Hi Alexander,
Thank you so much for taking the time to outline these suggestions!?
What if I wanted to only isolate the y-value at x = 1.0 across all of my 10 dataframes? That way, I could quickly see what the highest and lowest y-value is at x = 1.0? That said, in reality, not all x values are precisely 1.0 (it can be something like 0.99 to 1.02), but the idea is to target the y-value at x = ~1.0. Is that at all possible??
Thanks, again!
-----Original Message-----
From: Alexander Ilich <ailich at usf.edu>
To: r-sig-geo at r-project.org <r-sig-geo at r-project.org>; rain1290 at aim.com <rain1290 at aim.com>
Sent: Wed, May 10, 2023 10:31 am
Subject: Re: [R-sig-Geo] Finding the highest and lowest rates of increase at specific x value across several time series in R
#yiv9338178727 P {margin-top:0;margin-bottom:0;}So using your data but removing x=1, 0.8 and 1.2 would be equally close. Two potential options are to choose the y value corresponding to the first minimum difference (in this case x=0.8, y=39), or average the y values for all that are equally close (in this case average the y values for x=0.8 and x=1.2). I think the easiest wayodo that would to first calculate a column of the absolute value of differences between x and 1 and then subset the dataframe to the minimum of that column to extract the y values. Here's a base R and tidyverse implementation to do that.
#Base Rdf<- data.frame(x=c(0,0.2,0.4,0.6,0.8,1.2,1.4),? ? ? ? ? ? ? ? y= c(0,27,31,32,39,34,25))df$abs_diff<- abs(df$x-1)
df$y[which.min(df$abs_diff)] #Get first y value of closest to x=1#> [1] 39mean(df$y[df$abs_diff==min(df$abs_diff)]) #Average all y values that are closest to x=1#> [1] 36.5
#tidyverse
rm(list=ls())library(dplyr)
df<- data.frame(x=c(0,0.2,0.4,0.6,0.8,1.2,1.4),? ? ? ? ? ? ? ? y= c(0,27,31,32,39,34,25))df<- df %>% mutate(abs_diff = abs(x-1))
df %>% filter(abs_diff==min(abs_diff)) %>% pull(y) %>% head(1) #Get first y value of closest to x=1#> [1] 39
df %>% filter(abs_diff==min(abs_diff)) %>% pull(y) %>% mean() #Average all y values that are closest to x=1#> [1] 36.5From: rain1290 at aim.com <rain1290 at aim.com>
Sent: Wednesday, May 10, 2023 8:13 AM
To: Alexander Ilich <ailich at usf.edu>; r-sig-geo at r-project.org <r-sig-geo at r-project.org>
Subject: Re: [R-sig-Geo] Finding the highest and lowest rates of increase at specific x value across several time series in R?Hi Alex and everyone,
My apologies for the confusion and this double message (I just noticed that the example dataset appeared distorted)! Let me try to simplify here again.
My dataframes are structured in the following way: an x column and y column, like this:
Now, let's say that I want to determine the rate of increase at about x = 1.0, relative to the beginning of the period (i.e. 0 at the beginning). We can see clearly here that the answer would be y = 43. My question is would it be possible to quickly determine the value at around x = 1.0 across the 10 dataframes that I have like this without having to manually check them? The idea is to determine the range of values for y at around x = 1.0 across all dataframes. Note that it's not perfectly x = 1.0 in all dataframes - some could be 0.99 or 1.01.??
I hope that this is clearer!
Thanks,
-----Original Message-----
From: Alexander Ilich <ailich at usf.edu>
To: r-sig-geo at r-project.org <r-sig-geo at r-project.org>; rain1290 at aim.com <rain1290 at aim.com>
Sent: Tue, May 9, 2023 2:23 pm
Subject: Re: [R-sig-Geo] Finding the highest and lowest rates of increase at specific x value across several time series in R
<!--#yiv9338178727 #yiv9338178727x_yiv7769615370 p {margin-top:0;margin-bottom:0;}-->I'm currently having a bit of difficultly following. Rather than using your actual data, perhaps you could include code to generate a smaller dataset with the same structure with clear definitions of what is contained within each (r faq - How to make a great R reproducible example - Stack Overflow). You can design that dataset to be small with a known answer and the describe how you got to that answer and then others could help determine some code to accomplish that task.
