I have a dataset as follows:
DATE | AMOUNT | CATEGORY
20.12.2015 | 100.00 | Drinks
22.12.2015 | 50.00 | Food
20.12.2015 | 70.00 | Transport
07.12.2015 | 50.00 | Transport
...
There are several records with amounts spent per week and day.
I would like to have a bar chart with the categories on the left and the length of the bars indicating the weekly average, ie. what is spent on average per week during a filtered time frame
If I user the normal AVG([AMOUNT]) it calculates the daily average, rather than the weekly one.
I found this question:
Tableau - weekly average from daily data
However one of the answers is not dynamically, the other lists averages for consecutive weeks, rather than per category and I can't think of a way to apply the same technique for mmy problem.
Add a new dimension, which is for the weeks
You can then create a variable which calculates the average amount for a specific week as follows:
{FIXED [Date (Week numbers)], [Category]: avg([Amount]) }
Then when you want to average you can average the above formula
AVG({FIXED [Date (Week numbers)], [Category]: avg([Amount]) })
First make sure the data type for the field named DATE is type date instead of string. If not, change the data type from the right mouse menu or worst case use the date parse function in a calculated field.
Second, after you place the DATE field onto a shelf, set the date level of granularity to Week. Again ], use the right mouse context menu. Choose from the second batch of choices to truncate dates to the week level. The first batch of options on that menu are date parts, not dates. You may want to then change the field to discrete depending on your intended view.
Based on Mark Andersen's solution I found the following:
create a calculated field WeekNumber:
DATETRUNC('week', [Date])
create a calculated field WeekTotal:
{FIXED [WeekNumber], [Main Category]: SUM([Amount Person]) }
create a calculated field WeekDiff:
DATEDIFF('week',#2015-08-01#,TODAY())
create a calculated field WeekAvg:
[WeekTotal] / [WeekDiff]
Use WeekAvg as the meassure for the bars and it's done.
A few remarks for that:
Mark's solution went int he right direction. I had to replace avg([Amount]) with sum([Amount]) since I want to have the total per week and average it afterwards.
However it didn't exactly calculate what I wanted since Tableau only calculates averages based on the weeks that have a spending.
If I have
40$ in week 1
20$ in week 2
30$ in week 4
then it calculates (40+20+30)/3 = 30 while I would like to have (40+20+30)/4 = 20.25
In my use case my solution works because I have a fixed time frame until TODAY(), however it would be conviniant if that would be calculated automatically if I use a filter between two arbitrary dates.
Related
I’m trying to figure out how to create rolling 7 day periods. I have horizontal bar charts that are currently grouped by week, but I actually want them to be grouped by 7 day periods instead.
I used the Superstore data as an example. The top row in this image should be the last 7 days, with the latest date being in the top right, and so forth. Is this possible?
You can create a field to use as a dimension for this assuming you choose some anchor date to specify the beginning of a 7-day period. For this example, I’ll choose a literal date of July 4, 1776 but you could use the Today() function or the min or max transaction date in your data or whatever you like.
Then the DIV() and DATEDIFF() functions are all you need to calculate the number of 7 day periods Between the anchor date and the period containing [Order Date].
DIV(DATEDIFF('day', #7/4/1776#, [Order Date]), 7)
You’ll typically want to treat this field as a discrete dimension.
In the example below, I called the field [Period] and also displayed the earliest and latest dates found in the data for each Period.
In a more production oriented example, you may want to hide the header for the Period field and instead calculate the start/end dates for periods rather than draw them from the data, so that they show correctly if there were period boundaries without any transactions.
The formula to compute the [Period Start] is DATE(DATEADD('day', [Period] * 7, #7/4/1776#)) and to compute [Period End] is DATE(DATEADD('day', [Period] * 7 + 6, #7/4/1776#)) If you are going to use the anchor date in many formulas, it would be convenient to define it in one place with a parameter or calculated field.
I have Tableau 9.1 and have the costs per transaction in a column over the course of 3 years. I also have the dates and locations for all the transactions.
How do i make a calculated field for total cost at a location for a given quarter assigned to each observation?
Generally that depends on how you want to display these values.
An easy way would be via a LOD calculation:
{fixed DATETRUNC('quarter',[Date]), [Location]: SUM([Cost])}
This calculates the SUM([Cost]) for each quarter of [Date] and each [Location]
I have a few years of data by day that looks like this:
Date Count
1/1/2015 1000
1/2/2015 1010
1/3/2015 1040
I would like to create a calculation that allows me to switch between Day, Month and Year using Tableau's date formats without having to calculate the average for each individual format. For instance, the monthly average for Jan 2015 would be the total of Count for all 31 days in January 2015 divided by 31.
