I have a table of vehicles at service locations showing columns such as DAY, LICENSE, BOROUGH etc. I'd like to add a cross table showing the number of vehicles that have been serviced for 3 weeks or more. I'm not sure what custom expression to use.
Sample data:
Sample data
I hope your sample data isn't containing a bunch of legitmate license plates. not the most compromising data but I would recommend blacking out or replacing them with test data if it isn't already.
anyway. you're looking for the DateDiff() function. for example:
If(DateDiff('day', Date(DateTimeNow()), [Date]) >= 21, "21 days or more", "less than 21 days")
Related
I'm new of MDX and I'm trying to calculate a new measure based on two different date dimensions.
I have the Creation Date Dimension (with Year, Trimester, Month, Day) and Resolution Date (with Year, Trimester, Month, Day).As measure I have the number of tickets and I want to calculate two new measures in order to know how many tickets that were resolved this month were actually created last month and how many tickets were resolved in the same month as they were created.
I found this interesting post, but I cannot understand how to use properties..
https://bennyaustin.com/2012/06/05/ssas-mdx-calculated-measures-that-require-date-comparison/
Any ideas or suggests?
Thanks for your help.
This question cannot be answered as asked without knowing the exact definition of your time dimensions.
An approach which might be worth considering if your MDX knowledge is little, but you have some SQL knowledge and if your requirements can be fixed to just the month level as you described, could be the following, which does the main calculations already when loading the cube, and not at query time in MDX:
Add a column 'months_from_creation_to_resolution' to your fact table, possibly just add this as a column in the view you may already use on the fact table. This column would be 0 if the ticket was resolved in the same month where it was created, 1 if it was resolved in the month after creation, 2 if it was resolved e. g. in May and created in March, etc. You do this calculation using SQL date functions. You would then create a new dimension in your cube from this table, which would have the new column as the only attribute. SSAS has no problem using a table as base for both a measure group and a dimension.
Then, in MDX, the number of tickets resolved in the month they were created would just be
([Measures].[TicketCount], [Fact].[months from creation to resolution].[0])
and those resolved in the month after creation would be
([Measures].[TicketCount], [Fact].[months from creation to resolution].[1])
As a side effect, the query run time would be faster, as the main logic is pre-calculated when loading the cube.
I am creating a Tableau visualization for floor stock in our plant. We have a column for incoming date, quantity, and outgoing date. I am trying to create a visualization that sums the quantity but only while between the 2 columns.
So for example, if we have 9 parts in stock that arrived on 9/1 and is scheduled to ship out on 9/14, I would like this visualization to include these 9 parts in the sum only while it is in our stock between those 2 dates. Here is an example of some of the data I am working with.
4/20/2018 006 5/30/2018
4/20/2018 017 5/30/2018
4/20/2018 008 5/30/2018
6/29/2018 161 9/7/2018
Create a new calculation:
if [ArrivalDate]>="2018-09-01" and [ArrivalDate]<"2018-09-15"
and [Shipdate]<'2018-09-15"
then [MEASUREofStock] else 0 end
Here is a solution using UNIONs written before Tableau added support for Unions (so it required custom SQL)
Volume of an Incident Queue at a Point in Time
For several years now, Tableau has supported Union directly, so now it is possible to get the same effect without writing custom SQL, but the concept is the same.
The main thing to understand is that you need a data row per event (per arrival or per departure) and a single date column, not two. That will let you calculate the net change in quantity per day, and you can then use a running total if you want to see the absolute quantity at the close of each day
There is no simple way to display the total quantity between the two dates without changing the input table structure. If you want to show all dates and the "eligible" quantity in each day, you should
Create a calendar table that has all dates start from 1990-01-01 to 2029-12-31. (You can limit the dates to be displayed in dashboard later by applying date filter, but here you want to be safe and include all dates that may exist in your stock table) Here is how to create the date table quickly.
Left join the date table to stock table and calculate the eligible quantity in each day.
SELECT
a.date,
SUM(CASE WHEN b.quantity IS NULL THEN 0 ELSE b.quantity END) AS quantity
FROM date a
LEFT JOIN
stock b on a.date BETWEEN b.Incoming_Date AND b.Outgoing_Date
GROUP BY a.date
Import the output table to Tableau, and simply add dates and quantity to the chart.
I'm pretty new in Tableau. I have looked at the forum already and the answered suggested. But I'm not quite sure it match my question.
I have a bunch of records. This is about registration for a sport lesson depending on time. All of them have a start date and and some of them a finish date. The other never finish (They continue until date T with T = now).
My goal is to compare only the first 6 months of all my records, I think there are 50 of them, like the evolution during this period of time. So, for some the start date would be in January 2009, for some other, it would be in May 2016, etc.
As field provided, I have the start date and the number of person that have subscribed those lesson through time.
So, do you if there is any to achieve this goal? Is there enough detail for you to understand what I am saying ?
Thx to you guys !!
