Python Data Science with pandas 📊¶

Python Professional PathData Science with pandas

Prerequisites: Python Lists, Python Dictionaries

Welcome to the Data Science with pandas module. This is where Python stops being just a scripting language and starts being a superpower for analysing real-world data.

Mentor's Note: Data Science doesn't require a PhD — it requires curiosity and the right tool. pandas is that tool. Every CBSE Class 12 student and every aspiring data analyst needs exactly what you'll learn here. 💡

🌟 Why pandas?¶

Imagine your school gives you an Excel file with 10,000 student records. Finding the average marks manually would take hours. With pandas:

import pandas as pd
df = pd.read_csv('students.csv')
print(df['marks'].mean())  # Done in one line. ⚡

pandas is how the real world handles data — from government portals and hospitals to fintech startups.

🗺️ Your Learning Roadmap¶

graph LR
    A[🐼 pandas Intro] --> B[📈 Series]
    B --> C[🗃️ DataFrame Basics]
    C --> D[🔍 Indexing & Selection]
    D --> E[📂 CSV with pandas]

📚 Module Topics¶

🐼

Introduction to pandas

Install, Import, First Look

Learn what pandas is, why it exists, how to install it, and write your very first DataFrame.

Start Here →

📈

pandas Series

1D Labelled Arrays

Master the building block of pandas — a labelled, one-dimensional array with index and values.

Explore Series →

🗃️

DataFrame Basics

Structure, dtypes, Creation

Learn to create DataFrames from dicts and lists, inspect shape, dtypes, and add or drop columns.

Build Tables →

🔍

Indexing & Selection

loc, iloc, Filtering

Select rows and columns precisely using loc (label-based), iloc (position-based), and boolean filters.

Select Data →

📂

CSV with pandas

read_csv, to_csv, Missing Data

Read real-world CSV files into DataFrames, handle missing values, and save cleaned data back to CSV.

Handle Files →

✅ Prerequisites¶

Before starting this module, make sure you are comfortable with:

Python Lists — pandas is built on list-like structures
Python Dictionaries — DataFrames are created from dicts
Python File Handling / CSV — helpful but not required

Next: Introduction to pandas →