Course about Data Analysis with Python Course - Numpy, Pandas, Data Visualization

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The course is divided into 5 modules. Here is what the modules cover.

Lesson 1: Python & Jupyter Fundamentals

° Installation and setup - Python & Jupyter
° Jupyter notebook & Lab walkthrough
° Types, variables, statements & expressions
° Functions, exceptions & scope

Assignment 1 - Python Practice

° 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

Lesson 2: Numpy for data processing

° Numpy arrays
° Indexing
° Operations
° Numpy: advanced topics

Assignment 2 - Numpy Practice

° Explore different ways to create Numpy arrays
° Manipulate, aggregate and combine arrays
° Apply broadcasting & vectorization techniques
° Explore Numpy docs and write a blog post

Lesson 3: Pandas for working with tabular data

° Series
° Dataframes
° Operations
° Merging, Grouping & Joining

Assignment 3 - Pandas Practice

° Read and write different file types using Pandas data frames
° Manipulate rows, columns, empty values in data frames
° Merge, join and query data from multiple data frames
° Explore interoperability between Numpy & Pandas

Lesson 4: Visualization with Matplotlib and Seaborn

° Basic visualization with Matplotlib
° Beautiful visualizations with Seaborn
° Plotting directly from Pandas
° Other libraries: Plotly, Bokeh, Folium etc.

Lesson 5: Exploratory Data Analysis: A Case Study

° Working with Images using PIL
° Loading a dataset with Pandas
° Operations with numpy
° Visualization with Matplotlib & Seaborn

Course Project - Exploratory Data Analysis

° Find a real-world dataset of your choice online
° Use Numpy & Pandas to parse, clean & analyze data
° Use Matplotlib & Seaborn to create visualizations
° Ask and answer interesting questions about the data

More links for studies:

💻  Code References

• First steps with Python: https://jovian.ai/aakashns/first-steps-with-python

• Variables and data types: https://jovian.ai/aakashns/python-variables-and-data-types

• Conditional statements and loops: https://jovian.ai/aakashns/python-branching-and-loops

• Functions and scope: https://jovian.ai/aakashns/python-functions-and-scope

• Working with OS & files: https://jovian.ai/aakashns/python-os-and-filesystem

• Numerical computing with Numpy: https://jovian.ai/aakashns/python-numerical-computing-with-numpy

• 100 Numpy exercises: https://jovian.ai/aakashns/100-numpy-exercises

• Analyzing tabular data with Pandas: https://jovian.ai/aakashns/python-pandas-data-analysis

• Matplotlib & Seaborn tutorial: https://jovian.ai/aakashns/python-matplotlib-data-visualization

• Data visualization cheat sheet: https://jovian.ai/aakashns/dataviz-cheatsheet

• EDA on StackOverflow Developer Survey: https://jovian.ai/aakashns/python-eda-stackoverflow-survey

• Opendatasets python package: https://github.com/JovianML/opendatasets

• EDA starter notebook: https://jovian.ai/aakashns/python-eda-stackoverflow-survey