I have a simple Data Studio table consisting of two columns. The first column is the week (ISO Year Week) and the second column is the total registrations we've received for that week.
However, my Week column repeats 7 times (7 Rows) for each week as it's counting by day within that week. See below:
Is there any way to get this to group by the listed week? Below are my settings:
Dimension = Conversion Date set as "ISO Year Week" for the type.
Metric = Equals the count of Conversion Date (Same Conversion Date field used for dimension)
Any help would be much appreciated.
There might be an issue with the date format of the source. Without knowing the source (e.g. Google Analytics or Sheets) it’s hard to tell.
Blended Data
I recently had this issue with blended data. The response of a similar question helped me to find a way.
Basically you have to add a new custom field to the data source with the formula WEEK(date_field_link). Data studio will recognise this as a date in compatibility mode, but for me it still works. Then you can use this new date field as a join key to blend the data while grouping it in weeks.
Normal Data
If this problem appears in a regular non-blended dataset you might want to check if Data Studio correctly catches the date as a date. This help article from Google might be worth checking out: https://support.google.com/datastudio/answer/6401549?hl=en#zippy=%2Cin-this-article
I made a similar case work using blended data.
Your column "Conversion Date" repeats the same week 7 times because it's just a display value. Every row has a date value (year, month and a day) but you're just showing the corresponding week. So, data-studio treats them as different data and doesn't group them.
To be able to group them by Week you need to create a new field with a value containing only the week and the year. So, you can use the formula
YEARWEEK(your_date)
The resulting Date will be groupable.
NB1: If your date isn't of the type Date, you can parse it from text to date using
the method:
PARSE_DATE("%Y-%m-%d", your_date_text)
NB2: If the created field has the type number and doesn't show the possibility to change type to Date, you can do this trick: (it's weird but it works):
First type as a formula for the created field and apply:
MONTH(your_date)
This will unlock the compatibility Date types. You can choose from them the ISO Year Week type.
and then change the formula from MONTH(your_date) to YEARWEEK(your_date) [your formula] as I explained above. The chosen date type won't go away even if it wasn't available the first time.
Related
I have a table with column "date" in YYYY-MM-DD format HH:MM:SS:MMM (2015-01-27 11:22:03:742). I'm trying to make a time series with the dimension of month/year grouping, to display the total number of records by period.
Settings:
period dimension: date (type: date and time)
period: date (type: year and month)
metric: record count
My time graph doesn't display anything. Can someone help me identify what's going on?
formatDate is the column created with the expression:
PARSE_DATETIME("%Y-%m-%d %H:%M:%S",REGEXP_EXTRACT( create_date,"(.*):[0-9]*"))
Using the date in its standard format, as mentioned at the beginning of the question, the same happens.
When entering dates (original and formatted), both appear with null values.
The milliseconds have to be separated by a . not a :. An option is to import your date a as string/text and add a calculated field, which parse the string in Data Studio:
PARSE_DATETIME("%Y-%m-%d %H:%M:%S",REGEXP_EXTRACT( data_field,"(.*):[0-9]*"))
If the dates are several years in the past, please adjust the Default date range in your graph:
I leave the solution to my problem to the community.
The problem is in the date format. Failed to get Google Data Studio to receive a date with milliseconds. By removing the milliseconds it was possible to work with the dates normally, managing to apply the available functions.
Note: It may be a knowledge limitation, but none of the date formatting functions work if the datetime field contains milliseconds (FORMAT_DATETIME, PARSE_DATETIME,...)
I am having trouble with a line graph visual, where the data is organized by week number and by year number. However when I put the information into the visual and try viewing both 2020 & 2021, it rearranges the data in the order of 2021 & 2020. How do i get it to properly see the data in the correct order of week number by year?
I tried sorting the week # by an index value, also by year, also by week... with no luck
From the images it looks like there is no sort on the year and week, just by the week.
You need to add a column that has a year week key, that you can sort by.
For example 202101 for the week one of 2021.
Assuming you have a date like dd/mm/yyyy format, for example 11/04/2021 in DAX you can use:
YearWeek = YEAR('Table'[Date]) & WEEKNUM('Table'[Date])
This should now sort the data correctly. If you want you can add another column, that is more user friendly like WK01-2021, if you wish, you can then sort by that column, or use the new key column to sort the textual one.
