Programming Classes - Invidious

Programming Classes

Programming Classes | Learn Programming in Hindi | Mukesh Sir

Welcome to Programming Classes, one of India's trusted coding education channels. Learn programming in Hindi/Hinglish with simple explanations, practical coding examples, real-world projects, and interview-focused tutorials by Mukesh Sir.

📚 Topics Covered: C, C++, Java, Python, HTML, CSS, JavaScript, SQL, MySQL, Data Structures & Algorithms (DSA), MERN Stack, Artificial Intelligence (AI), Machine Learning (ML), OOPs, Git & GitHub, Jupyter Notebook, Database Management, Coding Interview Preparation, Placement Preparation, and Full Stack Development.

Whether you're a BCA, B.Tech, MCA, Diploma, B.Sc. CS, Class 11/12 student, or a beginner, this channel will help you build strong programming skills and become job-ready.

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11:03:31

Pandas Full Course 2026 | Complete Pandas Tutorial For Data Analysis and Data Science

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14:38

Day 65 Python Pandas | Head-to-Head Team Analysis in IPL Dataset 🔥

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11:33

Day 64 Python Pandas | Venue & Player of the Match Analysis 🔥

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13:27

Day 63 Python Pandas | Toss Analysis in IPL Dataset Using GroupBy 🔥

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13:59

Day 62 Python Pandas | Team Win Percentage Analysis Using GroupBy 🔥

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16:50

Day 61 Python Pandas | IPL Data Analysis Using GroupBy & Unique Functions 🔥

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11:23

Lecture 17 - MySQL Index Tutorial in Hindi | Speed Up Queries with Index

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10:06

Day 60 Python Pandas | Large DataFrame to MySQL in Chunks | Fast Data Upload Tutorial

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14:57

Lecture 16 - View in MySQL | Create View, Update View & Drop View

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11:50

Day 59: How to Store Pandas DataFrame in MySQL Using to_sql() | Python SQL Project

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14:42

Lecture 15 - Copy Table in SQL | Data Copy, Structure Copy, Existing Table Insert

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14:50

Day 58 : Read Complete Table in SQL | Python(Pandas)

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36:17

Lecture 14 - SQL Date Functions Explained | DATE_ADD(), CURDATE(), NOW() | Data Analytics Course

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28:34

Lecture 13 : SQL Joins with Three Tables in MySQL | Foreign Key Tutorial

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32:22

Lecture 12 : MySQL Foreign Key & Joins Tutorial | INNER JOIN, LEFT JOIN & RIGHT JOIN Explained

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13:43

Day 57: Python MySQL Tutorial | Read Data from MySQL Database Using Python & PyMySQL

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11:37

Day 56: Python MySQL Connection Tutorial | Connect MySQL Database with Python Using PyMySQL

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18:27

Python Pandas Day 55 | Window Functions in Pandas🔥

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3:06

📊✨Clean Invalid Emails in Excel Like a Pro! 📧🔥 #Shorts

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11:30

Python Pandas Day 54 | Multiple DataFrames into One Excel File using Pandas 🔥

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12:57

Python Pandas Day 53 | Export DataFrame to Excel 🔥 | to_excel() Method Explained (Complete Tutorial)

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10:16

Day 52: Sales Data Analysis Part 5 | Pivot Table | Pandas Python

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12:43

Day 51 Python Pandas Project | Sales Data Analysis with DateTime, Correlation & Customer Insights

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11:28

Day 50: Python Pandas Project | Sales Amount, GST Calculation & Sales Category Analysis in Python

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13:36

Day 49 | Pandas GroupBy Practice Project 🔥 | Sales Data Analysis in Python | Data Analytics

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15:58

Python Pandas Day 48 | Data Filtering Practice Questions 🔥 | Real-World Query Solving in Pandas

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15:30

Day 47 | Sales Data Analysis Project in Pandas 🔥 | Real World Data Analytics in Python

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9:06

Day 46 | Pandas Chunks Explained in Hindi | Handle Large CSV Files Efficiently in Python

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15:55

Day 45: Pandas CSV File Reading Tutorial 🔥 | Different Ways to Read CSV in Python

