Git-and-GitHub-final-assignment

This template repository hosts the final Git & GitHub assignment.

Description

We learnt how to use Git & GitHub to keep records of milestones during projects. Now, this is time for the final assignment that consists in creating 3 repositories each having a minimum of 3 commits to host some of the previous projects you worked on, during the previous phase of the program and fill the table in the Recap Table section.

Assignment

The following steps constitute your assignment :

1. Clone this repository on your local machine;
2. Configure it as described in the Setup section;
3. Select 3 projects, your own ones or projects done during the previous part of the Azubi program ;
4. Create a repository for each project, with a complete and personalized readme file and repository's description ;
5. Commit at least 3 times for each repository while including simple and clear commit's messages, and push;
6. Fill the table in the Recap Table section with the details of your created repositories.
7. Finally, commit with the message My 3 repositories has been created, then push your commit.

Recap Table

The below table must contain the details of the repositories you will create, fill it please.

	Project's Name	Description	GitHub's Link
1	A-simple-Excel-visualization-repository	This projects shows the different graphs in excel and how they are applied to answer different questions.Data from the documentation report of the recreation visitors in different states is used.	https://github.com/Pendopr/A-simple-Excel-visualization-repository
2	- A-simple-pandas-repository	This is a simple project on how to create a pandas Data Frame from a dictionary.The created dataframe is used to do simple calculations in pandas.-	https://github.com/Pendopr/A-simple-pandas-repository
3	- Housing-price-prediction	This is a supervised machine learning project. In this projects several features of the Californian housing data are used to train the model on predicting the median housing price.-	https://github.com/Pendopr/Housing-priice-prediction

NB: Do not modify the general structure of this table above to avoid issue of evaluation, just fill the rows .

Setup

Install the required packages to be able to run the evaluation locally.

You need to have Python 3 on your system (a Python version lower than 3.10). Then you can clone this repo and being at the repo's root :: repository_name> ... follow the steps below:

• Windows (Python should be added to the Path variable of environment):

    python3 -m venv venv; venv\Scripts\activate; python -m pip install --upgrade pip; python -m pip install -r requirements.txt  
  

• Linux & MacOs:

    python3 -m venv venv; source venv/bin/activate; python -m pip install --upgrade pip; python -m pip install -r requirements.txt
  

The both long command-lines have a same structure, they pipe multiple commands using the symbol ; but you may manually execute them one after another.

1. Create the Python's virtual environment that isolates the required libraries of the project to avoid conflicts;
2. Activate the Python's virtual environment so that the Python kernel & libraries will be those of the isolated environment;
3. Upgrade Pip, the installed libraries/packages manager to have the up-to-date version that will work correctly;
4. Install the required libraries/packages listed in the requirements.txt file so that it will be allow to import them into the python's scripts and notebooks without any issue.

Evaluation

This evaluation will be automatically grade, so please follow the instructions carefully.

You can run this command bellow being at the root of the repository to be sure your solutions are the good ones before to push your solutions.

python -m pytest -v

If everything is okay, you will have such an output

================================================= test session starts =================================================
platform xxx -- Python 3.9.6, pytest-7.2.0, pluggy-1.0.0 -- /xxx/python3
cachedir: .pytest_cache
rootdir: xxx/Git-and-GitHub-final-assignment
collected 3 items                                                                                                     

tests/test_filled_table.py::test_not_empty_table PASSED                                                         [ 33%]
tests/test_filled_table.py::test_not_empty_rows PASSED                                                          [ 66%]
tests/test_readme_table.py::test_contains_table PASSED                                                          [100%]

================================================== 3 passed in 0.000s ==================================================