I have built a line chart using two filter conditions and want to include dynamic average line to the visual. Like for example I need to show the average line based on two parameters, first is date i.e. 21st Jan - 25 Jan and the site locations selected, it will only consider average between 21st to 25th Jan and not till 4th of Feb.
The site location will also be selected to count the call volume.
I am struggling to find a way around as I I thought of using SelectedValue or switch method.
Any help will be much appreciated.
Related
I have a chart in excel I wish to replicate in PBI.
My Excel chart is a bar chart dated axis with 2 series, running up march, but with data only up until now.
Each bar series has a trendline, which forecasts a trend up to the end of the financial year.
In power BI I have tried to replicate, but I cannot seem to add 'forecast' from the analytics tab unless my chart is a line graph.
So I now have 2 line series in a chart like so:
I have added trendline to both but there is no option to add the forecast line unless I only have 1 data series.
As I've removed a series I can now toggle on the forecast line in the analytics tab.
So I now have 1 line series in my line graph like so:
I actually need to have the data and the corresponding forecast for both data series, so I would have series 1 & 2 plotted like above, on the same graph together.
Is there a way to do this on the analytics tab??
If not, how should I go about it? I was thinking I could use DAX to forecast until March 2023 instead and then drag the line into the line graph and format it to dashed?
Thanks
Here is some sample data step by step for what i'm looking for (very simple thing to do in excel!):
This is the same data, pivoted with the 2 series mapped out on a line graph, and trendline added for each:
I just want to be able to show a trendline extending and forecasting forward, past the months I already have like I have done in Excel.
Yeah i think here your best solution would be to use the "what if" parameter in Dax to get the result you need
For a forecasting line to be performed on a line chart, Below requirements should be met. Otherwise You can't see this option on the analytics tab:
You need to change your datasets, and datatypes accordingly.
The last one is especially valid for you, because there is not a one-day period between your data values, in fact monthly organized.
Been struggling with a problem and can't seem to get past it.
Trying to express the sample table below as Multi Info Cards.
Year
Description
Score
2018
Work Description One
25
2019
Work Description Two
21
2021
Work Description One
12
2019
Work Description Three
19
The cards need to display the description column based on the scores column. Currently row one and row three are combined due to having the same description, showing a sum value of 37.
The easiest way to differentiate would be based on the year but I am having trouble creating a measure/filter to achieve that.
My backend table has the data at a week level. It contain the current ISO year and current ISO week, as well as, the previous year's ISO year and week number that the current year's data should be compared with.
For each signup_iso_year-signup_iso_week combination, there exists only one iso_prev_year-iso_prev_yearweek combination.
The iso_prev_year, iso_prev_yearweek columns account for the offset that might occur due to certain years having 53 weeks instead of 52.
data table
(I can't embed images, so I have added a table here as well, although it has much less information than the image in 'data table').
Number_of_signups
signup_iso_year
signup_iso_week
iso_prev_year
iso_prev_yearweek
Country
grade_level
5
2020
18
2019
18
IN
middle school
7
2020
18
2019
18
US
high school
6
2021
17
2018
18
IN
middle school
8
2021
17
2018
18
US
high school
I want to calculate to Year-Over_Year Change in number_of_signups using the signup_iso_year, signup_iso_week, iso_prev_year, iso_prev_yearweek columns.
I have already tried to create a calculated column that contains the sum of number_of_signups from previous year, but since every combination of country, grade_level, subject, email_type might not exist in previous or current year, some of the values are getting lost and hence giving incorrect results.
The answer I am looking for, is a Power BI measure that can give me the YOY change based on signup_iso_year and signup_iso_week.
Edit: I should have mentioned this before, but I forgot. The table contains data from 2018 to current day. So, the data size is quite large. Also, I need this YoY measure for a time series visual, which means that I can't assign ISOyear/ISOweek values for previous year using simple MAX/MIN functions. It needs to pick values from the iso_prev_year, iso_prev_yearweek columns but since EARLIER function can't be used in a measure, I am not able to figure out how to do that.
Which is why I had tried to create a calculated column, and use the EARLIER function to compute previous year's number_of_signups. But because of the other columns present in the data, i.e., country, grade_level, subject, email_type, there were discrepancies occurring in the actual number_of_signups and the calculated previous_year_number_of_signups. These discrepancies were due to the fact that not every combination of these columns exists for each week, so we might miss out on some data when calculating previous_year_number_of_signups.
Edit 2: Was asked to include examples of what the expected result would look like, so adding some pictures.
YoY at overall level, country level, grade level
YOY at country+grade level
If I understand your requirement correct, you need a Measure like below. Remember, this may not the exact one you need, but this will definitely help you to reach your required output.
prev_signup =
var iso_prev_year = MIN(your_table_name[iso_prev_year])
var iso_prev_year_week = MIN(your_table_name[iso_prev_yearweek])
RETURN
CALCULATE(
SUM(your_table_name[Number_of_signups]),
FILTER(
ALL(your_table_name),
your_table_name[signup_iso_year] = iso_prev_year
&& your_table_name[signup_iso_week] = iso_prev_year_week
)
) + 0
You can also do some transformation in Power Query Editor and join the same table using your Key columns. That case, you can bring previous year's value in the same row. Rest is just compare 2 columns from your table to calculate YOY
Need help in Data Analytics Calculations.
