What is a DataFrame?

If a Series is a single labelled column, a DataFrame is the whole spreadsheet — a 2-dimensional table of rows and columns. It's the structure you'll use most in real data work.

1A table with two axes

A DataFrame stores an ordered collection of columns. It has two axes: the rows run along axis 0 and the columns along axis 1. Click around to see how each is picked out:

Anatomy of a DataFrame

A DataFrame is a table with TWO axes. Click a column header (axis 1) or a row label (axis 0) to see how each is selected.

axis 0 · rowsaxis 1 · columns

	Name	English	IP	Maths
ID 1	Rinku	65	89	72
ID 2	Ritu	77	83	69
ID 3	Pankaj	72	95	87
ID 4	Ajay	81	99	94
ID 5	Aditya	92	87	96

what you selected

click a column header or a row label…

Every value has an address: (row index, column name)— e.g. Ajay's IP mark lives at ('ID 4', 'IP').

2What makes a DataFrame a DataFrame

🧱 It's 2-dimensional — an ordered collection of columns.
🌈 It's heterogeneous: different columns can hold different data types (text, ints, floats, booleans). But within one column the type is the same.
🏷️ Both axes are labelled — row indexes and column names, which can be numbers, letters or strings.
✏️ It's value-mutable and size-mutable — you can change values and add or drop rows and columns.

3A DataFrame is many Series

Here's the key mental model: a DataFrame is really several Series stacked side by side, all sharing the same row index. Each column is a Series.

Series vs DataFrame

	Series	DataFrame
Dimensions	1-D (a column)	2-D (rows × columns)
Axes	just the index	axis 0 (rows) + axis 1 (columns)
Data types	one dtype	one per column (can differ)
Size	value-mutable	value- & size-mutable

4Your first DataFrame

You import Pandas the same way, then build a DataFrame from a dictionary of columns. Run it and notice the row index on the left (0, 1, 2…) and the column names across the top.

first_dataframe.py

import pandas as pd

df = pd.DataFrame({
    'Name':    ['Rinku', 'Ritu', 'Pankaj'],
    'English': [65, 77, 72],
    'IP':      [89, 83, 95],
})
print(df)

print("\nOne column is a Series:")
print(df['IP'])

import pandas as pd

df = pd.DataFrame({
    'Name':    ['Rinku', 'Ritu', 'Pankaj'],
    'English': [65, 77, 72],
    'IP':      [89, 83, 95],
})
print(df)

print("\nOne column is a Series:")
print(df['IP'])

Key Takeaway

A DataFrame is a 2-D, labelled, heterogeneous table. Every value has an address: (row index, column name). Think of it as a bundle of Series sharing one index.

Quick Check

How many axes does a DataFrame have, and what are they?

Quick Check

Within a single DataFrame, can different columns have different data types?

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🔍 Series Attributes

Creating a DataFrame 🧱