compare two data frames and get index from second dataframe for greater value in r programing-CodePudding

I have two data frames which is mentioned below :-

df1 = data.frame(df1_col = c(0.00002,0.00010,0.00020,0.00100,0.00200))

df2 = data.frame(df2_col1=c(0.00001702406727,0.00002002614159,0.00002018336933,0.0000977206871,0.00010785618371,0.00018966630497,0.00020173904639,0.00099759142132,0.00104912583361,0.00194016482197,0.00200732582737)

now i want to compare each row from df1 with each row of df2 and find out row number(index) of first greatest in df2, from index number i will take data from df2 for that corresponding index number.

note :- df1 is having less number of rows than df2

i tired using looping through each row for df1 and df2 and then used which function but it didn't work any other simple method is there?

my desired output will be :-

df3 = data.frame(df1_col1 = c(0.00002,0.00010,0.00020,0.00100,0.00200), df2_col2=c(0.00002002614159,0.00010785618371,0.00020173904639,0.00104912583361,0.00200732582737))

sorry for any inconvenience . this is my first question . thank you in advance !!!!

NEW DATA

df1=data.frame(df1_col1=c(0.00002, 0.00010, 0.00020, 0.00100, 0.00200, 0.00250, 0.00400, 0.00500, 0.01000, 0.02000, 0.03000))

df2=data.frame(df2_col1=0.00014940969624, 0.00015836812803, 0.00016803247695, 0.00017844541097, 0.00018966630497, 0.00020173904639, 0.00021473722873, 0.00022871767705, 0.00024376616425, 0.00025995387854, 0.00027740350512, 0.00029622853518, 0.00031659411339, 0.00033867002512, 0.00036270484799, 0.00038895378722, 0.00041774363175, 0.00044938435908, 0.00048425557455, 0.00052270555240, 0.00056516734709, 0.00058803959079, 0.00061213685774, 0.00063753303271, 0.00066436020792, 0.00069271759254, 0.00072278590327, 0.00075471258665, 0.00078871891980, 0.00082495135506, 0.00086370796092, 0.00090520244315, 0.00094974375995, 0.00099759142132, 0.00104912583361, 0.00110468513550, 0.00116471796237, 0.00122961947450, 0.00129997381226, 0.00137633261223, 0.00145941148983, 0.00150367150729, 0.00154993475674, 0.00164886456582, 0.00170177926583, 0.00175721404389, 0.00181530011799, 0.00187625634148, 0.00194016482197, 0.00200732582737, 0.00207790286653, 0.00215216527238, 0.00223029743932, 0.00231263720905, 0.00239942910043, 0.00249104495897, 0.00258772950799, 0.00268995918708, 0.00279808620674, 0.00291260618091, 0.00303393957317, 0.00316270550389, 0.00329945165204, 0.00344491415323, 0.00359970294452, 0.00376478162054, 0.00394100416242, 0.00412946943549, 0.00433124287660, 0.00454769286700, 0.00466181286329, 0.00478015613269, 0.00490287219562, 0.00503023860438, 0.00516231516987, 0.00529948405762, 0.00544190977016, 0.00558989424000, 0.00574363032708, 0.00590348262538, 0.00606970711776, 0.00624269632708, 0.00642267044700, 0.00661012222834, 0.00680537865824, 0.00700890517615, 0.00722105704960, 0.00744238908118, 0.00767333589656, 0.00791450623655, 0.00816629638134, 0.00842946839953, 0.00870457800002, 0.00899236514987, 0.00929347419740, 0.00960877976327, 0.00993906664874, 0.01028531629401, 0.01064836560114, 0.01102939995868, 0.01142946986211, 0.01184984756038, 0.01229174638031, 0.01275666542031, 0.01324605799479, 0.01376164646858, 0.01430505034994, 0.01487834806441, 0.01517680797833, 0.01548355354501, 0.01579883472796, 0.01612301677381, 0.01645629840316, 0.01679913158769, 0.01715180723470, 0.01751473695387, 0.01788823000264, 0.01827276128134, 0.01866870741769, 0.01907658694645, 0.01949670526428, 0.01992970835114, 0.02037603813266, 0.02083628226895, 0.02131092986923, 0.02180065884019, 0.02230604531786, 0.02282781673939, 0.02336654192662, 0.02392307856762, 0.02449812744245, 0.02509254651992, 0.02570710318883, 0.02634276037547, 0.02700040459895, 0.02768108720588, 0.02838568468843, 0.02911543211252, 0.02987138853965, 0.03065480656468, 0.03146687637367, 0.03230902465341, 0.03318262955971, 0.03408928114548, 0.03503049532094, 0.03600813039164, 0.03702399530373, 0.03808014377487, 0.03917864953982, 0.04032188867370, 0.04151227866069, 0.04275252873894, 0.04404534794164, 0.04539391077701, 0.04609007134882, 0.04680142876348)

CodePudding user response：

Here's one way but I bet there are more concise/elegant alternatives.

library(dplyr)
tidyr::crossing(df1, df2) %>%
  filter(df1_col < df2_col1) %>%
  group_by(df1_col) %>%
  slice_min(df2_col1) %>%
  ungroup()

CodePudding user response：

First sort df2

> df2=df2[order(df2$df2_col1),,drop=F]

using apply to obtain the indices

> tmp=apply(df1,1,function(x){which.max(df2$df2_col1>x)})
[1]  2  5  7  9 11

using these indices in df2 you get

> df2[tmp,]
[1] 2.002614e-05 1.078562e-04 2.017390e-04 1.049126e-03 2.007326e-03