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Styling scientific research

Now you have mastered customizing your plots it is time to let your creative energy flow!

In this exercise, you are continuing your work with the Antarctic research team to assist them to explore and understand the penguin data they have collected.

They have asked you to help them understand how the flipper length differs between species. Time is short, so you think a quick plotly.express visualization would do. However, they also want some specific customizations for the axes' titles and a timestamp annotation when the plot is generated.

Your task is to build a quick bar chart using plotly.express, including the specified customizations.

You have available a penguins DataFrame and timestamp variable which gives the current timestamp.

This exercise is part of the course

Introduction to Data Visualization with Plotly in Python

View Course

Exercise instructions

  • Create a plotly bar chart from the penguins DataFrame with the title Flipper Length (mm) by Species, the x-axis as spec, the y-axis as av_flip_length and different colors for spec.
  • Use the .update_layout() method to change the xaxis and yaxis text to Species and Average flipper length (mm) respectively.
  • Add an annotation to the plot without an arrow, placed at an x coordinate of 0.5 and a y coordinate of 1.1 with the timestamp when the plot was generated.
  • Show your plot!

Hands-on interactive exercise

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

# Create timestamp
timestamp = datetime.now()

# Create plot
fig = px.____(penguins, x=____, y=____, color="spec", title=____)

# Change the axis titles
fig.update_layout({____: {'title': {____: 'Species'}},
                  ____: {'title': {____: 'Average Flipper Length (mm)'}}})

# Add an annotation and show
fig.update_layout({'annotations': [{
  "text": f"This graph was generated at {____}", 
  "showarrow": False, "x": ____, "y": ____, "xref": "paper", "yref": "paper"}]})
____.____
Edit and Run Code