8  9

Comparison of Methods

Conclusion

DataFrames can be created from various data sources including dictionaries, lists, and NumPy arrays. Use dictionaries for labeled data and lists when you need more control over the structure.