How to add percentage column in data studio that is based on the grand total per date
(I also need this percentage column to update once I use filters)
This is what I would like my table to look like. I need to add a percentage column that calculates the percentage of the Volume Column based on the grand total of Volume for that date.
Screenshot
I tried doing this by computing the Percentage in the source sheet. However, the problem there was once I filtered the volume column using another dimension (location), the Percentage did not update so the grand total no longer became 100%. For example, filtering based on location would make the volume for Jan 18 to be row 1: 100, row 2: 50. However, the percentage is still based on the total (700) instead of the filtered total (150).
I also tried using comparison calculation. However the grand total for the Percentage also did not become 100% because the calculation is based on the grand total for Volume for all dates. For example, for Jan 18, the computation for the percentage should be 500/700. But what comparison calculation does is 500/(700+800+113).
Related
I have 2 tables from the same data source, same columns, one of them is filtered. For calculating total count COUNT_DISTINCT(another_field) metric is used. The percentages are calculated as COUNT_DISTINCT(another_field) and used the Percent of total comparison function. Title is the dimension.
Title
Total count
Percentage
title1
1,734
47.36%
Title
Total count(filtered)
Percentage(filtered)
title1
1,639
45.69%
Which are correct numbers. Now after blending these 2 tables joined by Title I get.
Title
Total count
Percentage
Total count(filtered)
Percentage(filtered)
title1
1,734
6.18%
1,639
9.97%
Now what happened to the percentages? Why did they change? And how to accomplish this joined table with the same numbers as in the separated ones.
The reason of my problem is that when I blend the data it's already aggregated so the percentages lose the sense of the base data. The correct workaround was to just create 2 charts with no aggregated dimensions or any metrics (one filtered, the other one - not), then manage the blended data to add any fields that are going to be used as a dimension, and only then aggregate the data on the blended chart.
I have imported data from a trading exchange listing sellers of a particular cryptocurrency.
From this data, I want to create dynamic pricing to display an average cost on an order based on given order size.
I will give an example of what I am looking for:
Example dataset
Within this example, we would be purchasing the cryptocurrency 'SINS'. As per the data showed on this table, if 29.06 SINS was purchased, that would fill the first order, and the total BTC paid would be 0.00459 BTC.
If an order was placed for 145 SINS, it would fill the orders up to row 12 and partially fill the order in row 13. By calculating that manually, I know that would cost 0.02293365 BTC (calculated using col D) at an average price of 0.00015816 per SIN.
What I would like to achieve is if a number is entered in a cell, it confirms the average price of an order based on the number entered and the orders imported from the trading exchange.
=INDIRECT(ADDRESS(MATCH(VLOOKUP(O2,F2:F,1),F:F,0),7,4))+(
INDIRECT(ADDRESS(MATCH(VLOOKUP(O2,F2:F,1),F:F,0)+1,4,4))*(O2-
INDIRECT(ADDRESS(MATCH(VLOOKUP(O2,F2:F,1),F:F,0),6,4)))/
INDIRECT(ADDRESS(MATCH(VLOOKUP(O2,F2:F,1),F:F,0)+1,3,4)))
spreadsheet demo
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 am pulling Facebook Fan data daily via Supermetrics into Data Studio and I was hoping someone could share a formula that I could use to calculate New Fans, as a calculated field, from Total Fans.
The formula would need Identify the last day of the month and the subtract followers from the first day of the month.
For example: If there 100 Fans at the end of September and 60 Fans at the beginning September, the formula would show 40 New Fans.
Formula Example
Assuming the net fan numbers is always increasing, first set the aggregation method for Total Fans to None in Fields screen by editing the data source. Then you can create a new calculated metric with the formula max(Total Fans)-min(Total Fans). This will work only at aggregate level (using scorecard or table total) and not at row level in tables.
I have a Matrix style report that I have created and it is currently displaying a total count of items for a series of companies throughout a 12 month period.
[Company1] [Company2] [Etc....] [Total]
[May] (Count)(Percent)
[June]
[Etc]
[Totals]-----------------------------------------------------
The last column total is a subtotal function and automatically adds column counts based on what is in the Column group which in my case gives me a total for both (Count)(Percent)
I only want to show <Count> but I don't find any method of modifying the parameters for the subtotal function.
The only way I found was to add an additional matrix to the right hand side of the main but only display total counts. Kind of hokey and I will refrain from implementing it at this time.
Any suggestions?