You have a table in a Fabric lakehouse that contains the following data: | SalesOrderNumber | OrderDate | CustomerName | Email | |------------------|------------|----------------|---------------------

You have a table in a Fabric lakehouse that contains the following data:

SalesOrderNumber	OrderDate	CustomerName	Email
SO49172	2021-01-01	Brian Howard	[email protected]
SO49173	2021-01-01	Linda Alvarez	[email protected]
SO49174	2021-01-01	Gina Hernandez	[email protected]
SO49178	2021-01-01	Beth Ruiz	[email protected]
SO49179	2021-01-01	Evan Ward	[email protected]

You have a notebook that contains the following code segment:

01 df = df.withColumn('CustomerName', when(col('CustomerName').isNull() | (col('CustomerName')==''), lit('Unknown')).otherwise(col('CustomerName')))
02 df = df.withColumn('Username', split(col('Email'), '@').getItem(0))
03 df = df.dropDuplicates(['OrderDate']).selectExpr('*', "year(OrderDate') as Year", "('CustomerName') as Username")
04 display(df.head(10))

For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point. Statements:

1. Line 01 will replace all the null and empty values in the CustomerName column with the Unknown value.
2. Line 02 will extract the value before the @ character and generate a new column named Username.
3. Line 03 will extract the year value from the OrderDate column and keep only the first occurrence for each year.