import pandas as pd
from pandas.plotting import scatter_matrix
pd.set_option('display.max_columns', None) # do not truncate columns
pd.set_option('display.max_rows', 100) # show up to 100 rows
import altair as alt
alt.__version__
import seaborn as sns
#Switch to Jupyter Notebook mode of matplotlib (pandas is using matplotlib for the scatterplot matrix)
%matplotlib inline
df = pd.read_csv('./soccer.csv') # Load the dataset
# Inspect the dataset
# See https://pandas.pydata.org/pandas-docs/stable/reference/frame.html
df.dtypes # No semicolon to see the output in the notebook
# Take a glimpse into the data
df.head() # No semicolon to see the output in the notebook
You are free to preprocess the data.
Select a categorical attribute and encode its values with color in the scatterplot matrix (e.g. with altair again or seaborn pairplot).
TODO: Share your top-2 insights from the scatterplot matrix/matrices
TODO: Share your top-2 insights from the heatmap
Please download this notebook as HTML (File > Download As... > HTML (.html)) and submit it.