Building a popularity histogram
You've calculated quantiles and binned streams - now visualize the full popularity distribution to complete your analysis. The popularity column from the Spotify dataset ranges from 0 to 100. Build histogram counts with custom bin edges, then plot the distribution with Plotly to see where most albums cluster.
polars is loaded as pl and plotly.express as px. The DataFrame spotify is available.
Questo esercizio fa parte del corso
Data Transformation with Polars
Istruzioni dell'esercizio
- Build histogram counts from
popularitywith bins at 0, 25, 50, 75, and 100. - Create a bar chart with
categoryon the x-axis andcounton the y-axis.
esercizio interattivo pratico
Prova questo esercizio completando questo codice di esempio.
# Build histogram counts with custom bins
hist = spotify["popularity"].____(bins=[0, 25, 50, ____, ____])
# Create a bar chart of the distribution
fig = px.____(hist, x="____", y="____")
fig.show()