You load a CSV and run the head(3) method to see the top few…
You load a CSV and run the head(3) method to see the top few rows of data. You see: df[“revenue”].head() #0 “$1,250.00” #1 “$980.50” #2 None #3 “$2,100.00” Which approach most directly converts revenue into a numeric column (float) with missing values preserved as NaN?
Read DetailsYour transaction table should have one row for each combinat…
Your transaction table should have one row for each combination of order_id and line_item_id. In other words, multiple rows can have the same order_id, and multiple rows can have the same line_item_id; but no two rows should have the same order_id and the same line_item_id. What is the best check?
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