Hi all,
I have two data sources with data separated by month.
- Left Table Source 1 has data in Jan & Feb.
- Right Source 2 does not have data in those months..
I have chosen Left Outer join so it would display all data from Source 1 and additional from Source 2.
- When pulling up the data, the table shows on Dimension Date “Null” for the months that Source 2 does not have data.
- The sum function of both source 1 and 2 shows “Null” as well.
How can I correct this situation that the chart still shows the data present in Source 1 even thought Source 2 lacks that?
However, when I
Hi,
You’re actually very close, this is normal and expected behaviour in Looker Studio.
When you use a Left Outer Join, the join keeps all the records from your left table (Source 1) and only brings in matching records from your right table (Source 2). So, if Source 2 doesn’t have data for certain months, those fields will appear as Null.
That’s why your table shows “Null” for Date and sums when Source 2 is missing data. It doesn’t mean the join failed, it just means there’s no corresponding data on the right side.
To fix how it looks, create a calculated field using something like:
SUM(IFNULL(Sales, 0))
This ensures that Null values are treated as 0 during aggregation, allowing your totals from Source 1 to display correctly even when Source 2 has no data. In short, your setup is correct, this is expected behaviour for Left Outer Joins when one source doesn’t contain matching records.
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Hi,
Thank you for your response as it is very helpful.
How would the IFNULL function work for missing months? Now it displays the missing months as null as well.
Hi,
For missing months, you can apply the IFNULL() function to substitute null values with a meaningful label, ensuring your report remains clear and consistent. This way, instead of showing null for months without data, a descriptive placeholder will appear. However, if those months are completely absent (no rows exist for them), you’ll need to ensure your date dimension includes all months.
I hope this helps, if not, feel free to share a snapshot of your data so I can provide a more precise and tailored explanation.