Jupyter , pandas python.
I recommend using Python for this. You are free to use any external libraries you like (e.g. scikit-learn, pandas, seaborn, etc.), as long as you document which ones you used in the report. You can use both Python scripts and IPython notebooks for implementation as you see fit.
The first stage in the pipeline is to preprocess and clean the dataset.
31 фрилансеров(-а) в среднем готовы выполнить эту работу за €170
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