High to low prices by region
Now you know how to sort a DataFrame, the estate agents have asked you to create a bar plot visualizing the average property price by region from largest to smallest.
regions
has been created by grouping melb
by region and calculating the average price, and preloaded for you:
regions = melb.groupby("region", as_index=False)["price"].mean()
This exercise is part of the course
Interactive Data Visualization with Bokeh
Exercise instructions
- Sort
regions
by price in descending order. - Create the figure, setting
x_range
equal to the"region"
column ofregions
and labeling the x- and y-axes as"Region"
and"Sales"
, respectively. - Add bar glyphs from
regions
, showing theprice
on the y-axis against eachregion
on the x-axis, and setting the width to0.9
- Update the y-axis format to display in millions of dollars with 1 decimal place.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Sort df by price in descending order
regions = regions.____("____", ascending=____)
# Create figure
fig = figure(x_range=____, x_axis_label=____, y_axis_label=____)
# Add bar glyphs
fig.vbar(x=____, top=____, width=____)
# Format the y-axis to numeric format
fig.____[____].____ = ____(____="$0.0a")
output_file(filename="sorted_barplot.html")
show(fig)