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.

This exercise is part of the course

Interactive Data Visualization with Bokeh

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Exercise instructions

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.

Hands-on interactive exercise

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

# 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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