I am trying to create a line chart counting all the optins per date, however the only dimension that is will allow me to choose from have to be a date column on my source. The problem with this is it only chooses from dates that are populated in those fields with an optin date.
For example: I have 5 optins on 1/1/2019, 0 on 1/2/2019, and 3 on 1/3/2019
If I use this series and want to include another metric, 1/2/2019 will not show anything for that other metric
I just want a standard everyday series that counts every metric on a given day. The google analytics connection source has a generic Date dimension but I can not figure out how it was done
Ive tried creating a new column with everydate on it and trying to use that as a dimension without any luck
You should be able to use a Time Series graph (of which there are 3 types) instead of a Line graph.
A Time Series will keep the days where no data is available unlike the Line Graph which only presents labels for those which have values in the data.
Related
I have imported my GA4 data into Google Data Studio and am trying to see how many giftcards have been sold by their value.
The item revenue metric in GA4 is equal to the giftcard value (i.e. revenue = $200 therefore $200 giftcard was sold).
I want to breakdown sales by giftcard value like so:
Giftcard (revenue)
Count
$200
4
$250
3
$300
6
To do this, I need to set a copy of item revenue as a dimension rather than a metric.
In Google Data Studio, I can create a calculated field with the following formula that should convert the item revenue into text:
CAST(Item Revenue AS TEXT)
The problem I'm having is that while the formula sets the field type as text, it is still regarded by GDS as a metric and can't be used as a dimension.
Even when I try to add text, GDS still recognises the field as a number:
CONCAT(CAST(Item Revenue AS TEXT), " giftcard")
To use a metric as a dimension you can make a combination of data. When defining the graphic element (table, for example) and the respective data source, just create a data combination, but do not combine the data with any other source and just define the combination with the initial data itself. So you will have the same data structure only through a combined structure.
When making a combination of data, data studio recognizes all calculated fields (metrics) as dimensions. Thus, it is possible to make the conversion.
Can I have a time series chart to display the last 6 months QTY sold? as the report filter is monthly based.
ex. Users can choose 2021/10/01 - 2021/10/31 to view the report and there is a chart to display the last 6 months QTY sold. In this case, the time series chart will display 2021/05/01 to 2021/10/31.
If users can choose 2021/06/01 - 2021/6/30 to view the report and there is a chart to display the last 6 months QTY sold. In this case, the time series chart will display 2021/01/01 to 2021/06/30.
Through my advanced knowledge of the platform, I am not aware of the possibility of obtaining the mentioned result.
It is not possible to use the date filter control element and the respective date range as an input variable to define the period dimension used in the temporal graph.
You will probably have to look for an alternative solution that doesn't match the proposed objective. Using a fixed period of the last 6 months, without the possibility of dynamic variation through the date control element. Or, use two date filter control elements, one for the time graph only. Solutions far from ideal.
The issue was solved, I created another data source for 6 months of sales.
I am trying to match date and time, and metric category with multiple rows in a data sheet. Currently, I record metrics every day in a similar function with a set of rows showing metric data based on intervals of time. These rows are broken up by date.
I would like to be able to add to a dashboard the current metrics without someone needing to dig through the tables I am recording in. This would require the metric to stay up there until the next interval changed.
I will use =SPLIT(NOW) for the date and time but for now I would like to at least get this to work with static interval and date. I tried using Index Match using AND(), & etc and I cannot get it to work. I also tried to use an array but it errors every time.
Google Sheets Index Match Multi Criteria
If the time intervals for each day will be exactly the same and the data structure will never change with 3 identical lines per day (as per your screenshot) than I think you are overcomplicating things a little:
B2:
=index($A$7:$E$15,MATCH($A$1,$A$7:$A$15,0)+1,MATCH(B$1,$A$7:$E$7,0))
B3:
=index($A$7:$E$15,MATCH($A$1,$A$7:$A$15,0)+2,MATCH(B$1,$A$7:$E$7,0))
B4:
=index($A$7:$E$15,MATCH($A$1,$A$7:$A$15,0)+2,MATCH(B$1,$A$7:$E$7,0))
This should be simple so I think I am missing it. I have a simple line chart that shows Users per day over 28 days (X axis is date, Y axis is number of users). I am using hard-coded 28 days here just to get it to work.
I want to add a scorecard for average daily users over the 28 day time frame. I tried to use a calculated field AVG(Users) but this shows an error for re-aggregating an aggregated value. Then I tried Users/28, but the result oddly is the value of Users for today. The division seems to be completely ignored.
What is the best way to show average number of daily users over a time frame? Average daily users over 10 days, 20 day, etc.
Try to create a new metric that counts the dates eg
Count of Date = COUNT(Date) or
Count of Date = COUNT_DISTINCT(Date) in case you have duplicated dates
Then create another metric for average users
Users AVG = (Users / Count of Date)
The average depends on the timeframe you have selected. If you are selecting the last 28 days the average is for those 28 days (dates), if you filter 20 days the average is for those 20 days etc.
Hope that helps.
I have been able to do this in an extremely crude and ugly manner using Google Sheets as a means to do the calculation and serve as a data source for Data studio.
This may be useful for other people trying to do the same thing. This assumes you know how to work with GA data in Sheets and are starting with a Report Configuration. There must be a better way.
Example for Average Number of Daily Users over the last 7 days:
Edit the Report Configuration fields:
Report Name: create one report per day, in this case 7 reports. Name them (for example) Users-1 through Users-7. These are your Row 2 values. You'll have 7 columns, with the first report name in column B.
Start Date and End Date: use TODAY()-X where X is the number of days previous to define the start and end dates for each report. Each report will contain the user count for one day. Report Users-1 will use TODAY()-1 for start and end, etc.
Metrics: enter the metrics e.g. ga:users and ga:new users
Create the reports
Use 'Run reports' to have the result sheets created and populated.
Create a sheet for an interim data set you will use as the basis for the average calculation. The first column is date, the remaining columns are for the metrics, in this case Users and New Users.
Populate the interim data set with the dates and values. You will reference the Report Configuration to get the dates, and you will pull the metrics from each of the individual reports. At this stage you have a sheet with date in first columns and values in subsequent columns with a row for each day's values. Be sure to use a header.
Finally, create a sheet that averages the values in the interim data set. This sheet will have a column for each metric, with one value per column. The one value is calculated from the series in the interim data set, for example =AVG(interim_sheet_reference:range) or any other calculation you'd like to do.
At last, you can use Data Studio to connect to this data source and use the values. For counts of users such as this example, you would use Sum as the aggregation field type when you are creating the data source.
It's super ugly but it works.
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.