Getting Started with Pandas for Data Analysis

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python pandas data-science

Learn the fundamentals of pandas, Python's powerful data manipulation library.

Table of Contents

Pandas is the cornerstone of data analysis in Python. This guide will help you get started with the basics.

Installing Pandas

pip install pandas numpy

Core Data Structures

Series

A one-dimensional labeled array:

import pandas as pd

s = pd.Series([1, 3, 5, np.nan, 6, 8])
print(s)

DataFrame

A two-dimensional labeled data structure:

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

Common Operations

Reading Data

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

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

# JSON
df = pd.read_json('data.json')

Basic Exploration

df.head()      # First 5 rows
df.tail()      # Last 5 rows
df.info()      # Column info
df.describe()  # Statistical summary

Next Steps

Practice with real datasets from Kaggle or your own data to solidify these concepts!