Core Designer Certificate
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I am stuck at question 5, as per question 4, after filtering it, it should have 485 rows and 11 columns. I am getting expected output but I have noticed population column has no values, it's blank.
But as per question 5 we need to divide some columns by population, since population has null values only, it doesn't make any sense to divide it by population column. Can anyone please hep and confirm you guys are getting values in population column or it's blank?
Some columns ( Oil production (Etemad & Luciana) (terawatt-hours), meat_prod_tonnes, and Food Balance Sheets: Eggs - Production (FAO (2017)) (tonnes) ) report country total data. Transform these three columns into per-capita data.
- Hint 1: To convert from country “total” data to “per-capita” data divide by the country's population.
- Hint 2: The Formula page in the reference documentation shows the proper syntax for using formulas to read column values when the column names include spaces.
- Hint 3: You will not need the original columns (including Population) for further analysis.
Answers
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JordanB Dataiker, Dataiku DSS Core Designer, Dataiku DSS Adv Designer, Registered Posts: 295 Dataiker
Hi @ankush9646
,We're happy to help. You should not be seeing null values under Population, so please go back to your join recipe (step 3) to make sure the steps have been completed correctly. Note, you will need to use CO2_and Oil.csv as your base dataset (it should be the left most dataset). You can only select two datasets initially when selecting the join recipe (you have to add on the third dataset within the recipe). To do this, select the + button next to the C02_and_Oil dataset.
Next, when you've added all 3 datasets to the join, please go to "selected columns" and make sure that you see the Population column in the Urbanization_GDP_and_Population dataset is checked:
Then, you will want to add your filter within the "Post filter" section of the join recipe where year >= 2008 and <= 2012.
Once you run the recipe, your output dataset should look similar to this:
Please let us know if you have any questions.
Thanks!
Jordan