Pandas से Data Cleaning

Pandas Data Cleaning क्या है?

Pandas Data Cleaning ka matlab hai: Data cleaning fixes missing values, duplicate rows, wrong data types and inconsistent entries. Simple words me, ye topic practical Python programs likhne me direct use hota hai.

Is topic ko sirf definition ke liye nahi, balki removing duplicates jaise real examples ke liye practice karein.

यह क्यों सीखना जरूरी है?

• Ye removing duplicates me kaam aata hai.
• Ye filling missing values se bhi connected hai.
• Isse aap code ka output aur errors better samajh paate hain.

Important Terms

Syntax / Basic Pattern

Basic idea: pehle data तैयार करें, phir Python logic apply करें, aur finally result display करें.

import pandas as pd
df = pd.DataFrame({"Name": ["Aarav", "Riya", "Riya"], "Marks": [82, None, None]})
df = df.drop_duplicates()
df["Marks"] = df["Marks"].fillna(0)
print(df)

Complete Example Program

import pandas as pd

df = pd.DataFrame({"Name": ["Aarav", "Riya", "Riya"], "Marks": [82, None, None]})

df = df.drop_duplicates()
df["Marks"] = df["Marks"].fillna(0)

print(df)

Expected Output

Program Explanation

• import pandas as pd imports ready-made features from a module/library.
• df = pd.DataFrame({"Name": ["Aarav", "Riya", "Riya"], "Marks": [82, None, None]} stores a value in df.
• df = df.drop_duplicates() stores a value in df.
• df["Marks"] = df["Marks"].fillna(0) stores a value in df["Marks"].
• print(df) displays information or calculated result on the screen.

Practical Uses

• Removing duplicates.
• Filling missing values.
• Fixing column data types.

Common Mistakes

• Analysing data before checking missing values, duplicates and data types.
• Changing original data without keeping a clean copy.
• Creating charts without title, labels or explanation.

Practice Tasks

1. Program ko pandas-data-cleaning.py file me type karke run karein.
2. Values change karke output compare karein.
3. removing duplicates par ek छोटा example banayen.
4. Logic ko apne words me 5 lines me likhein.

सारांश

Pandas Data Cleaning ko tab complete maanenge jab aap iska meaning, example, output aur practical use clearly explain kar saken.