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Shared 3 months ago

64 views

13:07

Day 44:Student Marks Analysis Part 4 | Correlation,Pass Percentage,Rank System| Pandas Project Hindi

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13:21

Day 43: Student Marks Analysis Part 4| GroupBy,Grade Analysis,Class-wise Stats| Pandas Project Hindi

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15:18

Day 42: Student Marks Analysis Part 3 | Ranking, Grading, Topper Analysis | Pandas Project Hindi

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11:04

Day 41: Student Marks Analysis Part 2| Filtering, Sorting, Top/Bottom Students| Pandas Project Hindi

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55 views

11:11

Day 40:Student Marks Analysis in Pandas 🔥 |Total, Percentage, Average, GroupBy |Python Data Analysis

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10:04

Day 39: Pandas concat() Explained 🔥 | Combine DataFrames Row-wise & Column-wise | Python Hindi

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11:05

Python Pandas Day 38 |DataFrame.join() Explained |Join Two DataFrame in Pandas(Beginner to Advanced)

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12:50

Day 37: Merge DataFrames in Pandas 🔥 | SQL Joins (Inner, Left, Right) Explained | Python Hindi

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Shared 4 months ago

66 views

14:53

Python Pandas Day 36 | Why Use Multiple DataFrames? 🔥 | Smart Data Handling Explained

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10:20

Day 35: Expanding Window in Pandas 🔥 | Cumulative Sum, Expanding Mean | Python Data Analysis Hindi

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9:53

Day 34: Rolling Window in Pandas 🔥 | Moving Average, Rolling Mean, Sum, Std | Data Analysis Hindi

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11:11

Day 33: Pandas GroupBy + Resample 🔥 | Time Series Analysis in Python | Data Analytics Hindi

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12:31

Pandas Resampling Explained 🔥 | Time-Based Grouping in Python (Day 32)

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12:24

Day 31: DateTime Handling in Pandas 🔥 | to_datetime(), Date Extract, Time Difference

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9:39

Day 30: Ranking in Pandas 🔥 | rank() Function Explained | Data Analysis Series | Python Pandas Hindi

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Shared 4 months ago

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12:56

Day 29: Sorting Data in Pandas 🔥 | sort_values(), sort_index() Explained | Python Pandas

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9:56

Day 28: Merge Columns in Pandas | Combine Columns in DataFrame | Data Cleaning in Python

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10:56

Day 27:Split Columns in Pandas | str.split() Explained | Data Cleaning in Python| DataFrame Tutorial

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17:48

Day 26: Fix Data Types in Pandas | astype() & to_datetime() Explained | Data Cleaning in Python

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14:25

Python Pandas Day 25 | Fix Wrong & Inconsistent Data Like a Pro 🔥 | Data Cleaning Tutorial

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Shared 4 months ago

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14:46

Python Pandas Day 24 | Handling Duplicate Data in Pandas | Remove Duplicates Easily

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88 views

16:19

Python Pandas Day 23 | Fill Missing Values (NaN) in Pandas | Data Cleaning Tutorial for Beginners

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16:52

Day 22: Drop Missing Values in Pandas | dropna() Explained | Data Cleaning in Python | NaN Remove

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13:56

Handling Missing Values in Pandas 🔥 | NaN & None Explained | Day 21 Data Cleaning

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Shared 4 months ago

142 views

9:58

Data Cleaning in Python Pandas | Fix Dirty Data 🔥 | Day 20 Data Analysis Series #shorts

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Shared 4 months ago

104 views

13:52

Pivot Table in Pandas | Data Analysis Made Easy 🔥 | Python Pandas Tutorial Day 19

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Shared 4 months ago

149 views

13:43

GroupBy in Pandas 🔥 | Data Grouping & Aggregation Explained (Day 18)

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Shared 4 months ago

145 views

11:06

Pandas Aggregate Functions 🔥 | sum(), mean(), max(), min() Explained (Day 17)

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13:40

Top Pandas Functions for Data Filtering 😱 | Must Know Tricks (Day 16)

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12:10

Pandas Interview Questions 🔥 | Condition Based DataFrame Problems (Day 15)

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8:17

Fancy Indexing in Pandas 🔥 | Select Multiple Rows & Columns (Day 14)

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