Pandas Essentials for Machine Learning Engineers — Pandas Best Practices and Optimization

Pandas Overview and Installation

• Introduction to Pandas
• Real World use Cases of Pandas
• Create Virtual Environment
• Installing Pandas and Dependencies
• Understanding DataFrames and Series
• Quiz - Pandas Overview and Installation

Data Import and Export

• Importing CSV Files
• Reading Excel Files
• Exporting Data to CSV and Excel
• Handling Other Data Formats (JSON, HTML)
• Quiz - Data Import and Export

Data Cleaning Techniques

• Identifying and Handling Missing Values
• Removing Duplicates and Irrelevant Data
• Data Normalization and Standardization
• Using Regular Expressions for String Cleaning
• Quiz - Data Cleaning Techniques

Data Transformation Techniques

• Understanding Data Types in Pandas
• Changing Column Data Types
• Using Apply and Lambda Functions for Transformations
• Reshaping Data with Melt and Pivot Table
• Quiz - Data Transformation Techniques

Exploratory Data Analysis (EDA)

• Exploring Data with Descriptive Statistics
• Data Visualization with Pandas Plotting
• Identifying Outliers and Trends
• Summary Statistics and Groupby Operations
• Quiz - Exploratory Data Analysis (EDA)

Data Merging and Joining

• Understanding Different Join Types
• Merging DataFrames on Common Columns
• Combining Data using Concatenation
• Joining DataFrames with Indexes
• Quiz - Data Merging and Joining

Data Analysis and Manipulation

• Filtering Data with Conditions
• Applying Functions Across DataFrames
• Sorting and Ordering Data
• Aggregating Data with Group By
• Quiz - Data Analysis and Manipulation

Handling Time Series Data

• Working with Date-Time Objects
• Resampling and Frequency Conversion
• Time Series Visualization
• Time Zone Handling in Pandas
• Quiz - Handling Time Series Data

Statistical Analysis with Pandas

• Introduction to Statistical Methods in Pandas
• Correlation and Covariance Analysis
• Applying Statistical Tests
• Understanding Distribution and Basics of Probability
• Quiz - Statistical Analysis with Pandas

Categorical Data Handling

• Understanding Categorical Data Types
• Implementing One-Hot Encoding for Categorical Variables
• Using Categorical Data in Analysis
• Visualization Techniques for Categorical Data
• Quiz - Categorical Data Handling

Integrating Pandas with Other Libraries

• Combining Pandas with NumPy
• Data Visualization with Matplotlib and Pandas
• Using Pandas with Scikit-learn for Machine Learning
• Integrating Pandas with Statsmodels for Forecasting
• Quiz - Integrating Pandas with Other Libraries

Preparing Data for Machine Learning

• Feature Engineering Techniques
• Data Scaling and Normalization
• Handling Imbalanced Datasets
• Splitting Data for Training and Testing
• Quiz - Preparing Data for Machine Learning

Pandas Best Practices and Optimization

• Understanding Performance and Memory Usage
• Optimizing Data Operations with Vectorization
• Using Queries for Fast Data Access
• Profiling and Benchmarking Pandas Operations
• Quiz - Pandas Best Practices and Optimization

Real-World Applications of Pandas

• Case Study: Data Analysis in Business
• Using Pandas in Web Scraping
• Analyzing Financial Data with Pandas
• Building Dashboards with Pandas and Visualization Tools
• Quiz - Real-World Applications of Pandas