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This page has 1 thread | Add post

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Exercises

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Software ==>	Power BI (160 exercises)
Topic ==>	Query editor (9 exercises)
Level ==>	Relatively easy
Subject ==>	Power BI training

Importing, tidying up and filtering skyscraper data to create a column chart

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 .

Create a new Power BI Desktop file, and load a list of the world's tallest buildings from Skyscraper Centre. You can get a link to the relevant website at this page.

If you don't have Internet access you can use the CSV file in the above folder, but it might not be as much fun!

Add steps to your query so that it creates results like this:

Table of skyscrapers

We've lost the height in feet and some other columns, and split the city into City and Country.

Create a chart comparing the number of skyscrapers for each country:

Number of tall buildings by country

The number of buildings for each country.

Apply a filter to the visualisation within Power BI Desktop itself to show only countries having 5 or more skyscrapers:

Top 3 countries

United Arab Emirates, China and the US, if you're wondering ...

Save this file as Skyscrapers, and close down the Power BI instance that created it.

You can unzip this file to see the answers to this exercise, although please remember this is for your personal use only.

You can find other training resources for the subject of this exercise here:

This page has 1 thread

From:	sardor4ik
When:	05 Dec 22 at 19:51

these are only columns available. could not extract country column. even the csv file doesnt have it

RANK

NAME

CITY

STATUS

COMPLETION

HEIGHT

FLOORS

MATERIAL

FUNCTION

From:	Andy B
When:	06 Dec 22 at 09:12

The country is at the end of the city as an abbreviation (which is all that is shown in the chart). For example:

Nanchang (CN)

Reply

Reply

Head office

Kingsmoor House

Railway Street

GLOSSOP

SK13 2AA

London

Landmark Offices

99 Bishopsgate

LONDON

EC2M 3XD

Manchester

Holiday Inn

25 Aytoun Street

MANCHESTER

M1 3AE

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