Currently, I am getting historical data for consumption as follows:
on above data, I am adding custom columns for calculating exact consumption(gallons) in no. of days. like:
Now, I have to plot month wise bar chart for consumption of respective Meter ID in 2016 year. But problem here is, I will have to calculate Every months consumption by dividing it in days in each respective month of 2016, and then only I will able to plot them monthly like:
y axis = consumption in every month
x axis = Jan Feb March Apr May Jun Jul Aug Sep Oct Nov Dec
so, in jan month, consumption should be = 10 + 100 + ((115/38) * 7) gallons
Notes: here, in ((115/38) * 7) : we are calculating avg consumption of single day 7 days in Jan and whole march and then getting last 7 day consumption of Jan so that we can add it in calculation of total consumption of Jan month
but how to add measure/custom column/new table for these calcualtions?
Thanks
What you need to do is relatively complicated, but the summary of my solution is:
Calculate the per-day consumption
Calculate the start and end date of each reading (e.g. the previous reading date plus one day, and the reading date)
Expand your data to have 1 row per day rather than 1-row per reading
You want to do these steps before you load the data into your data model (i.e. in your source system, or as the data is loaded using the Query Editor/Power Query).
Below, I assume you're using the Query Editor/Power Query. However, if you can use your source system, it's often the better choice (since the source system may be a database that is vastly faster than your desktop).
Note that your No. of Days calculation doesn't make sense to me. There are more than 38 days between 24 Jan 2016 and 31 Mar 2016. There are also more than 13 days between 10 Jan and 24 Jan. For this reason, it was difficult to tell whether you wanted a new reading to count on the day the previous reading was taken, or on the next full day. I assume the former. Also note, I've proceeded on the basis that your No. of Days calculation is correct
Calculate the Per Day Consumption
This is the easiest step, given that you have already calculated the Consumption and the No. of Days. Just divide one by the other. In the Query Editor, you can click in the Consumption (gallons) column and select Add Column > Standard > Divide. Under Value, choose Use values in a column and then select the No. of Days column.
Calculate the Start & End Date of Each Reading
The date of the reading is the end date, so you can rename Date to be End Date (since a reading is applied retroactively).
For the start date, in the Query Editor, you will need to add an index column (Add Column > Index Column). You will want to make sure your data is sorted by Meter ID and Date Ascending before doing this. Call the column Index.
Next, Add Column > Custom Column and pull the reading date from the prior row. Call the new column Previous End Date for now.
// A try is necessary because we can't get the previous row if there is no previous row (we'll get an error, which we can handle in the 'otherwise' block)
try
if
// See if the previous row is for the same Meter ID
[Meter ID] = #"Reordered Columns"{[Index] - 1}[Meter ID]
then
// If it is, grab the Reading Date from the previous row
#"Reordered Columns"{[Index]-1}[End Date]
else
// If this is the first reading for a meter, calculate the Start Date by subtracting the No. of Days from the End Date
Date.AddDays([End Date], -[No. of Days])
otherwise
// If this is the first row in the table, also calculate the Start Date by subtracting the No. of Days from the End Date
Date.AddDays([End Date], -[No. of Days])
Next, you'll want to add 1 to the Start Date, as we want the reading to apply to the day after the previous reading, not on the day of the previous reading.
Note, if you want the reading date to count in the prior period, subtract 1 from the End Date rather than add 1 to the start date (previous end date).
Expand your data to have 1 row per day
At this point, you should have a Meter ID, Start Date, End Date, and per day consumption column that reflects what you expect (i.e. the per day consumption is correct for the date range).
The final step is to duplicate each row for each date in the date range. There are several solutions to this outlined in this thread (https://community.powerbi.com/t5/Desktop/Convert-date-ranges-into-list-of-dates/td-p/129418), but personally, I recommend the technique (and video) posted by MarcelBeug (https://youtu.be/QSXzhb-EwHM).
You should end up with something more like this (after some removing & renaming of columns):
Finally
Now that you have one row per meter & date, with a per day consumption already calculated, you can build a visual. For example, you could do a column chart with Date on the Axis, and Consumption per Day as the value. By default, Power BI will recognize that Date is a date, and will roll it up by Year-Quarter-Month-Day. Press the little 'x' by Year and Quarter, and you'll have a chart that sums up the per day consumption by month. You can also drill down to individual date.
Further Reading
Reading a value from a previous row in Power Query
If Statements in Power Query
The AddDays function in Power Query
Adding Comments in Power Query
Catching Errors in Power Query
Converting a date range into a list of dates (Marcel Beug's solution)
A similar problem I previously answered
I'm trying to get a stepped line chart with Google Chart API. I've searched the docs and haven't found anything.
Here's an example I saw with Flot:
http://www.flotcharts.org/flot/examples/threshold/index.html
More info:
I'm trying to plot account balances over time. So, if there's a balance of $1,000 on Jan 1 and a balance of $2,000 on Feb 1, the google line chart displays a sloped line between Jan and Feb, which does not reflect the actual account balance accurately. I'd rather not plot more values (i.e. by adding the balance of $1,000 on Jan 31) but may have to if that's the only way...
In your example, if you plot the $1,000 on Feb 1 (ie the before and after values on the same date) you get a nice step. It's a work-around and there must be better solutions, but it's easy to implement and does give you what you're after visually.
Look into the following article:
https://developers.google.com/chart/interactive/docs/gallery/steppedareachart?hl=ru
and playground:
https://code.google.com/apis/ajax/playground/?type=visualization#stepped_area_chart