Since you have no missing data (days) and no duplicate data, the solution is extremely easy.
Place the Count field on any shelf (except the filter shelf). For example, place it on the Rows shelf. Click on the Count field on the Rows shelf and change the aggregation to AVG(). You should see the AVG(Count) of all your data rows at this point.
Place the Date field on any shelf (except the filter shelf). For example, place it on the Columns shelf. Click on the Date field pill on the Columns shelf, and choose the level of granularity you wish from the SECOND batch of choices. (The first batch returns date parts, not dates) For example, choose Month. You'll see the Avg(Count) per month.
Place any other dimensions on shelves to either filter to specific dimension values or to show the average counts broken down by your other dimensions.
Users can drill up or down the granularity of your dates by clicking the + or - icons by the date axis, or by clicking on the Date pill. You can choose to display the dates as a continuous or discrete value.
If you don't like the +/- UI, then you can create a string valued parameter with values: year, quarter, month, day etc, and then create a calculated field using the date_trunc() function to allow, say, a dashboard user to to choose the date granularity from a different type of UI control.
I am a very basic user of tableau and I have not found an answer to my question.
I have a txt file that has historical daily data for 98% of all the stocks in the US, with their daily capitalization. Each stocks has its TICKER, Daily Market Value for every trading day of the year, and its SECTOR.
I did a simple time series that display SUM([Mktval]) (sum of all individual market values) across all stocks, on a daily daily, and where I can see that the total value as of 2016 is about 24 Trillion USD, as in the image below.
When I change the view column from DAY to YEAR, I don't see the right values, but something a lot larger. So I realized that I need to do SUM([Mktval])/252 to get the right value for a year (there are 252 trading days in a year).
If I change the view to MONTH, as in the chart below, the numbers are again wrong because 252 is not the right value to use in the division.
Is there any way that Tableau can adjust the values automatically to reflect the AVG MktVal across different time intervals?
Thanks
Replace SUM(Mktval) on the Rows shelf with the following calculated field
avg({ fixed day(Date1) : sum(Mktval) })
That solution is all in one step. It is perhaps a bit more clear to use 2 steps. First, create a calculated field called total_daily_market_value defined as
{ fixed day(Date1) : sum(Mktval) }
Then make sure that calculated field is a measure. It is an LOD calculation that you can think of as a separate table with one value for each day showing the total market value for that day.
Drag that measure to a shelf, and then change the aggregation function to AVG(), MEDIAN(), MIN(), MAX() or STDEV() as desired. Tableau will aggregate the total_daily_market_value using your chosen aggregation function for whatever values of Date1 are in your view.
My input text source always contains last 12 months worth of data. e.g: Current month is October. So My input source contains data starting from last Oct 1st to till date. But I want the aggregate statistics to be displayed on a daily basis for last 10 days of sales , 30 days of sales, 45 days of sale per product across various regions
I am trying to use window_avg fuction with something like window_avg(sum(sales), first() + datediff('day', window_min(min([date]))-1, dateadd('month',1,window_min(min([Date]))-1)) * 13,13) something like that. But I am not able to crack the exact logic.
Could you please suggest me some better way to achieve this, rather than using these kind of calculations. Also I am afraid if this goes wrong if there is data missing in the middle one or two days.
Any help is appreciated.
A very simple thing is to use a relative date filter. There's a UI for you to select they last N days.
Put the date on the columns shelf and set it to the date truncation of year-month-days. Put your measure row shelf. Put the date pill on the filter shelf too and use a relative date filter.
If you are doing simple aggregate like the sum of sales for a day it's easy and you'll not need to do anything else. You can can also fairly easily create a table calculation by right clicking on the measure and choosing one of the quick table calculations. Even when I'm doing a more sophisticated calculation, I start with a quick table calculation and then start editing.
If you are doing something like a moving average, the filter and the moving average can interact. For example, if I'm showing a 5 day trailing moving average over 30 day period, the first few days do not get averaged in the same way -- you don't have days over 30 days ago. If that's not really an issue for you, that's cool and you are done.
If it is an issue, it's going to be trickier. I'd suggest creating a second filter based on a table calc. The reason is the order of operations in Tableau. The raw data is filtered then aggregated by the database, then the table calcs are performed. If there are any filters on table calculations, then they are filtered after that. So basically, in my example, you want create a filter for 35 days on the date, then create a table calc on the date -- like using the INDEX() function. Filter the index function to show 30 days worth, then you've got a moving average that uses 35 days to compute the average, but only shows 30.