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Analyzing basketball stats

You have been contracted by a national basketball team to help them visualize and understand key player stats for their top 50 players.

They have requested you to create a plot comparing players' 'Field Goal Percentage' (FGP) vs. their 'Points Per Game' (PPG). This sounds like a great opportunity to utilize your scatterplot skills!

It is important that this graph is comparable to their other graphs. Therefore, all axes need to start at 0 and the y-axis (FGP) needs to have a range of 0-100, since it is a percentage.

You have available a bball_data DataFrame with columns FGP and PPG.

This exercise is part of the course

Introduction to Data Visualization with Plotly in Python

View Course

Exercise instructions

  • Create a plotly.express scatterplot with PPG on the x-axis and FGP on the y-axis and show it to see the default doesn't start at zero.
  • Use the update_layout() method to change the x-axis range to be from 0 to a buffer of 5 past the maximum of the PPG variable.
  • Now use the update_layout() method to update the range of the y-axis to be 0 to 100.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Create and show the plot
fig = px.scatter(
  data_frame=bball_data,
  x=___, 
  y=___,
  title='Field Goal Percentage vs. Points Per Game')
fig.show()

# Update the x_axis range
fig.update_layout({____: {'range': [____, bball_data['PPG'].max() + ____]}})
fig.show()

# Update the y_axis range
fig.update_layout({____: {'range' : [____, ____]}})
fig.show()
Edit and Run Code