And we pore over customer reviews to find out what matters to real people who already own and use the products and services we’re assessing. We gather data from the best available sources, including vendor and retailer listings as well as other relevant and independent reviews sites.

At this point, you can Close and Load the Editor, and all your data will appear on an Excel worksheet.ZDNET's recommendations are based on many hours of testing, research, and comparison shopping.

A new column will appear next to your data set as per the rules set in the Conditional Column.

You can continue to add as many clauses to the column as required, and then click OK.

If none of these clauses are true, then, we set the Else value to Miscellaneous.

We click the Add clause button to create our next rule.

For the purpose of this data set, if the Transaction column contains the value E-TRANSFER (case sensitive) then the category assigned to it should be Email Transfer Received.

In the dialog box for Conditional Column, insert the column name (in this case it’s Category), and then assigned conditions through clauses.

Click on Add Column > Conditional Column and a dialog box will appear asking you to assign conditions/clauses to organize your data.

Next, we will use the Conditional Column command, which is quite useful in cleaning up and organizing bank data.

A dialog box will appear asking for the number of rows that need to be removed. Use the Remove Rows option to remove any unwanted data that has been exported from the PDF.Right-click on the Column to rename the columns as required.

Your data will then show up in the Power Query Editor, where you can clean it up.

In the file data preview, click on Transform Data or Edit (depending on your OS).

Select the CSV file downloaded earlier, then click on Get Data, then click Next.

Under Choose Data Source, select Text/CSV.

To clean the bank activity, you will need the Power Query Add-in in Excel.

Cleaning up will allow your data to be more concise and easier to read.

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