Pandas Data Manipulation

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Module 1: Introduction to Pandas

Overview of Pandas
Installation and setup of Pandas.
Basic data structures: Series and DataFrame.
Loading and saving data in various formats.

Module 2: Data Exploration with Pandas

Descriptive statistics and summary functions.
Handling missing data and duplicates.
Data filtering and selection.
Grouping and aggregation.

gray concrete wall inside building

gray concrete wall inside building

white and black abstract painting

white and black abstract painting

worm's-eye view photography of concrete building

worm's-eye view photography of concrete building

Module 3: Data Cleaning and Preprocessing

Data cleaning techniques
Text data manipulation.
Date and time handling.
Merging and joining datasets.

Module 4: Time Series Analysis with Pandas

Introduction to time series data.
Time-based indexing and resampling.
Moving averages and rolling windows.
Analyzing trends and seasonality.

Module 5: Advanced Data Manipulation

Multi-indexing and hierarchical indexing.
Pivot tables and cross-tabulations.
Melting and stacking data.
Advanced aggregation techniques.

white concrete building during daytime

white concrete building during daytime

white concrete building during daytime

white concrete building during daytime

A curved facade covered in white latticework

A curved facade covered in white latticework

Module 6: Data Visualization with Pandas

Integration with Matplotlib and Seaborn.
Plotting basics: line plots, bar plots etc.
Visualizing relationships: scatter plots, pair plots.
Customizing and styling plots.