PyData_Global2021_DataAnalysisPandasandNumPy

This Jupyter Notebook contains the code for my talk for PyData Global 2021 on 28th Oct 2021. The notebooks has following sections :

• Introductory NumPy
• Introductory Pandas
• Very Brief Introduction to Matplotlib
• Case Study with Pandas
• Case Study with Pandas

I have referred and taken inputs from many excellent sources by fantastic authors. All the sources have been gratefully acknowledged in the notebook and I wish to acknowledge them here as well.

[1] https://numpy.org

[2] https://pandas.pydata.org/

[3] https://matplotlib.org/

[4] https://cs231n.github.io/python-numpy-tutorial/#numpy

[5] https://www.kaggle.com/lavanyashukla01/pandas-numpy-python-cheatsheet

[6] https://cs231n.github.io/python-numpy-tutorial/#numpy

[7] https://www.geeksforgeeks.org/how-to-set-the-spacing-between-subplots-in-matplotlib-in-python/

[8] https://www.geeksforgeeks.org/how-to-set-the-spacing-between-subplots-in-matplotlib-in-python/

[9] https://pandas.pydata.org/docs/pandas.pdf

[10] https://nbviewer.org/github/justmarkham/pandas-videos/blob/master/pandas.ipynb#14.-When-should-I-use-a-%22groupby%22-in-pandas%3F-%28video%29

[11] https://www.hackerearth.com/practice/machine-learning/data-manipulation-visualisation-r-python/tutorial-data-manipulation-numpy-pandas-python/tutorial/

[12] https://github.com/datasciencedojo/datasets/blob/master/titanic.csv

[13] https://towardsdatascience.com/all-pandas-groupby-you-should-know-for-grouping-data-and-performing-operations-2a8ec1327b5

[14] Case Study -This case study is heavily inspired by the data analysis case study from NVIDIA Deep Learning Institute's Course "Fundamentals of Accelerated Data Science with Rapids". https://www.nvidia.com/en-in/training/instructor-led-workshops/