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.

本练习是课程的一部分

Data Transformation with Polars

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练习说明

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.

交互式实操练习

通过完成这段示例代码来试试这个练习。

# 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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