Pandas DataFrame Basics

Last Updated: 27st August 2025

  • A DataFrame is a 2D table (rows × columns) in Pandas.
  • Think of it like an Excel sheet or an SQL table.
  • It has:
    • Rows (index/labels)
    • Columns (labeled headers)
    • Values (data stored inside)

Hinglish Tip 🗣: DataFrame poora Excel sheet jaisa hota hai.

✏ Creating a DataFrame

1. From Dictionary

import pandas as pd

data = {
    "Name": ["Amit", "Priya", "Rahul", "Sneha"],
    "Age": [20, 22, 21, 19],
    "Marks": [85, 90, 78, 88]
}

df = pd.DataFrame(data)
print(df)

2. From List of Dictionaries

import pandas as pd
data = [
    {"Name": "Amit", "Age": 20, "Marks": 85},
    {"Name": "Priya", "Age": 22, "Marks": 90},
    {"Name": "Rahul", "Age": 21, "Marks": 78},
]
df = pd.DataFrame(data)
print(df)

3. From List of Lists

import pandas as pd
data = [
    ["Amit", 20, "Delhi"],
    ["Priya", 22, "Mumbai"],
    ["Rahul", 21, "Kolkata"],
]

df = pd.DataFrame(data, columns=["Name", "Age", "City"])
print(df)

4. From Series

import pandas as pd
s1 = pd.Series([1, 2, 3], name="RollNo")
s2 = pd.Series(["A", "B", "C"], name="Grade")

df = pd.concat([s1, s2], axis=1)
print(df)
← PreviousNext →