What is a DataFrame?

The core pandas data structure — a labeled 2D table

Knowledge0%

Learn & Drill

Fluency0%

Drill & Speed

Retention0%

Mastery & Review

Confidence0%

All modes

Practice

Knowledge

Fluency

Retention

Knowledge Debt detected

You can study this freely — but your score may plateau if these foundations have gaps. The Mastery badge requires them to be solid.

Creating NumPy Arrays0%

Explanation

A DataFrame is a 2D labeled data structure — think of it as a spreadsheet or SQL table inside Python.

Key concepts:

Rows — each row is one observation (one record)
Columns — each column is one variable/feature
Index — the row labels (default: 0, 1, 2, …)
dtype — each column has its own data type

python

import pandas as pd

# Create from a dictionary
df = pd.DataFrame({
    'name':   ['Alice', 'Bob', 'Carol'],
    'age':    [25, 30, 35],
    'salary': [50000, 65000, 80000]
})
print(df)
#     name  age  salary
# 0  Alice   25   50000
# 1    Bob   30   65000
# 2  Carol   35   80000

Quick inspection:

df.shape → (rows, columns)
df.dtypes → data type of each column
df.head(n) → first n rows (default 5)
df.info() → summary including nulls
df.describe() → statistics for numeric columns

Examples

Creating and inspecting a DataFrame

df.shape gives (rows, cols) like NumPy

import pandas as pd

df = pd.DataFrame({
    'name':   ['Alice', 'Bob', 'Carol'],
    'age':    [25, 30, 35],
    'salary': [50000, 65000, 80000]
})

print(df.shape)   # (3, 3)
print(df.dtypes)
# name      object
# age        int64
# salary     int64
print(df.head(2))

How well did you understand this?

Next in pandas

Reading a CSV File

Continue

Unlocks

Reading a CSV File