The repository contains various Jupyter notebooks which introduces basic Python modules such as NumPy, Matplotlib, Seaborn and Pandas for basic data analysis, clearning, manipulation and exploratory data analysis.
You can open the notebooks in Google Colab and save a copy to work on the commands and add your own content.
The content is adapted from the masters subject Applied Data Programming that I used to teach students in Masters in Data Science degree program at Kingston University.
The Jupyter notebook Introduction_to_NumPy.ipynb introduces NumPy and basic NumPy operations. Topics covered includes:
Introduction to Numpy
Installing NumPy
Initializing a NumPy array
NumPy Operations
Basic Array Operations
The Jupyter notebook Numpy_Advanced_(Maths_and_Stats).ipynb introduces advanced concepts of NumPy and advanced NumPy operations. Topics covered includes:
Basic Array Operations
NumPy Broadcasting
Advanced Array Operations
File Input and Output with arrays
Linear Algebra
Introduction to Scipy
The Jupyter notebook Introduction_to_Basic_Visualization_using_Matplotlib.ipynb introduces the basics of visualization along with some basic plots using Matplotlib. Topics covered includes:
Introduction to Matplotlib
Plotting arrays with Matplotlib
Customizing plot properties
Creating a simple plot
Subplots
If you find this repository useful and use it in your work, please provide a link to this Github page in your work or publication.
Please report any errors or any feedback to the author, Nabajeet Barman via email at [email protected]