Power BI Tutorial: Transform data from folder data source

Data for the tutorial can be obtained by downloading CSV files from:


For the tutorial I downloaded data for Alabama, Alaska and Arizona into a folder. Open the CSV files, and notice that all of them have the same layout. In this tutorial we are going to:

  • Read data from the folder data source
  • Concatenate all the CSV files in the folder
  • Notice that state name exists in cell A2 in all the files. We are going to parse the state name from here and add it as a column
  • Clean up all the comments
  • Delete data for Males and Females and save data for BOTH SEXES

Step 1: Create connection to folder data source

  • Open a new Excel work book
  • From the ribbon, click on POWER QUERY -> From File -> From Folder
  • Dialogue box opens. Browse to the folder where the CSV files are located. Click Ok
  • This creates a connection to the folder as the data source
  • Query editor opens
  • Notice that an excel file exists in the folder. If you do have other file formats, filter it out by clicking on the arrow next to Extension and select .csv
  • Click on the two arrows next to Content. This will concatenate all the CSV files and open it in the query editor

Step 2: Using Power Query to transform data

  • To create a column with state names, create a copy of Column1 by right clicking on Column1 and selecting Duplicate Column
  • A duplicate column is created all the way to the right. If you are not there already, scroll to the new column
  • Select the cell that has the state name. From the ribbon select Home -> Split Column -> By Delimiter
  • Split Column by delimiter dialogue box opens
  • From the drop down select Custom
  • Enter “Table 2. Intercensal Estimates of the Resident Population by Sex and Age for” in the text area below Custom drop down
  • Click Ok
  • Notice column is split into two
  • Select Column1 – Copy.1 and right click. Select Remove
  • In Column1 – Copy.2 select the cell with the state name in it
  • From the ribbon select Home -> Split Column -> By Delimiter
  • Split Column by delimiter dialogue box opens
  • From the drop down select Colon. Click OK
  • Notice column is split into two. One column with the state name we need
  • Highlight Column1 – Copy.2.2, right click and select Remove
  • Highlight the cell with state name in Column1 – Copy.2.1
  • From the ribbon select Transform -> Fill -> Down
  • Notice state name is filled in the columns
  • Right click Column1-Copy2.1 and rename column as State
  • Scroll to the left and select the first cell in Column1
  • Right click and select Text Filters -> Does Not Contain
  • This will remove the row. Also notice that there are a few more rows in Column1 which has the word “table” and we need to remove these rows
  • From the APPLIED STEPS panel on the right, click on the gear next to Filtered Rows1
  • Filter Rows dialogue box opens

  • Replace text “table with row headers in column A and column headers in rows 3 through 4. (leading dots indicate sub-parts)” with “table”.
  • Select “And” option and in the second drop down select “does not contain” and enter “Table” in the text area
  • Click OK
  • This will remove all the rows with the word “table” or “Table” in the Column1
  • Similarly remove all rows in Column1 with the word “Sex and Age” by right clicking on “Sex and Age” and selecting Text Filters -> Does not equal
  • From the ribbon, click on Home -> Use First Row As Headers”
  • Rename the first column as “Category”
  • Rename column “_1” as “2000 Census”
  • Notice that in the file there is data for BOTH SEXES, MALE and FEMALE. We want just BOTH SEXES. To achieve this, add a Custom column
  • From the ribbon click Add Column -> Add Custom Column
  • Add Custom Column dialogue box opens
  • In the formula enter following:if [Category]=”BOTH SEXES” then “BOTH SEXES” else if [Category]=”MALE” then “MALE” else if [Category]=”FEMALE” then “FEMALE” else null
  • Highlight the Custom column, from the filter select Transform -> Fill -> Down
  • Notice Custom column if filled with BOTH SEXES, MALE and FEMALE
  • Filter Custom column and select BOTH SEXES only
  • Notice this filters out MALE and FEMALE categories
  • Scroll to the right and Remove columns _2 and _3
  • Highlight all the year columns 2000 Census, 2000, 2001 through 2009
  • From the ribbon, select Transform -> Unpivot Columns -> Unpivot Columns
  • Rename Attribute column as Year

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