I would like to calculate values for yesterday for every date in a table.
Firstly I have simply calculated the number of orders for each date using COUNTD function.
But afterwards I encountered some problems trying to calculate values for "yesterdays".
Please refer to the image
example
For example for 12th of April I would like to obtain the value for 11th of April.
On the internet there are a lot of examples using today() or max() or table functions but they do not give the required result because a would like to filter for example 12th April but still see the value for 11 April.
Could you please help, how is it possible to do this?
I have a chart that shows the number of departures for a given 15 minute interval as seen here.
I need to compound these counts backwards for one hour. For example, the 3 departures shown at 11:00 need to also be represented at the 10:00, 10:15, 10:30, and 10:45 columns. When completed, the 10:00 would have a total of 6 departures (10:15 -> 6, 10:30 ->5, 10:45 -> 4, 11:00 -> 4).
I have done this via VBA in excell, but am now needing to replicate the chart in Tableau and have been beating my head in for about two weeks now. I'd love to hear any and all suggestions.
You can use a Cartesian join against a large enough date range of your choosing to in effect resample your data and add the additional time intervals you desire.
For example, if you have a month's worth of data (min date -> max date = 30 days), then you have (30 * 24 * 4) 2880 15 minute intervals.
Create all those intervals in a separate data sheet
Add a bogus column with value of link for all rows
Create the same bogus in your actual data source
Join the two sheets together on the link column
Create a calculated field that is something along the following:
[Interval] <= [Flight Time] AND [Interval] >= DATEADD('hour',-1,[Flight Time])
This calculated field will evaluate to TRUE when the interval time is within one hour before the flight time. You can then drag this field onto your filter shelf and select TRUE value only. Effectively your [Interval] field becomes your new date field.
I would recommend adding that filter to the context and applying across the entire datasource. Before you add this filter you'll have 2880 times the about of data so be sure to do a live view first. Be careful with extracts using Cartesian joins as you could potentially be extracting more than you bargained for.
See the following links for different techniques on how to do this and re-sampling dates in general in tableau.
https://community.tableau.com/thread/151387
Depending on the size of your data (and if a live view is not necessary) it is often times easier and more efficient to do this type of pre-processing outside of tableau in SQL or something like python's pandas library.
Here is another solution provided from the Tableau Cumunity Forum. I have not tried tyvich's solution yet, but I know this one got me where I needed. Please follow the link to see the solution using moving table calculations.
https://community.tableau.com/thread/251154
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.
I'm calculating how long it takes to detect an issue in Tableau.
I have the following calculated field to work out mean time to detection:
DATEDIFF('hour',[DATE Reported], [DATE Responded])
When I use the meantimetodetect calculated field it only shows me one result and the rest 0s.
The one result shown is correct there were 3 days apart from when it was reported to the response date. The rest of the results are reported and responded in the same day so I dont know if that has anything to do with it?
Does anyone know why it is displaying like this perhaps there is a better way to calculate it?
Thanks.
I am relatively inexperienced with matlab, as I only use it occasionally. I am trying to plot a large range of values against time and I am running into some problems.
The data, which is from a text file, with about 55000 entries, gives the information in the following format:
year month day hour minute second value
The seconds column has accuracy of 6 decimal places and there are about 24hrs worth of data.
What I want to do is plot the values against time, which works fine. However as a result of my code below, the x-axis has label ticks in serial date number format, which is not very useful when looking at the figure. I want to change the labels to something more useful such intervals of hours. However I am not sure how to go about doing this.
Here is the code:
A = dlmread('data.txt',' ');
time = datenum(A(:,1),A(:,2),A(:,3),A(:,4),A(:,5),A(:,6));
scatter(time,A(:,7),1)
axis([min(time) max(time) min(A(:,7)) max(A(:,7))])
I found a solution here: matlab ticks with certain labels however, the process here is manual and with so much information I don't want to do this manually. How would I automate this process? or is there a better way to do what I am trying to achieve?
EDIT: I also found this method: http://www.mathworks.com/help/matlab/ref/datetick.html#btpnuk4-1, however, I dont want to show the actual date, I rather want to show intervals of time, ie an hour or 30 minutes.
EDIT 2: I have found a somewhat satisfactory solution. It could still be improved upon, so I don't know if I should submit this as an answer to my own question or not, but here it is:
A = dlmread('data.txt',' ');
time = datenum(A(:,1),A(:,2),A(:,3),A(:,4),A(:,5),A(:,6));
temp= time(1);
timediff = time - temp;
scatter(timediff,A(:,7),1)
axis([min(timediff) max(timediff) min(A(:,7)) max(A(:,7))])
datetick('x', 'HH')
This takes the original time vector in serialized time format and subtracts the first time from all the subsequent times to get the difference. The it uses the datetick function to to convert that to hours. It isn't ideal because instead of 24 hours it goes back to 00, but its the best I have tried thus far.
With reference to the other article, you will have to follow the same method but in order to automate the process you'll need to form the vectors of xtick and xticklabels as you read in the data and after you've plotted the data change the xticks and xticklabels.
Its not difficult what you're trying to do, but I will need more details of how you want to organize the ticks to be able to exactly say the steps that you'd have to follow
Matlab serial time is simply days since January 1, 0000, so your timediff variable is really elapsed days (and fractions thereof) since the start of your experiment. If you want your x ticks to be elapsed hours you could multiply timediff by 24.
scatter(timediff * 24, values)
This avoids the weirdness that can arise when using datetick as well.