FILTER() will often return a 0 for blank rows, even when a return string is specified. Using filter() I am often getting a 0 return value for empty cells. Assume these 6 rows of data in column A: abc xyz abc xyz abc If I use FILTER(A10:A15, A10:A15 <> "xyz", "") I get back the following (sometimes): abc abc 0 abc This seems to be somewhat ...
Setting the value of the filter query-string parameter to a string using those delimiters creates a list of name/value pairs which can be parsed easily on the server-side and utilized to enhance database queries as needed.
I find the list comprehension much clearer than filter + lambda, but use whichever you find easier. There are two things that may slow down your use of filter. The first is the function call overhead: as soon as you use a Python function (whether created by def or lambda) it is likely that filter will be slower than the list comprehension.
You create your filter over A:G by condition of K:K, like you had and you filter the result for the columns in your filtered range being equal to the given columns.
The -Filter parameter can do more than just match on everything, which is effectively what -Filter * does. The -Filter string is very much like Powershell syntax (not quite, but most of the way there). You can use most of the same logical operators that Powershell supports, and they work much in the same way that Powershell operators do.
Filter dataframe rows if value in column is in a set list of values [duplicate] Asked 13 years, 3 months ago Modified 4 years, 11 months ago Viewed 579k times
filter is designed to work robustly with the rest of dplyr and the tidyverse, both interactively and programmatically, and has a separate standard-eval version filter_ for when necessary. Also, it treats commas as &.
tablix.filter.expression.datatype = text tablix.filter.operator = IN tablix.filter.value = =SPLIT (JOIN (Parameters!id.Value,","),",") Using this method, I was able to call the SP once, use it in a param to get available values, run the report, and the tablix table read the selected data from step #5 above and displayed the correct number of rows.
Limitations of filter definitions: As implied by the above, filter bodies are implicit process blocks, and therefore do not also support begin, end, and clean blocks, the way that function s do Because filter s operate on pipeline input only, you cannot pass the input they expect as arguments.
