This repository contains the archive of code for the data analysis with python
- First steps with Python & Jupyter notebooks
- Arithmetic, conditional & logical operators in Python
- Quick tour with Variables and common data types
- Branching with if, elif, and else
- Iteration with while and for loops
- Write reusable code with Functions
- Scope of variables and exceptions
- Deadline: Tue Dec 06, 11:30 PM
- Solve word problems using variables & arithmetic operations
- Manipulate data types using methods & operators
- Use branching and iterations to translate ideas into code
- Explore the documentation and get help from the community
- Gettting the current working directory
- Creating a directory
- Reading File
- Going from Python lists to Numpy arrays
- Working with multi-dimensional arrays
- Array operations, slicing and broadcasting
- Working with CSV data files
- Deadline: Tue Dec 13, 11:30 PM
- Explore the Numpy documentation website
- Demonstrate usage 5 numpy array operations
- Publish a Jupyter notebook with explanations
- Share your work with the course community
- Reading and writing CSV data with Pandas
- Querying, filtering and sorting data frames
- Grouping and aggregation for data summarization
- Merging and joining data from multiple sources
- Deadline: Tue Dec 20, 11:30 PM
- Create data frames from CSV files
- Query and index operations on data frames
- Group, merge and aggregate data frames
- Fix missing and invalid values in data
- Basic visualizations with Matplotlib
- Advanced visualizations with Seaborn
- Tips for customizing and styling charts
- Plotting images and grids of charts
- Finding a good real-world dataset for EDA
- Data loading, cleaning and preprocessing
- Exploratory analysis and visualization
- Answering questions and making inferences
- Assignment 1 - Python Basics Practice
- Assignment 2 - Numpy Array Operations
- Assignment 3 - Pandas Practice