I'm trying to build a weekly cohort analysis depicted by line charts in Tableau. The problem is that all weeks line should start from 100%.
Below is the process I took :
dropping order date to columns and selecting week number
COUNTD (order id) and in rows
creating a calculated field : first purchase date{ FIXED [User Id]:MIN([Order Date])} and then
Dropping first purchase date to color field
I'm getting weeks depicted as lines (different colors) but can't figure out a way to make all lines starting from 100% point.
Here is the screenshot of what it should look like https://prnt.sc/1uugad5
Link to the dummy data where order_id is unique Dummy Data link . Any help is appreciated
Thanks
To achieve the viz, I used COUNTD([User ID]) instead of order ID.
The x axis represent the difference of weeks between the order date and the cohort date.
Finally, the percent can be found using percent of total quick table calculation and using table across.
Related
The dashboard in the linked workbook shows a table with sales split by year on the top. Below, there's a table with the rolling average of the last 4 weeks, including the current. It's set to show NULL if there are not enough data points. I'd like for it to compute the first January 2018 value based on the current week and 3 full weeks from the end of 2017. Carrying that concept forward, all NULLs from 2018 onward will be eliminated. The NULLs for the first 5 weeks of 2017 will be the only NULL values. The average should always be computed on a full 4 weeks (28 days) even when week 53 doesn't contain 7 days.
How can I write a calculation to achieve what's described above?
I've tried putting the WINDOW_AVG function inside a LOD, but that's not allowed. Furthermore, I've also tried using FIXED and even FIXED inside WINDOW_AVG.
Here's one of my attempts:
{FIXED [Week_int]:
WINDOW_AVG(SUM([Sales]), -4, 0)
}
It returns this error: "Error: Level of detail expressions cannot contain table calculations or the ATTR function"
Here's the data structure. It includes one value of Sales per day.
Basically I created a dummy data in Excel by creating dates (from 1-1-2017 to 2-2-2021) and filling some random values (unif dist *5000) against these.
I added Week[date] to columns and year[date] to rows as in your screenshot. I added sum(value) on the text marks card.
Thereafter, I added table calculation --> Moving average --> edited it for previous 4 values , next 0 values, (check current value if you want to include current record), then check Null if there are not enough values. (your requirement). --> click compute using -Specific Dimensions change the order of fields below - drag Year above than week (table across then down will also create the same view)
You should be able to get a view as desired.
Regarding your query on number of days in the week, Tableau caters it automatically if you have chosen it datepart.
Edit I verified this in Excel, the method is correctly working.
See, the average of first 28 values in Excel
and the view built in tableau:
Here's the corrected dashboard hosted on Tableau Public.
How do I populate the number of purchases and sales per day in tableau?
Here is my Sample Data:
In my first attempt, sales numbers are not counted to the exact date.
In my second attempt, I tried to tabulate by dropping sales date into the rows. However, it returned two figures - purchases and sales.
I have also tried Calculated Field but Tableau is unable to do a "for loop" like python.
First attempt:
After dropping Sales Date into the Rows. This is what I get:
Is there any way to populate it like this? Please help, I am still new to tableau. Special thanks to Fabio Fantoni for the first solution!
Desired Format:
I have another sample data (refer to sample data 2) which I would like to populate in the desired format (refer to desired format 2). In Sample Data 2, the purchase date "15/12/2020" is not reflected in sold dates.
My apologies but I may require some guidance as I am still new to tableau. Thank you in advance.
Sample Data 2:
Desired Format 2:
Based on this sample:
In order to bypass your double count for two different date columns, you may want to cross join your original data with a copy of it on original.Purchase = support.Sold, like this:
Doing so, you just have to create two calculated fields:
count Purchase:
count([Purchase Date])
count Sold:
Count([Purchase Date (Foglio11)])
The only thing you have to pay attention to is that in the second calculus you have to count Purchase date due to your "inverted" cross join.
You should get something like this:
I have a data set which has incidents resolved w.r.t date. I would like to look at the trends of number of incidents resolved over the past 45 days only on a Clustered column chart.
I couldn't see entries for specific dates (because the number of incidents resolved was zero on that day). How do I include those dates as well showing the number to be zero?
I tried the following:
1) Enabling "Show items with no data" - While this working fine, it is removing the last 45 days filter and is showing me unnecessary trends. The last 45 days filter is set on a page level and report level filter as well.
2) Creating a new measure to replace null values with 0 when the count of incidents resolved on a particular day is 0 - It again removed last 45 days filter.
Someone please let me know what I can do to get the required trends over last 45 days.
Thanks
This can be late reply, but I hope it may be useful for future users. As I suggested in a comment, you can try using measure for achieving this.
I have designed the following table with sample data.
INCIDENT_RECORD Table:
Created Measure:
Total Incident = IF(SUM(INCIDENT_RECORD[Resolved Incident])=BLANK(),0,SUM(INCIDENT_RECORD[Resolved Incident]))
Now I have designed Clustered Column Chart with & without Measure to show difference for you.
Clustered Column Chart with/without Measure:
First graph is showing label as 0 (Zero) which doesn't have any value
for that date.
Second graph is not showing data for Jan-03 in your case.
Feel free to ask your doubts/clarifications in the comment section.
First, make sure the column on your x-axis is a date data type. Then go to the Format tab for the visual and under the X-Axis options, set the Type to Continuous (rather than Categorical).
I have date-wise data of a month in Tableau and I want to know total sales of the month. Can anyone show how to do it?
Here is the snapshot of the issue:
First of all, I would advise you to go to the "Data Source" Panel on the bottom left and change the data type of the dimension "Date" to date instead of string. If this is not possible, please speak with your datasource admin. It might be a problem, that the dates are in different formats (like "1.07.06" and "1.11.2016").
After that you can simply choose the discrete MONTH(Date) dimension by rightklicking (blue pills). If you display data ranging over different years it is advised to keep the "YEAR(Date)" blue pill.
In the sample data it looks like this:
Steps to get total sales month wise
Drag your date into column shelf and change by Right click on date and change into month.
Drag sales into row shelf and Right click on measure and go into sum.so you will get total sales per month.
I want to create a monthly report, calculating the % from the previous 2 month average from the previous 12 months average. Basically I want to see which shops have dropped in sales in the previous 2 months, and hopefully only show the shops that have decreased 20% in sales.
So i believe the columns need to be like this
Shop|Products|Avg of 12 months|Avg of 2 months| %
Since i have many entries for the sales, i also need to sum the previous 12 months and then average it... as well as sum the previous 2 months and average it
I have thought of some ways to do it, but it didnt seem to work and seems all too complicated and complex.
Im hoping if there is a simpler solution to this? Do i need to use pivot table?
I'm using PostGres 9.1 on Visual Studio 10
Thanks a bunch
When something seems too complicated to resolve with a single query, I create and populate a DataTable runtime and pass it to ReportViewer.
In this case you can:
create a DataTable with Shop and Product as a PK (if you want print the report for a period of months you can also add Month as PK). The other 2 columns will be Avg12Months and Avg2Months
insert a record for each combination of Shop/Product (and eventually Month)
for each record Shop/Product calculate and save the results for Avg12Months and Avg2Months
pass your DataTable to ReportViewer
use a single Tablix to display the results (sort, grouping and other operations can be done in the Tablix)
Some passages can be combined in order to speed up the process.