Why Power Query transforms messy data in Excel - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to load data into Power Query.

Excel

let Source = Excel.CurrentWorkbook(){[Name=[1]]}[Content] in Source

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A"Range1"

B"Sheet1"

C"Data"

D"Table1"

Attempts:

3 left

💡 Hint

Common Mistakes

Using sheet names instead of table names

Forgetting quotes around the name

Power Query loads data from named tables like "Table1" in Excel.

2fill in blank

medium

Complete the code to remove empty rows in Power Query.

Excel

CleanedData = Table.SelectRows(Source, each [1] <> null)

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AText.Length([Column1])

BList.Count([Column1])

C[Column1]

DRecord.FieldCount([Column1])

Attempts:

3 left

💡 Hint

Common Mistakes

Using functions that don't apply to the column type

Checking for empty string instead of null

Checking if the value in [Column1] is not null removes empty rows.

3fill in blank

hard

Fix the error in the code to change data types.

Excel

ChangedType = Table.TransformColumnTypes(Source, {{"Date", [1])

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Atype date

Btype text

Ctype number

Dtype datetime

Attempts:

3 left

💡 Hint

Common Mistakes

Using text or number type instead of date

Missing the type keyword

To convert a column to date type, use type date.

4fill in blank

hard

Fill both blanks to filter rows where sales are greater than 1000.

Excel

FilteredRows = Table.SelectRows(Source, each [[1]] [2] 1000)

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ASales

B>

C<

DQuantity

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong column name

Using less than operator instead of greater than

We filter rows where the Sales column is greater than 1000.

5fill in blank

hard

Fill all three blanks to create a new column with doubled sales values for sales above 500.

Excel

AddedColumn = Table.AddColumn(Source, "DoubleSales", each if [[1]] [2] [3] then [Sales] * 2 else [Sales])

Drag options to blanks, or click blank then click option'

ASales

B>

C500

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong operator

Using wrong threshold value

Checking wrong column

This adds a new column doubling sales only if sales are greater than 500.

Practice

1. Why do people use Power Query in Excel when working with messy data?

easy

A. To clean and organize data easily without complex formulas

B. To create charts and graphs automatically

C. To write VBA macros for automation

D. To send emails directly from Excel

Solution

1. Step 1: Understand Power Query's main purpose

   Power Query is designed to clean and transform messy data into a usable format.

2. Step 2: Compare options with Power Query features

   Creating charts, writing macros, or sending emails are not Power Query's main functions.

3. Final Answer:

   To clean and organize data easily without complex formulas -> Option A

4. Quick Check:

   Power Query = Easy data cleaning [OK]

Hint: Power Query cleans data without formulas [OK]

Common Mistakes:

• Confusing Power Query with chart tools
• Thinking Power Query writes macros
• Assuming Power Query sends emails

2. Which of these is the correct way to start Power Query in Excel?

easy

A. Open the Review tab and select Spell Check

B. Press Ctrl + C to copy data

C. Use the Insert tab to add a new chart

D. Go to Data tab and click Get & Transform Data

Solution

1. Step 1: Identify where Power Query is located

   Power Query is accessed from the Data tab under Get & Transform Data.

2. Step 2: Eliminate unrelated options

   Copying data, spell check, and inserting charts are unrelated to starting Power Query.

3. Final Answer:

   Go to Data tab and click Get & Transform Data -> Option D

4. Quick Check:

   Power Query start = Data tab [OK]

Hint: Power Query is under Data tab in Excel [OK]

Common Mistakes:

• Trying to start Power Query from Insert tab
• Confusing copy shortcut with Power Query
• Looking in Review tab for Power Query

3. You load a table with extra spaces and inconsistent capitalization into Power Query. After applying the 'Trim' and 'Lowercase' steps, what will the data look like?

medium

A. Data with spaces removed but original capitalization kept

B. Data unchanged with spaces and mixed case

C. Data with no extra spaces and all letters in lowercase

D. Data converted to uppercase with spaces kept

Solution

1. Step 1: Understand the 'Trim' step effect

   'Trim' removes extra spaces from text values in Power Query.

2. Step 2: Understand the 'Lowercase' step effect

   'Lowercase' converts all text letters to lowercase.

3. Final Answer:

   Data with no extra spaces and all letters in lowercase -> Option C

4. Quick Check:

   Trim + Lowercase = clean lowercase text [OK]

Hint: Trim removes spaces; Lowercase changes text to small letters [OK]

Common Mistakes:

• Thinking Trim changes capitalization
• Assuming Lowercase removes spaces
• Believing data stays unchanged

4. You tried to remove duplicates in Power Query but still see repeated rows. What is the likely mistake?

medium

A. You removed duplicates before trimming spaces, so spaces differ

B. You applied the Remove Duplicates step twice

C. You forgot to load the data back to Excel

D. You used the Filter Rows step instead of Remove Duplicates

Solution

1. Step 1: Understand how spaces affect duplicates

   Extra spaces make rows look different, so duplicates remain if not trimmed first.

2. Step 2: Check the order of steps

   Removing duplicates before trimming spaces won't remove all duplicates correctly.

3. Final Answer:

   You removed duplicates before trimming spaces, so spaces differ -> Option A

4. Quick Check:

   Trim first, then remove duplicates [OK]

Hint: Trim spaces before removing duplicates [OK]

Common Mistakes:

• Removing duplicates before cleaning data
• Confusing Filter Rows with Remove Duplicates
• Not loading data back to Excel

5. You have a messy sales data table with missing dates, extra spaces, and inconsistent product names. Which sequence of Power Query steps will best clean this data?

hard

A. Remove duplicates, Change product names to uppercase, Trim spaces, Remove rows with missing dates

B. Remove rows with missing dates, Trim spaces, Change product names to lowercase, Remove duplicates

C. Change product names to lowercase, Remove duplicates, Remove rows with missing dates, Trim spaces

D. Trim spaces, Remove duplicates, Remove rows with missing dates, Change product names to uppercase

Solution

1. Step 1: Remove rows with missing dates first

   Missing dates cause incomplete data, so remove those rows early.

2. Step 2: Trim spaces and standardize product names

   Trim spaces to clean text, then convert product names to lowercase for consistency.

3. Step 3: Remove duplicates last

   After cleaning, duplicates can be accurately identified and removed.

4. Final Answer:

   Remove rows with missing dates, Trim spaces, Change product names to lowercase, Remove duplicates -> Option B

5. Quick Check:

   Clean data stepwise: remove blanks, trim, standardize, then dedupe [OK]

Hint: Clean missing data first, then trim and standardize before deduplication [OK]

Common Mistakes:

• Removing duplicates before cleaning text
• Trimming spaces after removing duplicates
• Changing case inconsistently