EDIT
You can find enclosed a screenshot of the result that I already have.
number of registration for all lesson through time
I'm not sure to be clear, what I try to do is to compare the first 6 months only of each courses. So the evolution of the first 6 months of this course compare to the evolution of the first 6 months of this other course and so on :)
If I understand your question correctly you are wanting to show only the first six months of your data but you want this by each category.
I am assumuming that by definition this means 6 months from the first record in your data for each category.
In order to achieve this I would create a true/false flag using a level of detail expression. As you are new to tableau I would suggest you do some reading on this but basically you can force a calculation to be at a certain level of the data rather than at the row level. You use this to find the minimum date in the table and then use a date diff to return true if the actual date field is within 6 months of this.
Create a calculated field as follows:
[date] <= DATEADD('month', 6, { FIXED [category] :min([date])})
Then drag this onto your filters pane and select "TRUE". This should give you only the first six months of records for each category.
Let me know if you need anything else.
I have an SAS dataset in a long format. The intervention program started from 2014 Spring semester, and it has been on until 2017 Spring semester. So there has been 7 semesters (2014 Spring and Fall, 2015 Spring and Fall, 2016 Spring and Fall, 2017 Spring).
Not everyone participated in all 7 semesters though. Some participated once and never came back, some participated more than twice but not necessarily two semesters in a low.
So each individual has a different number of cases. For someone who participated twice, for example, has 2 rows, some with 5 participations have 5 rows.
I want everyone has 7 rows in the dataset for some reason.
What could be the best way of programming to do this in SAS?
I would really appreciate any suggestions!
PROC EXPAND is probably the most direct way to do this, although it has the limitation that it won't extrapolate beyond the observed start/end of the range, and it expects regular intervals (or a lot more work to define intervals).
proc expand data=your_data out=expanded_data from=semiyear extrapolate method=none;
by student;
id semester_date;
run;
That relies on semester_date being a date variable corresponding generally to the start of each half-year.
Perhaps more easily in this case, you could use the printmiss option in proc tabulate, which would generate a table pretty easily.
ods output table=out_table;
proc tabulate data=your_data;
class student semester;
tables student,semester/printmiss misstext=' ';
run;
ods output close;
Then merge that back to the main dataset, this will have a row for every student*semester combination.
I'm an historian of medieval history and I'm trying to code networks between kings, dukes, popes etc. over a period of time of about 50 years (from 1220 to 1270) in medieval Germany. As I'm not a specialist for graph-databases I'm looking for a possibility to handle dates and date-ranges.
Are there any possibilities to handle over a date-range to an edge so that the edges, which represents a relationship, disappears after e.g. 3 years?
Are there any possibility to ask for relationships who have their date-tag in a date-range?
The common way to deal with dates in Neo4j is storing them either as a string representation or as millis since epoch (aka msec passed since Jan 01 1970).
The first approach makes the graph more easily readable the latter allows you to do math e.g. calculate deltas.
In your case I'd store two properties called validFrom and validTo on the relationships. You queries need to make sure you're looking for the correct time interval.
E.g. to find the king(s) in charge of France from Jan 01 1220 to Dec 31st 1221 you do:
MATCH (c:Country{name:'France'})-[r:HAS_KING]->(king)
WHERE r.validFrom >= -23667123600000 and r.validTo <=-23604051600000
RETURN king, r.validFrom, r.validTo
addendum
Since Neo4j 3.0 there's the APOC library which provides couple of functions for converting timestamps to/from human readable date strings.
You can also store the dates in their number representation in the following format: YYYYMMDD
In your case 12200101 would be Jan 1st 1220 and 12701231 would be Dec 31st 1270.
It's a useful and readable format and you can perform range searches like:
MATCH (h:HistoricEvent)
WHERE h.date >= 12200101 AND h.date < 12701231
RETURN h
It would also let you order by dates, if you need to.
As of Neo4J 3.4, the system handles duration and dates, see the official documentation. See more examples here.
An example related to the original question: Retrieve the historical events that happened in the last 30 days from now :
WITH duration({days: 30}) AS duration
MATCH (h:HistoricEvent)
WHERE date() - duration < date(h.date)
RETURN h
Another option for dates that keeps the number of nodes/properties you create fairly low is a linked list years (earliest year of interest - latest year), one of months (1-12), and one of dates in a month (1-31). Then every "event" in your graph can be connected to a year, month, and day. This way you don't have to create a new node for every new combination of a year month and day. You just have a single set of months, one of days, and one year. I scale the numbers to make manipulating them easier like so
Years are yyyy*10000
Months are mm*100
Date are dd
so if you run a query such as
match (event)-[:happened]->(t:time)
with event,sum(t.num) as date
return event.name,date
order by date
You will get a list of all events in chronological order with dates like Janurary 17th, 1904 appearing as 19040117 (yyyymmdd format)
Further, since these are linked lists where, for example,
...-(t0:time {num:19040000})-[:precedes]->(t1:time {num:19050000})-...
ordering is built into the nodes too.
This is, so far, how I have liked to do my event dating