The repository contains all the solved assignments based on following course contents:
Assignment 01: Data Manipulation
- Task 01 - Data Inspection
- Task 02 - Imputation of the missing data
- Task 03 - Unique, 2 most used & 2 least used "Equity Style" values
- Task 04 - Use of Lambda Function
- Task 05 - Data Aggregation using GroupBy
- Task 06 - Data Aggregation using pivot tables
- Task 07 - Groupby and Pivot Tables Usage
Assignment 02: Data Visualization using Matplotlib
- Task 01 - Data Inspection (Distribution of data)
- Task 02 - Gender-based comparison of no.of births over the years
- Task 03 - 3 most and least popular Male & Female Names
- Task 04 - Data Visualization using Matplotlib
Assignment 03: Exploratory Data Analysis on Sales Data
- Task 01 - Choose an appropriate graph to display the change in sales of each category throughout the year. Display each sale inside a separate graph; *Hint: Make use of subplots
- Task 02 - What is the total number of sales of each sub-category inside each category *Hint: Use Subplots
- Task 03 - Figure out a way to present your data to stakeholders in such a way they could: 1. see the sales change in each country through out the year 2. could differentiate between each category of the sales each country made
- Task 04 - Play with the data, make some intresting plots and draw some conclusion
- Task 05 - Let's do the visualization in Task 01 using Seaborn instead of Matplotlib
The course repository and lecture notebooks can be found here Course Notebooks
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 - Bayes Theorem