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Software ==>	Python (36 exercises)
Topic ==>	Matplotlib (2 exercises)
Level ==>	Relatively easy
Subject ==>	Python training

Show a bar chart of the number of tall buildings by country

This exercise is provided to allow potential course delegates to choose the correct Wise Owl Microsoft training course, and may not be reproduced in whole or in part in any format without the prior written consent of Wise Owl.

Before you can do this exercise, you'll need to download and unzip this file .

The Excel workbook in the above folder contains a list of the tallest buildings in the world (at the time of writing this exercise, at any rate):

Against each building is the city and country where it can be found.

The aim of this exercise is to create a chart showing the number of buildings by country:

Chart showing number of buildings for each country

No great surprise that China has by far the most tall buildings!

Read on for how to do this!

Start by reading the data into a Pandas dataframe, counting the number of buildings per country and turning the results into a NumPy array. Here's one way to do this:

# read Excel worksheet into dataframe (defaults to sheet 1)

buildings_table = pd.read_excel("c:/wiseowl/tallest buildings.xlsx")

# group by country and count buildings

country_counts = buildings_table["Country"].value_counts()

# turn first (index) column into a normal column

country_counts = country_counts.reset_index()

# change the column names

country_counts.columns = ["Country", "Number of buildings"]

# turn this into an array

country_data = country_counts.to_numpy()

As metnioned above, this is only one way to do this - there are many, many ways to skin a Panda in Python.

Now use barh to create a bar chart, adding a title and X and Y axis labels. Here are a couple of lines of code to remind you of how to proceed: