📘 Pandas DataFrame for Beginners

Pandas DataFrame A DataFrame in Pandas is like a table with rows and columns  similar to an Excel sheet.

It is used for storing and analyzing structured data in Python.

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1️⃣ How to Import Pandas

import pandas as pd

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2️⃣ Creating a DataFrame

✔ Create DataFrame from a Dictionary

import pandas as pd

data = {
    'Name': ['Amit', 'Riya', 'John'],
    'Age': [22, 25, 28],
    'City': ['Delhi', 'Mumbai', 'Pune']
}

df = pd.DataFrame(data)
print(df)

Output

   Name   Age    City
0  Amit   22   Delhi
1  Riya   25  Mumbai
2  John   28    Pune

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3️⃣ Reading Data from a File

CSV File

df = pd.read_csv("data.csv")

Excel File

df = pd.read_excel("data.xlsx")

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4️⃣ Basic Operations on DataFrame

✔ View First & Last Rows

df.head()     # first 5 rows
df.tail()     # last 5 rows

✔ Get Information About Data

df.info()
df.describe()

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5️⃣ Selecting Data

✔ Selecting One Column

df['Name']

✔ Selecting Multiple Columns

df[['Name', 'City']]

✔ Selecting Rows using index

df.loc[0]      # by label
df.iloc[0]     # by position

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6️⃣ Filtering Data

df[df['Age'] > 24]

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7️⃣ Adding Columns

df['Age_after_5_years'] = df['Age'] + 5

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8️⃣ Removing Columns

df.drop('City', axis=1, inplace=True)

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9️⃣ Sorting

df.sort_values(by='Age')

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🔟 Handling Missing Values

Find missing values

df.isnull().sum()

Fill missing values

df.fillna(0)

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🧪 Simple Beginner Project (Mini Project)

Project: Student Marksheet Analysis

Steps:

1. Create a DataFrame of students with marks.

2. Calculate total and average.

3. Find toppers.

4. Plot results (optional).

Example

import pandas as pd

data = {
    'Name': ['Amit', 'Riya', 'John'],
    'Math': [80, 90, 75],
    'Science': [85, 88, 70],
    'English': [78, 92, 82]
}

df = pd.DataFrame(data)

df['Total'] = df[['Math', 'Science', 'English']].sum(axis=1)
df['Average'] = df['Total'] / 3

print(df)