Jovian
Sign In
Learn practical skills, build real-world projects, and advance your career

LaLiga (2018-2019) Data Analysis Project

This project aims to analyse the 2018-2019 season of LaLiga (Spanish Football League).
The dataset used in this project contains advanced player statistics performance on LaLiga 2018/2019, it was found on kaggle via the following link: https://www.kaggle.com/alvarob96/laliga_2018-19_season_player_stats

Since this project counts for the final assignment of the course Data Analysis with Python: Zero to Pandas, we will try to perform a basic/simple exploratory data analysis of this real-world dataset by applying the concepts learned in this course.
Among the useful skills & techniques learned during the course are: Numpy & Pandas to parse, clean & analyze data, and Matplotlib & Seaborn to create visualizations.

How to run the code

This is an executable Jupyter notebook hosted on Jovian.ml, a platform for sharing data science projects. You can run and experiment with the code in a couple of ways: using free online resources (recommended) or on your own computer.

Option 1: Running using free online resources (1-click, recommended)

The easiest way to start executing this notebook is to click the "Run" button at the top of this page, and select "Run on Binder". This will run the notebook on mybinder.org, a free online service for running Jupyter notebooks. You can also select "Run on Colab" or "Run on Kaggle".

Option 2: Running on your computer locally

  1. Install Conda by following these instructions. Add Conda binaries to your system PATH, so you can use the conda command on your terminal.

  2. Create a Conda environment and install the required libraries by running these commands on the terminal:

conda create -n zerotopandas -y python=3.8 
conda activate zerotopandas
pip install jovian jupyter numpy pandas matplotlib seaborn opendatasets --upgrade
  1. Press the "Clone" button above to copy the command for downloading the notebook, and run it on the terminal. This will create a new directory and download the notebook. The command will look something like this:
jovian clone notebook-owner/notebook-id
  1. Enter the newly created directory using cd directory-name and start the Jupyter notebook.
jupyter notebook

You can now access Jupyter's web interface by clicking the link that shows up on the terminal or by visiting http://localhost:8888 on your browser. Click on the notebook file (it has a .ipynb extension) to open it.

Downloading the Dataset

!pip install jovian opendatasets --upgrade --quiet

Let's begin by downloading the data, and listing the files within the dataset.