7 ways to create a Pandas DataFrame in Python

There are several ways to create a Pandas DataFrame. Here are a few examples:

From a dictionary

import pandas as pd
data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
df = pd.DataFrame(data)

From a list of lists

data = [{'Name': 'Alice', 'Age': 25}, {'Name': 'Bob', 'Age': 30}, {'Name': 'Charlie', 'Age': 35}]
df = pd.DataFrame(data)

From a 2D Numpy array

import numpy as np
data = np.array([['Alice', 25], ['Bob', 30], ['Charlie', 35]])
df = pd.DataFrame(data, columns=['Name', 'Age'])

From a CSV file:

df = pd.read_csv('data.csv')

From an excel file

df = pd.read_excel('data.xlsx')

From a SQL query

import sqlite3

conn = sqlite3.connect('database.db')
df = pd.read_sql_query("SELECT * FROM table", conn)

You can also specify the index of DataFrame while creating it.

df = pd.DataFrame(data, columns=['Name', 'Age'], index=[1,2,3])

You can also create an empty DataFrame using the pd.DataFrame() constructor and later add data to it using the various DataFrame methods like loc[], iloc[], append(), insert(), concat() etc.