Of table) means that each number displayed is the SUM(Sales) for See Data Aggregation in Tableau for more information.įor example, if the aggregation applied to the Sales measure is a summation, then the default percentage calculation (percent Standard aggregations include summation, average,Īnd several others. Percentages are computed on the basis of the aggregationįor each measure. The percentages are calculated with the Sales measureĪggregated as a summation, and are based on the entire table.

The figure below is an example of a text table with percentages. Other percentageĬalculations are available via the Percentage of menu By default, Tableau uses the entire table. The comparison can be based on the entire table, a row, a pane,Īnd so on. You want, and is the number to which you compare all your calculations.

The denominator depends on the type of percentage The data to which you compare all percentage calculations There are two factors that contribute to the percentageĬalculation: 1. Want to view each product’s sales as a percentage of the total sales Also there are some cases with Indicators, where a single record could include some errors and an average would hide them.Any analysis in Tableau can be expressed in terms of percentages.įor example, rather than viewing sales for every product, you might The mean across countries.Īnd why should I just not take the last year record or the first or the median or one other? Because as I said, I want to include the diachronical sence. What about unweightend average? Well that would show me a better description of what I am searching for. What would the weightend average show me? A too low price. We have a small, developed Country with every year records (total 50) and all of them are between Īnd a big, less developed Country with records (1960, 1990, 2015) between Īnd I want to show diachronically some representative average (forest area) on those 2 Countries. (Lets simplify above example with 2 Countries and not 50) Keep also in mind that values from that Indicator are pretty hard to change much. but because there had been no survey (for example some less developed countries could have last 50 years only 4 or 5 year records.). That happens though not because there was no forest. However there are some years where some Countries have no record at all (empty record instead). So we got one indicator record for 100 Countries for 50 last years. I will describe bellow the case I personally decided to go with unweighted.Īll those values represent a single Indicator (lets say forest area in KM2 per Country per year). However there can be some rare cases (in my opinion) where unweighted is the way to go. Indeed an unweighted average is pretty meaningless 99% of the time. Thanks in advance for anyone who can post their thoughts on this. I feel like there must be other situations where this kind of analysis is useful, but is there any standard method for doing this? Or average = (sum(a+b)/sum(a))*mean(q's) where q = (b-a)/(b+a)īut neither of these are quite satisfactory and certainly not standard methods, and so I can't really use them for what I'm working on. I can arrive at something closer to what I am hoping for if I use:Īverage = (10^mean(q's)) - 1 where q = log(b/a) For example:īefore (a), after (b), percentage change (q):Īrithmetic mean of percentage change = 0.25 whereas I would like it to equal 0. I want a representative figure, such that if the event causes someone to double their giving, this is as significant as if it causes someone to halve their giving. Yields answers of q = 0 to ∞ for an increase, and q = 0 to -1 for a decrease. Using the standard formula for percentage change: My issue however, is that taking a standard arithmetic mean of the percentages yields a value that is unrepresentatively high as an increase counts for more than a decrease. It is also just as significant if someone doubles their giving as if someone halves their giving etc. If someone doubles their giving, it is just as significant if it goes from 100 to 200 as from 1 to 2, hence unweighted mean. I am trying to calculate the average effect of an event on how much an individual gives, which can increase or decrease. I realise that in most situations, the unweighted mean of percentage increase is fairly meaningless, unless the initial values for all of the percentages are the same however in this situation I feel that it is the best way to go. I am trying to calculate the unweighted mean of several percentages which represent both positive and negative change. I have come across an interesting problem, which I'm sure there must be a standard solution to, but lots of Googling hasn't yielded much (which may mean I'm well off track.).

Average of percentages mean