Analyzing Web page data using Power BI Desktop (tutorial)

In this tutorial, you learn how to import a table of data from a Web page and create a report to visualize this data. As part of this process, you navigate across tables available on a web page, and apply data transformation steps to bring the table into a new shape.

In this article:

  • Task 1: Connect to a web data source
  • Task 2: Shape data in the Query view
    • Step 1: Remove Other Columns to only display columns of interest
    • Step 2: Replace Values to clean up values in a selected column
    • Step 3: Filter values in a column
    • Step 4: Rename a column
    • Step 5: Filter null values in a column
    • Step 6: Rename a query
    • Query Steps created
  • Task 3: Create visualizations using the Report view
    • Step 1: Load the query to your report
    • Step 2: Create a Map visualization

Task 1: Connect to a web data source

In task 1, you import a Tournament Summary table from the UEFA European Football Championship Wikipedia page at the following location: http://en.wikipedia.org/wiki/UEFA_European_Football_Championship



Add a Wikipedia page data source

  1. In the Getting Started dialog or in the Home ribbon tab, select Get Data.
  2. This brings up the Get Data dialog, where you can pick from a wide range of data sources to import data into Power BI Desktop. We will select Web which is available under the All or Other group.
  3. In the Web Content dialog box, in the URL text box, paste the Wikipedia URL (http://en.wikipedia.org/wiki/UEFA_European_Football_Championship).
  4. Click OK.

After establishing a connection to the web page, you see a list of tables available on this Wikipedia page in the Navigator dialog. You can single-click on each of these tables to preview the data.

In the Navigator left-pane, select the Results[edit] table for the Tournament Summary results, or select the Results[edit] table and select Edit. This will allow us to reshape this table before loading it to the Report, since the data is not in the shape that we need for our analysis.

This will land a preview of the table in the Query view, where we can apply a set of transformation steps to clean up the data.

Task 2: Shape data in the subject table

Now that you have the subject table selected for your data query, you learn how to perform various data shaping and cleansing steps.

Step 1: Remove Other Columns to only display columns of interest

In this step, you remove all columns except Year and Final Winners.

  1. In the Query Preview grid, select the Year and Final Winners columns (use CTRL + Click).
  2. Right-click a column header in the Query Preview grid, and click Remove Other Columns to remove the unselected columns. Note that this operation is also available in the Home ribbon tab, in the Manage Columns group.

Step 2: Replace Values to clean up values in a selected column

In this step, you replace the Details suffix in the Year column. Note that this suffix is on a new line so it is not visible in the table preview. However, if you click in one of the cells with a numeric value in the Year column, you will see the full value in the detailed view.

  1. Select the Year column.
  2. In the Query view ribbon, click Replace Values under the Home tab or right-click the Year column, and click Replace Values to replace Details with empty text.
  3. In the Replace Values dialog box, type Details in the Value to Find text box and leave the Replace With text box empty.
  4. Click OK.

Step 3: Filter values in a column

In this step, you filter the Year column to display rows that do not contain “Year”.

  1. Click the filter drop down arrow on the Year column.
  2. In the Filter drop-down, clear the Year option.
  3. Click OK.

Step 4: Rename a column

Now that we have cleaned up the data in the Year column, we are going to work on the Final Winner column.

Since we are only looking at the list of winners, we can rename this column to Country.

  1. Select the Final Winner column in the Query preview.
  2. In the Query view ribbon, under the Transform tab and Any Column group, you will find Rename.
  3. This will make the column name editable. We will rename this column to Country.

Step 5: Filter out null values in a column

We also need to filter out null values in the Country column. In order to do this, we could use the filter menu as we saw in Step 3, or alternatively we can:

  1. Right-click on one of the cells in the Country column that contain a null value.
  2. Select Text Filters -> Does not Equal in the context menu.
  3. This creates a new filter step to remove rows with null values in the Country column.

Step 6: Name a query

In this step, you name your final query Euro Cup Winners.

  1. In the Query Settings pane, in the Name text box, enter Euro Cup Winners.

Task 3: Create visualizations using the Report view

Now that we have converted the data into the shape that we need for our analysis, we can load the resulting table into our Report and create a few visualizations.

Step 1: Load the query to your report

In order to load the query results to Power BI Desktop and create a report, we select Close & Load from the Home ribbon.

This will trigger evaluation of the query and load of the table output to the Report. In Power BI Desktop, select the Report icon to see Power BI Desktop in Report view.

You can see the resulting table fields in the Fields pane at the right of the Report view.

Step 2: Create a Map visualization

In order to create a visualization, we can drag fields from the Field list and drop them in the Report canvas.

  1. Drag the Country field and drop it in the Report canvas. This will create a new visualization in the Report canvas. In this case, since we have a list of countries, it will create a Map visualization.

  2. We can easily change the type of visualization by clicking on a different icon in the Visualization pane.

  3. We are going to stay with the Map visualization type to Map, We can also resize the visualization by dragging from one of the corners of the visualization up to the desired size.

  4. Note that currently all the points in the map have the same size. We want to change this so that countries with more Euro Cup tournaments won are represented with a larger point in the map. In order to do thiso, we can drag the Year field in the Fields list to the Values box in the lower half of the Fields pane.

As you can see, it is very easy to customize visualizations in your report, in order to present the data in the way that you want. Power BI Desktop provides a seamless end-to-end experience from getting data from a wide range of data sources and shaping it to meet your analysis needs to visualizing this data in rich and interactive ways. Once your report is ready, you can upload it to Power BI and create dashboards based on it, which you can share with other Power BI users.

This concludes the Importing Data from the Web tutorial. You can download the completed Power BI Desktop file here.

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