Introduction to Pandas 📊

Last Updated: 26st August 2025

  • Pandas is a Python library used for data analysis and manipulation.
  • It provides two main data structures:
    • Series → 1D labeled array (like an Excel column).
    • DataFrame → 2D labeled table (like an Excel sheet).
  • Pandas is built on top of NumPy and is widely used in Data Science, ML, and Data Analytics.

Hinglish Tip 🗣: Agar aapko Excel ya SQL ki tarah Python me data handle karna hai — rows/columns ke form me — toh Pandas sabse powerful library hai.

✏ Installing & Importing Pandas

# Install (only once in your environment)
pip install pandas

# Import
import pandas as pd

📊 Pandas Series (1D Data)

A Series is like a single column in Excel.

import pandas as pd

# Create a Series
s = pd.Series([10, 20, 30, 40], index=["a", "b", "c", "d"])

print(s)
print(type(s))

🎯 Accessing Series Data

print(s["a"])   # by label → 10
print(s[0])     # by index → 10
print(s.values) # only values → [10 20 30 40]
print(s.index)  # only index → Index(['a','b','c','d'], dtype='object')

🧮 Operations on Series

print(s + 5)            # Add 5 to all values
print(s.mean())         # Mean → 25.0
print(s.max())          # Max → 40
print(s.min())          # Min → 10
print(s.sum())          # Sum → 100
print(s.count())        # Count → 4
print(s.unique())       # Unique values → [10 20 30 40]
print(s.nunique())      # Unique values count → 4
print(s.value_counts()) # Value counts → a    1, b    1, c    1, d    1
print(s.sort_values())  # Sort values → a    10, b    20, c    30, d    40

Hinglish Tip 🗣: Series ko hum ek list + dictionary dono ka mix samajh sakte hai. Isme values bhi hoti hain aur unke labels (index) bh

💡 Quick Practice

  • Create a Series of 5 fruits with their quantities.
  • Access the 2nd fruit using both label and index.
  • Find the mean and maximum quantity.
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