DSCI560

random_num.py works for generating 1000 random numbers between 0 to 100, and then resulting a random_num.csv file.

function_random_num.py works for generating 1000 numbers based on random_num.csv by using function y=3x+6, and then resulting a function_random_num.csv file.

visualization_nums.py works for visualizing the result of random_num.csv and function_random_num.csv, and then resulting a visualization_nums.png file.

Three Script.ipynb is a jupyter notebook which works for invoking above 3 files in one notebook and generating the distributions and linear plot of initial, intermediate and final results.

How to create and use a virtual environment for DSCI560 repository in your computer

1. Install virtualenv package on your computer by running the command line below:

   pip install virtualenv

2. Copy the url of repository and clone it by running the command line below:

   git clone https://github.com/liling10822/DSCI560.git

3. Running cd DSCI560 to go to the folder that you cloned

4. Create a blank virtual environment called dsci560H4 by running the command line below:

   For macOS and Linux: python3 -m venv dsci560H4

   For Windows: py -m venv dsci560H4

5. Activate the dsci560H4 enviornment by running the command line below:

   For macOS and Linux: source dsci560H4/bin/activate

   For Windows: .\dsci560H4\Script\activate

6. Install dependencies by running the command line below:

   pip install -r requirements.txt

   Otherwise, running the command line below to manually install the packages that will be needed:

   pip install seaborn
   pip install matplotlib
   

   After installing, run pip freeze in dsci560H4 environment to list all the packages in the environment (which shows empty before installing the packages), it should be like below:

   certifi==2020.6.20
   cycler==0.10.0
   kiwisolver==1.3.0
   matplotlib==3.3.2
   numpy==1.19.3
   pandas==1.1.3
   Pillow==8.0.1
   pyparsing==2.4.7
   python-dateutil==2.8.1
   pytz==2020.1
   scipy==1.5.3
   seaborn==0.11.0
   six==1.15.0
   

7. To run scripts in the DSCI560 repository, excuting the commmand line below:

   python random_num.py
   

   python function_random_num.py
   

   python visualization_nums.py
   

   For example, we run random_num.py successfully in our dsci560H4 environment in macOS, the terminal will show as below (the screenshot):

   

8. A binder badge to click for showing distributions and linear plot of DSCI560 repository.