If you just have a year and week column, create a new column that concatenates the two.
For this you should have a Calendar table, that contains a the date groupings that you you need. For example using CALENDARAUTO or you can do it in Power Query here or here.
This actually does not give the correct sequence, when you are dealing with single digit week numbers. For example when dealing with the first ten weeks of 2020, the sequence would be 20201, 202010,20202, 20203... which is obviously wrong.
Here you need a double digit Week number, so a small change in the suggested formula should do it:
YearWeek = YEAR('Table'[Date]) & FORMAT(WEEKNUM('Table'[Date]),"00")
The sequence should now work.
I linked Firebase to BigQuery and start using Google Data Studio to create a table to list users by "User Pseudo ID".
My goal is to calculate the difference between two dates, the date of first_open and the date of app_remove to come up with an average retention time.
How can I write the right query in Data Studio?
It can be achieved using the three step process below:
1) HH:MM:SS
The Calculated Field below uses the DATETIME_DIFF function to find the difference between app_remove and first_open, and displays the difference in SECOND (for future reference, set the third input DATETIME_DIFF as required, for example, to view the difference in days, set the input to DAY):
DATETIME_DIFF(app_remove, first_open, SECOND)
2) Type (HH:MM:SS)
Number > Duration (Sec.)
3) Aggregation (HH:MM:SS)
AVG
Google Data Studio Report and a GIF to elaborate:
DATE_DIFF may be what you are looking for.
That is if first_open and app_remove are date fields or date expressions
I need to create a YYYYMM format computed column for defining a date in Data Studio since our data is held in separate year, month, and day columns. Unfortunately our the month and day fields are not left zero-padded so a simple concat will not work.
The formula I'm using still uses concat, but also uses todate to parse the hyphenated date string into the compatible format.
TODATE(CONCAT(systems.added_year, CONCAT('-', concat(systems.added_month, concat('-', systems.added_day)))), 'DEFAULT_DASH', '%Y%m')
The problem I'm running into, is that Data Studio doesn't seem to correctly recognize the resultant value, even though it seems to be correct. I'm not sure why, but the YYYYMM field seems to one-month behind even though the result of the calculated field looks correct.
In fact it seems 1-day behind, if I show YYYYMMDD the displayed value is the last day of the previous month.
Here is a screenshot showing the component elements, a string version of the calculated field, and then a Date(YYYYMM) version of the calculated field.
Looks like a bug with the output format. As a workaround, you could output as a full date and then change the column format to YYYYMM.
TODATE(CONCAT(year, CONCAT('-', CONCAT(month, CONCAT('-', day)))), 'DEFAULT_DASH', '%Y-%m-%d')
You could also use '-01' as the last segment.
I have a PivotTable (actually it is five PivotTables, each on its own separate sheet) that is created from a query of an outside database. Each of the PivotTables represents a day (i.e. Today, Tomorrow, Today+2, Today+3, and Today+4). For the report filter for the first two, we use a date range filter of today and tomorrow which automatically filters the data and allows it to roll over. We created custom date ranges for the other three days, but upon every external data refresh we have to go into each sheet and reselect the report filter from all to the specified time frame. This data rolls over every day so we can see the lineup for the next 96 hours out.
Is there a way to either keep the PivotTable report filter criteria (VBA and macros are both acceptable, although we are also fairly new to both)?
Or is there some super secret way to extend the report filter from just today and tomorrow to a time range (48 hours, 96 hours) instead of next month?
I need the days to be separated, so next week will not work because all the days will populate on one page.
Without seeing a real example it's hard to tell, but how about changing the query to a relative date index, i.e. something like
SELECT DATEDIFF('day', GETDATE(), report_dt) AS days_from_today FROM reporting_table
And then set your report filters on this relative date index (days_from_today = 1 for tomorrow, etc)? You can always create another Excel column in the report =TODAY() + days_from_today to get your absolute date back. (Assuming you are just dealing with one time zone for reporting purposes.)
I.e., instead of rolling filters, keep the filters on constant indices, and let the indices cover a rolling date range. I'm not sure Excel is smart enough to do the rolling filters thing.