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Advanced Python Course

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Overview:

This 4-week advanced course delves into sophisticated data manipulation techniques, high-performance computing in Python, and practical applications for data analysis. It is designed for Python users who are familiar with the basics and wish to expand their skill set in handling, analyzing, and visualizing complex datasets effectively.

What You’ll Learn

Proficient use of Pandas for advanced data manipulation tasks.
Leveraging NumPy for high-performance scientific computing.
Time series analysis in Pandas for trend analysis and forecasting.
Techniques for complex data transformations to prepare data for analysis.
Efficient memory management to optimize Python’s performance.
Performance tuning of Python code for large datasets.
Integrating Python scripts with relational and NoSQL databases.
Advanced data visualization techniques using Matplotlib and Seaborn.
Automating repetitive tasks and workflows using Python.
Implementing robust error handling to build reliable applications.

Course Content

Module 1: Data Manipulation and Analysis

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What is a Data Frame – Creating DataFrame from Dictionary

Creating DataFrame from List

Accessing Data in DataFrame

Accessing Rows in DataFrame

Basic Operations on DataFrame

Filtering Data in DataFrame

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Creating Series from List

Creating Series from Dictionary

Accessing Data in Series

Basic Operations on Series

Handling Missing Data in Series

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Reading CSV Data

Reading Excel Data

Reading JSON Data

Reading SQL Data

Exporting CSV Data

Exporting Excel Data

Exporting JSON Data

Writing SQL Data

Module 2: Clean, Aggregate & Group Data

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Identifying Missing Values

Handling Missing Values

Identifying Duplicates

Removing Duplicates

Checking Data Types

Converting Data Types

Applying Functions to Data

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Basic Aggregation Functions

Applying Multiple Aggregations

Grouping by Multiple Columns

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Merging DataFrames

Joining DataFrames

Concatenating DataFrames

Combining DataFrames

Module 3: Time Series Data

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Creating Time Series

Indexing and Slicing Time Series

Resampling Time Series

Rolling and Expanding Windows

Plotting Time Series Data

Module 4: Advanced Time Series Analysis with Pandas

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Downsampling Data

Upsampling Data

Custom Aggregation Functions

Frequency Conversion

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Rolling Windows

Expanding Windows

Combining Functions

Plotting Rolling and Expanding Windows

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Basic Time Series Plot

Customizing Time Series Plot

Plotting Multiple Time Series

Highlighting Specific Periods

Plotting Rolling Statistics

Seasonal Decomposition

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Pivoting DataFrames

Handling Duplicates

Melting DataFrames

Module 5: Advanced Data Processing and Transformation

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Data Encoding Introduction

Converting to Categorical Type

Categorical Data

Encoding Categorical Data

Working with Categories

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Using Apply Function

Using Map Function

Creating Custom Functions

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Loading Text Data

Cleaning Text Data

Extracting Information from Text

Manipulating Text Data

Applying Functions to Text Data

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Multi-Level Indexing

Complex Aggregations

Custom Transformations

Handling Missing Data

Module 6: Memory Management and Optimization

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Understanding Reference Counting

Garbage Collection

Monitoring Memory Usage

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Using Memory Profiler

Using Tracemalloc

Module 7: Database Interaction

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Setting Up SQLite Database

Inserting Data into Database

Querying Data from Database

Updating Data in Database

Deleting Data from Database

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Connecting to SQLite with SQLAlchemy

Creating Tables with SQLAlchemy

Inserting Data with SQLAlchemy

Querying Data with SQLAlchemy

Updating Data with SQLAlchemy

Deleting Data with SQLAlchemy

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Connecting to SQL Database with Pandas

Inserting Data with Pandas

Reading Data with Pandas

Writing Data to SQL with Pandas

SQL Queries with Pandas

Data Manipulation with Pandas

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Training sessions have been delivered at Microsoft, Bosch, Deloitte, Michelin, IBM, Collins Aerospace, and Cognizant. We are in no way associated with or sponsored by these companies.

This educational material is independently created and offered by Bot Campus AI. It is not sponsored by,endorsed by, or affiliated with Microsoft Corporation, Amazon Technologies, Inc., Google LLC, the Python Software Foundation, or Tableau Software, LLC. The use of these terms in our course material is for descriptive purposes only and does not imply any affiliation with or endorsement by the trademark owners.