हिन्दी में

Pandas for Absolute Beginners

Zero to Pandas hero—launch your data career with India's easiest course!

4.4
1+ enrolled
Absolute Beginner

Certificate of Completion

Complete this course and earn a verified certificate to showcase your achievement.

Verified & ShareableShare on LinkedIn, resume, or portfolio
QR Code VerificationEmployers can instantly verify online
Unique Certificate IDTamper-proof with unique serial number
Industry RecognisedAccepted by 500+ companies across India
Grow Up More
CERTIFICATE OF COMPLETION
This is to certify that
Your Name Here
has successfully completed
Pandas for Absolute Beginners
6 Modules

Course Curriculum

6 Modules · 8 Chapters · 24 Topics · 142 Sub-topics

01
Getting Started
1 Chapters · 2 Topics · 9 Sub-topics
Getting Started with Pandas
2 Topics
Introduction to Pandas
5 Sub-topics
What is Pandas and Why Use It
Installing Pandas and Verifying Installation
Understanding Pandas Data Structures Overview
Importing Pandas and Basic Conventions
Your First Pandas Program
Pandas Development Environment
4 Sub-topics
Setting Up Jupyter Notebook for Pandas
Using VS Code with Pandas
Understanding Pandas Documentation
Exploring Pandas Community Resources
02
Understanding Series
1 Chapters · 2 Topics · 12 Sub-topics
Series Fundamentals
2 Topics
Creating and Understanding Series
5 Sub-topics
Creating Series from Lists
Creating Series from Dictionaries
Creating Series from NumPy Arrays
Creating Series with Custom Index
Series Attributes - index, values, dtype, shape, size
Series Operations and Manipulation
7 Sub-topics
Accessing Elements by Position
Accessing Elements by Label
Slicing Series
Boolean Indexing in Series
Series Arithmetic Operations
Series Mathematical Methods
Checking and Handling Missing Values in Series
03
Understanding DataFrame
1 Chapters · 4 Topics · 18 Sub-topics
DataFrame Fundamentals
4 Topics
Creating DataFrames
5 Sub-topics
Creating DataFrame from Dictionary of Lists
Creating DataFrame from List of Dictionaries
Creating DataFrame from NumPy Arrays
Creating DataFrame from Series
DataFrame Attributes - shape, size, columns, index, dtypes
DataFrame Inspection
3 Sub-topics
Viewing DataFrame - head(), tail(), sample()
DataFrame Info and Memory Usage
Understanding DataFrame Structure
DataFrame Access and Selection
6 Sub-topics
Accessing Columns
Accessing Rows with loc
Accessing Rows with iloc
Selecting Multiple Columns
Selecting Rows and Columns Together
Boolean Indexing in DataFrame
DataFrame Modification
4 Sub-topics
Adding New Columns
Deleting Columns
Renaming Columns and Index
Modifying DataFrame Values
04
Basic Data Operations
2 Chapters · 7 Topics · 42 Sub-topics
Data Input and Output
3 Topics
Reading Data from Files
11 Sub-topics
Reading CSV Files
Reading Excel Files
Reading JSON Files
Reading from Clipboard
Reading HTML Tables
Reading SQL Database Tables
Handling File Paths
Setting Custom Delimiters
Handling Missing Values While Reading
Specifying Data Types While Reading
Reading Large Files in Chunks
Writing Data to Files
4 Sub-topics
Writing to CSV Files
Writing to Excel Files
Writing to JSON Files
Export Options and Parameters
Advanced File Operations
10 Sub-topics
Reading Multiple Files
Handling Different Encodings
Parsing Fixed-Width Files
Reading Files with Custom Separators
Handling Messy Headers
Skipping Rows and Footers
Reading Only Specific Columns
Using Converters for Custom Parsing
Handling Bad Lines
Compression Support - gzip, zip, bz2
Filtering and Selection
4 Topics
Boolean Filtering
5 Sub-topics
Boolean Filtering with Single Condition
Boolean Filtering with Multiple Conditions
Using AND, OR, NOT Operators
Using isin() for Multiple Values
Using between() for Range Filtering
String-Based Filtering
3 Sub-topics
String Filtering with contains()
Filtering with str.startswith() and str.endswith()
Filtering with Regular Expressions
Query Method
3 Sub-topics
Using query() Method
Query with Multiple Conditions
Dynamic Filter Construction
Advanced Filtering
6 Sub-topics
Filtering Null and Non-Null Values
Combining Complex Conditions
Multi-condition Boolean Filtering
Filtering Numeric Ranges
Filtering with Lambda Functions
Filter Performance Optimization
05
Simple Data Analysis
2 Chapters · 7 Topics · 52 Sub-topics
Data Exploration and Inspection
3 Topics
Statistical Summaries
5 Sub-topics
Understanding describe() for Statistical Summary
Using info() for DataFrame Overview
Checking Unique Values
Value Counts for Frequency Distribution
Correlation Analysis
Data Quality Assessment
5 Sub-topics
Finding Null Values
Data Type Inspection
Checking Duplicates
Memory Usage Analysis
Exploring Categorical Data
Data Profiling
9 Sub-topics
Comprehensive Summary Statistics
Distribution Analysis
Skewness and Kurtosis
Percentile Calculations
Value Counts and Frequencies
Unique Values Analysis
Data Cardinality
Creating Data Profiles
Automated Profiling Reports
Grouping and Aggregation
4 Topics
GroupBy Basics
8 Sub-topics
Understanding groupby() Concept
Grouping by Single Column
Grouping by Multiple Columns
Aggregation with sum()
Aggregation with mean()
Aggregation with count()
Aggregation with min() and max()
Multiple Aggregations with agg()
Advanced GroupBy
9 Sub-topics
Custom Aggregation Functions
Named Aggregations
Grouping with Transformations
Filtering Groups
Iterating Over Groups
Getting Group Keys
Size and Count Differences
Nunique for Unique Counts
Groupby with Multiple Statistics
GroupBy Performance
8 Sub-topics
GroupBy with Multiple Keys
GroupBy with Custom Functions
GroupBy with Filters
GroupBy with Apply
Nested GroupBy Operations
GroupBy Performance Tuning
Memory-Efficient GroupBy
GroupBy Result Formatting
Aggregation Patterns
8 Sub-topics
Custom Aggregation Functions
Multiple Aggregations Per Column
Different Aggregations Per Column
Aggregation with Filtering
Conditional Aggregation
Nested Aggregations
Aggregation with Transform
Weighted Aggregations
06
Saving Your Work
1 Chapters · 2 Topics · 9 Sub-topics
Data Export and Serialization
2 Topics
Export Formats
5 Sub-topics
Exporting to CSV with Options
Exporting to Excel with Formatting
Exporting to JSON
Exporting to HTML
Exporting to LaTeX
Serialization
4 Sub-topics
Pickling DataFrames
Parquet Format for Efficient Storage
Feather Format for Fast I/O
HDF5 for Large Data

Student Reviews

0.0 (0 reviews)
0.0
Course Rating
5
0%
4
0%
3
0%
2
0%
1
0%

No reviews yet. Be the first to review this course!

Frequently Asked Questions

No FAQs for this course yet.

Preview this course
Free
Lifetime access to all materials
Certificate of completion
Available in multiple languages
Access on mobile & desktop
7-Day Money-Back Guarantee Not satisfied? Get a full refund within 7 days, no questions asked. Zero risk.

Start Your Journey Today

Join thousands of students already mastering new skills. Enroll now and get instant access.

Request Callback