Is there a way to extend the findfirst(==(val1), df.col1) for more than one value over more than column in a dataframe. Something like findfirst(==([ val1, val2]) , [df.col1, df.col2]) I tried findfirst(row -> (row[1] == val1 && row[2] == val2), eachrow(select(df, [:col1, :col2]))) but that see…

findfirst(df.col1 .== val1 .&& df.col2 .== val2)

awesome thanks! Just curious why is subsetting with findall on val1 first meaningfully faster? @benchmark df1[findfirst(df1.date .==(Date(2024,2,23)) .&& df1.time .==(Time(10,00,00))),:] BenchmarkTools.Trial: 186 samples with 1 evaluation. Range (min … max): 26.772 ms … 27.584 ms ┊ GC (min … m…

findfirst(==((v1,v2)), tuple.(df.c1,df.c2))

[image] phantom: Just curious why is subsetting with findall on val1 first meaningfully faster? What expression are you referring to? Can you post a data set to test on? I’ve tried different ways to check times and allocations and something like the following seems the most efficient (altho…

I think the main speed difference comes from the fact that the data was read from an .arrow file and therefore not stored in memory. Also I’m probably not handling interpolation correctly? Having the dataset in chronological order also makes a difference but not as much. Accounting for size and d…

ffr seems much more efficient or am I wrong? julia> function ffr(c1,c2,f,l) i=1 for (fr,lr) in zip(c1,c2) fr == f && lr == l && return i i+=1 end end ffr (generic function with 1 method) julia> @btime df2[ffr(df2.dates,df2.times…

yeah you’re right in terms of efficiency. I was just looking at execution times. These are the results I got. ffr() from RAM julia> @benchmark $ffr(df3.dates,df3.times,Date(2024,2,23),Time(10,00,00)) BenchmarkTools.Trial: 800 samples with 1 evaluation. Range (min … max): 6.179 ms … 6.603 ms …

[image] phantom: Having the data in chronological order If the data is sorted, then you should use searchsortedfirst instead of findfirst and it should make a significant difference.

awesome thanks! What would be the appropriate syntax to apply searchsortedfirst to multiple values from multiple columns in a data frame? The docs only include examples with a single array.

Are the rows sorted by df.dates and df.times jointly?

yes, they are in chronological order by both date and time.

Using findfirst with for multiple values and columns in a Dataframe?

New to Julia

lrnv March 24, 2024, 10:38am 22

Since it seems a bit related, take a look here Fastest way to fetch an index where we designed alternatives to searchsortedlast it might give you more ideas

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Using findfirst with for multiple values and columns in a Dataframe?

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