Here are my data analytics related works.
I only update this repo occasionally, for records keeping purposes.
For more information please check my Kaggle page, thanks!

1. Data-exploration-with-pandas: Learn the basic concept and functions of pandas module, get used to .ipynb notebook enviroment.
   Google Colab
   day71-pandas-colab

2. Data-visualization-matplotlib: Performed EDA on dataset using pandas then learn the basic functions and methods of matplotlib lib, analyze programming language trends using StackExchange query data.
   Google Colab
   notebook
   popularity

3. Data-aggregate-and-merge-data-with-pandas: Diving deep into a dataset all about LEGO, which will help us answer a whole bunch of interesting questions about the history of the company, their product offering, and which LEGO set rules them all. Keep diving into pandas module and learning agg, groupby, merge methods and how to format and beautify MD file with HTML.
   Google Colab
   day-73-screenshot
   day-73

4. Resampling-and-visualizing-time-series-data: Investigate how search volume for various topics related to their prices or values, through pandas and matplotlib libraries.
   Google Colab
   day-74-screenshot
   day-74

5. Plotly-analyzing-Google-playstore-appdata: Wrestle the Android App Store Data into Beautiful Looking Charts with Plotly.
   Google Colab
   day75-screenshot
   day75-1
   day75-2
   day75-3
   day75-4

6. Computation-with-Numpy: Review basic numpy methods and functions, including arange, linspace, np.random.random, image manipulation using array and the concept of scalar and broadcasting- "NumPy will make the shape of the smaller array - our scalar - compatible with the larger array".
   Google Colab
   day76-1 day76-2
   day76-2
   day76-2
   day76-2

7. Linear-Regression-with-scikit-learn-and-seaborn: Dive into movie box office data and explore the relationship between move production budget and its gross income, using linear regression from scikit-learn and plot beautiful graphs using matplotlib + seaborn.
   Google Colab
   day77-1
   day77-2

8. Analyze-Nobel-prize-with-plotly-matplotlib-seaborn: Analyse a dataset on the past winners of the Nobel Prize using pandas and numpy, viz with plotly, matplotlib and seaborn.
   Google Colab
   day78-1
   day78-1
   day78-1
   day78-1
   day78-1

9. Analysis-of-Handwashing-Ttests-and-Distributions: Analyzing the effect of Dr. Ignaz Semmelweis's implementation of handwashing for Vienna General Hospital in 1840s, using t-tests and distributions.
   Google Colab
   day79-handwashing
   day79-1
   day79-2
   day79-3

10. Predict-Boston-Housing-Price: using multivariate regression and valuation model from scikit-learn package.
    Google Colab
    day80-boston
    day80-1
    day80-2