The repository contains all the notebooks and datasets that we are going to use during the course.
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Chapter 01: Data Manipulation with pandas
- 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
Chapter 02: Merging Dataframes with pandas
- 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)
Chapter 04: Data Cleaning and Preparation
- 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
Chapter 05: Introduction to Probability
- 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
Chapter 06: Statistical Thinking
- Lecture 01 - Descriptive Statistics
- Lecture 02 - Measure of Variation
- Lecture 03 - Range
- Lecture 04 - Standard Deviation
- Lecture 05 - Percentile
- Lecture 06 - Boxplot
- Lecture 07 - Skewness
- Lecture 08 - Inferential Statistics
- Lecture 09 - Density Plot
- Lecture 10 - Srandard Normal Distribution
- Lecture 11 - Central Limit Theorem
- Lecture 12 - Hypothesis Testing