pandasNot Started

What is a DataFrame?

The core pandas data structure — a labeled 2D table

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))

Next in pandas

Reading a CSV File

Continue

Unlocks

Reading a CSV File