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.

Latihan ini adalah bagian dari kursus

Data Transformation with Polars

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Petunjuk latihan

Build histogram counts from popularity with bins at 0, 25, 50, 75, and 100.
Create a bar chart with category on the x-axis and count on the y-axis.

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# 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()

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