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Pandas Data Wrangling Essentials

Clean, Transform & Conquer Data with Pandas - Your Data Career Starts Here!

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Pandas Data Wrangling Essentials

7 Modules

Course Curriculum

7 Modules · 10 Chapters · 34 Topics · 211 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

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

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

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

Data Cleaning - Missing Data

3 Topics

Detecting Missing Data

3 Sub-topics

Detecting Missing Values with isnull() and notnull()

Counting Missing Values

Visualizing Missing Data Patterns

Handling Missing Data

8 Sub-topics

Dropping Rows with Missing Values

Dropping Columns with Missing Values

Filling Missing Values with Scalar

Forward Fill Method

Backward Fill Method

Filling with Mean, Median, Mode

Filling with Interpolation

Replacing Specific Values

Missing Data Strategies

7 Sub-topics

Missing Data Imputation Strategies

Forward and Backward Fill Limitations

Interpolation Methods Comparison

Multivariate Imputation Concepts

Missing Indicator Variables

Dropping vs Imputing Decision Framework

Validating Imputation Results

Data Cleaning - Duplicates and Quality

3 Topics

Handling Duplicates

5 Sub-topics

Detecting Duplicate Rows

Removing Duplicate Rows

Keeping First or Last Occurrence

Finding Duplicates in Specific Columns

Handling Duplicates with Custom Logic

Data Validation

8 Sub-topics

Checking Data Ranges

Validating Data Types

Checking for Impossible Values

Identifying Outliers

Ensuring Data Consistency

Cross-Field Validation

Creating Validation Rules

Generating Data Quality Reports

Data Quality Frameworks

8 Sub-topics

Defining Data Quality Rules

Implementing Validation Checks

Creating Quality Scorecards

Automated Quality Monitoring

Data Lineage Tracking

Quality Issue Documentation

Remediation Strategies

Quality Reporting

Data Transformation Basics

5 Topics

Sorting and Ranking

8 Sub-topics

Sorting by Single Column

Sorting by Multiple Columns

Sorting in Ascending and Descending Order

Sorting Index

Sorting with Missing Values

Ranking Data

Ranking Methods - average, min, max, first, dense

Ranking with Ascending and Descending Order

String Operations

11 Sub-topics

Accessing String Methods with str

Converting Case - lower(), upper(), title()

Stripping Whitespace

Replacing Substrings

Splitting Strings

Concatenating Strings

Checking String Contains

Extracting Substrings

String Length

Finding and Replacing with Regex

Extracting with Regex Patterns

Advanced String Operations

8 Sub-topics

Complex String Parsing

Extracting with Named Groups

Multiple Pattern Matching

String Tokenization

Text Normalization

Handling Special Characters

Unicode Operations

String Vectorization Performance

Type Conversion

8 Sub-topics

Checking Data Types

Converting to Numeric with to_numeric()

Converting to Datetime

Converting to String

Converting to Category

Handling Errors in Conversion

Downcasting for Memory Optimization

Converting Multiple Columns at Once

Data Type Optimization

8 Sub-topics

Understanding Memory Layout

Integer Type Optimization

Float Type Optimization

String vs Category Decision

Boolean Type Usage

Date Type Optimization

Memory Profiling Tools

Creating Memory-Efficient Pipelines

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

Merging and Joining

3 Topics

Merge Fundamentals

8 Sub-topics

Understanding Different Join Types

Inner Join with merge()

Left Join with merge()

Right Join with merge()

Outer Join with merge()

Merging on Single Column

Merging on Multiple Columns

Specifying Left and Right Keys

Advanced Merging

13 Sub-topics

Handling Duplicate Column Names

Indicator Parameter for Merge Tracking

Validating Merges

Merging with Index

Using join() Method

Merging on Index

Merging with Suffixes

Fuzzy Matching Concepts

Cross Join Operations

Merge with Sorting

Handling Duplicate Keys

Merge Performance Optimization

Troubleshooting Merge Issues

Concatenation

5 Sub-topics

Concatenating DataFrames Vertically

Concatenating DataFrames Horizontally

Handling Index in Concatenation

Ignoring Index While Concatenating

Adding Keys to Concatenated Data

Reshaping and Pivoting

5 Topics

Pivot Tables

6 Sub-topics

Creating Basic Pivot Tables

Pivot with Multiple Aggregations

Pivot with Multiple Indices

Pivot with Multiple Columns

Filling Missing Values in Pivot

Pivot Table Margins

Cross Tabulations

3 Sub-topics

Cross Tabulation with crosstab()

Normalized Cross Tabulations

Cross Tab with Multiple Variables

Stack and Unstack

5 Sub-topics

Understanding Wide vs Long Format

Using stack() to Convert Wide to Long

Using unstack() to Convert Long to Wide

Multi-Level Index Stacking

Handling Missing Values in Stack/Unstack

Melt and Pivot

3 Sub-topics

Pivot and Melt for Reshaping

Using melt() for Unpivoting

Using pivot() for Pivoting

Advanced Reshaping

8 Sub-topics

Complex Pivot Operations

Multiple Index Pivoting

Pivoting with Aggregations

Melting with Multiple Value Columns

Cross Tabulation Advanced

Reshaping with MultiIndex

Conditional Reshaping

Memory-Efficient Reshaping

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Pandas Data Wrangling Essentials

Certificate of Completion

Course Curriculum

Student Reviews

Frequently Asked Questions

Start Your Journey Today

Pandas Data Wrangling Essentials

Certificate of Completion

Course Curriculum

Student Reviews

Frequently Asked Questions

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