Data Analysis Using Python

The repository contains all the notebooks and datasets that we are going to use during the course.

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Course Content

  • Lecture 01 - Inspecting Dataframes
  • Lecture 02 - Some basic methods
  • Lecture 03 - Subsetting Columns
  • Lecture 04 - Summary Statistics
  • Lecture 05 - Slicing and Indexing
  • Lecture 06 - Selection with loc and iloc
  • Lecture 07 - Groupby and Pivot Tables
  • Lecture 01 - Importing Multiple Files
  • Lecture 02 - Indexing and Reindexing
  • Lecture 03 - Concatinating and Appending Data
  • Lecture 04 - Joining Tables
  • Lecture 05 - Merging Dataframes

Chapter 03: Data Visualization

  • Lecture 01 - Getting started with Matplotlib
  • Lecture 02 - Matplotlib Subplots
  • Lecture 03 - Matplotlib Interface
  • Lecture 04 - Getting started with Seaborn
  • Lecture 05 - Seaborn Subplots
  • Lecture 06 - Scatter Plot (with pandas, matplotlib and seaborn)
  • Lecture 07 - Histograms (with pandas, matplotlib and seaborn)
  • Lecture 08 - Line Plots (with pandas, matplotlib and seaborn)
  • Lecture 09 - Bar Plots (with pandas, matplotlib and seaborn)
  • Lecture 01 - Handling Missing Data
  • Lecture 02 - Visualizing Missing Data
  • Lecture 03 - Deleting Missing Data
  • Lecture 04 - Interpolating Missing Data
  • Lecture 05 - Removing Duplicate Values
  • Lecture 06 - Parsing Dates
  • Lecture 07 - Regular Expressions
  • Lecture 08 - Type Conversions
  • Lecture 01 - Sets and Events
  • Lecture 02 - Mutually/ Non Mutually Exclusive Events
  • Lecture 03 - Independent/Dependent Events
  • Lecture 04 - Laws of Probability
  • Lecture 05 - Conditional Probability: Practice
  • Lecture 06 - Law of Total Probability
  • Lecture 07 - Bayes Theorem