This is the first BLU in the Data Wrangling specialization. In this specialization you'll learn how to get data from multiple data sources and how to transform raw data into clean enough data so that you can begin your data science workflow.
In this BLU, we'll start by learning some Jupyter notebooks magics, that can be very useful. Then, we'll learn about file formats and how to read them efficiently into pandas DataFrames. Finally, we'll practice some data cleaning, using string methods and other tools.
- Install all the needed dependencies, specified in the requirements.txt file
- Install via pip
pip install -r requirements.txt
- Install via conda
conda install --file requirements.txt
- Install via docker
sh run-jupyter-notebook.sh
- Go through the Learning Notebooks (they are in the Learning Notebooks folder)
- Do the Exercise notebook, and submit it on the portal as usual
You can and should ask for help, be it about Learning Notebooks, Exercises, or anything else. Please checkout the How to Ask for Help, and remember not to share code when asking for help about the exercises!
This repo is completely open source and is continuously improving over time. When you spot a mistake, please check whether it has been detected in the issues. If it hasn't, please open an issue, explaining in details where it is (e.g. in what notebook, and on what line), and how to reproduce the error. If it is an easy fix, feel free to make a pull request.