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Annotating Netflix stock price growth

As a reminder, you previously created dates and timestamps, displayed below:

start_date = dt.datetime(2017, 6, 30)
end_date = dt.datetime(2017, 7, 27)
start_float = start_date.timestamp() * 1000
end_float = end_date.timestamp() * 1000

The final steps to display the Netflix line plot with a polygon annotation are to subset the data for the stock price, call PolyAnnotation(), and add the annotation to the figure's layout.

Diese Übung ist Teil des Kurses

<Kurs>Interactive Data Visualization with Bokeh</Kurs>
Kurs ansehen

Übungsanweisungen

  • Create start_data by subsetting netflix for the row where "date" equals start_date.
  • Repeat for end_data to get the close value from end_date.
  • Create polygon, fill in "green", with 0.4 transparency, and finish the xs and ys arguments.
  • Add polygon to the figure's layout.

Interaktive praktische Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# Create start and end data
start_data = netflix.loc[netflix["____"] == ____]["close"].values[0]
end_data = ____.____[____["____"] == ____]["close"].values[0]

# Create polygon annotation
polygon = PolyAnnotation(fill_color="____", fill_alpha=____,
                         xs=[start_float, ____, end_float, ____],
                         ys=[start_data - 10, ____ + 10, end_data + 15, ____ - 15])

# Add polygon to figure and display
fig.____(____)
output_file(filename="netflix_annotated.html")
show(fig)
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