Best Regards,AlexFrom: R-sig-Geo <r-sig-geo-bounces at r-project.org> on behalf of rain1290--- via R-sig-Geo <r-sig-geo at r-project.org>
Sent: Tuesday, May 9, 2023 1:01 PM
To: r-sig-geo at r-project.org <r-sig-geo at r-project.org>
Subject: [R-sig-Geo] Finding the highest and lowest rates of increase at specific x value across several time series in R?I would like to attempt to determine the difference between the highest and lowest rates of increase across a series of dataframes at a specified x value. As shown below, the dataframes have basic x and y columns, with emissions values in the x column, and precipitation values in the y column. Among the dataframes, the idea would be to determine the highest and lowest rates of precipitation increase at "approximately" 1 Terratons of emissions (TtC) relative to the first value of each time series. For example, I want to figure out which dataframe has the highest increase at 1 TtC, and which dataframe has the lowest increase at 1 TtC. at However, I am not sure if there is a way to quickly achieve this? Here are the dataframes that I created, followed by an example of how each dataframe is structured:
#Dataframe objects created:
??? CanESMRCP8.5PL<-data.frame(get3.teratons, pland20)???? IPSLLRRCP8.5PL<-data.frame(get6.teratons, pland21)??? IPSLMRRCP8.5PL<-data.frame(get9.teratons, pland22)??? IPSLLRBRCP8.5PL<-data.frame(get12.teratons, pland23)??? MIROCRCP8.5PL<-data.frame(get15.teratons, pland24)??? HadGEMRCP8.5PL<-data.frame(get18.teratons, pland25)??? MPILRRCP8.5PL<-data.frame(get21.teratons, pland26)??? GFDLGRCP8.5PL<-data.frame(get27.teratons, pland27)??? GFDLMRCP8.5PL<-data.frame(get30.teratons, pland28)
#Example of what each of these look like:
??? >CanESMRCP8.5PL
??????? get3.teratons?? pland20??? X1????? 0.4542249 13.252426??? X2????? 0.4626662? 3.766658??? X3????? 0.4715780? 2.220986??? X4????? 0.4809204? 8.495072??? X5????? 0.4901427 10.206458??? X6????? 0.4993126 10.942797??? X7????? 0.5088599? 6.592956??? X8????? 0.5187588? 2.435796??? X9????? 0.5286758? 2.275836??? X10???? 0.5389284? 5.051706??? X11???? 0.5496212? 8.313389??? X12???? 0.5600628? 9.007722??? X13???? 0.5708608 11.905644??? X14???? 0.5819234? 6.126022??? X15???? 0.5926283? 9.883264??? X16???? 0.6042306? 7.699696??? X17???? 0.6159752? 5.614193??? X18???? 0.6274483? 6.681527??? X19???? 0.6394011 10.112812??? X20???? 0.6519496? 8.721810??? X21???? 0.6646344 10.315931??? X22???? 0.6773436 11.372490??? X23???? 0.6903203? 8.662169??? X24???? 0.7036479 10.106109??? X25???? 0.7180955 10.990867??? X26???? 0.7322746 13.491778??? X27???? 0.7459771 17.256650??? X28???? 0.7604589 12.040960??? X29???? 0.7753096 10.638796??? X30???? 0.7898374? 7.889500??? X31???? 0.8047258 11.757174??? X32???? 0.8204160 15.060151??? X33???? 0.8359387? 9.822078??? X34???? 0.8510721 11.388695??? X35???? 0.8661237 10.271567??? X36???? 0.8815913 13.224285??? X37???? 0.8984146 15.584782??? X38???? 0.9154501? 9.320024??? X39???? 0.9324529? 9.187128??? X40???? 0.9497379 12.919805??? X41???? 0.9672824 15.190318??? X42???? 0.9854439 12.098606??? X43???? 1.0041460 16.758629??? X44???? 1.0241779 17.435182??? X45???? 1.0451656 15.323428??? X46???? 1.0663605 18.292109??? X47???? 1.0868977 12.625429??? X48???? 1.1079376 17.318583??? X49???? 1.1295719 14.056624??? X50???? 1.1516720 18.239445??? X51???? 1.1736696 16.312087??? X52???? 1.1963065 18.683315??? X53???? 1.2195753 20.364835??? X54???? 1.2425277 14.337167??? X55???? 1.2653873 16.072449??? X56???? 1.2888002 14.870248??? X57???? 1.3126799 18.431717??? X58???? 1.3362459 19.873449??? X59???? 1.3593610 17.278361??? X60???? 1.3833589 18.532887??? X61???? 1.4083234 16.178170??? X62???? 1.4328881 17.689810??? X63???? 1.4572568 21.395131??? X64???? 1.4821021 20.154886??? X65???? 1.5072721 15.655971??? X66???? 1.5325393 21.692028??? X67???? 1.5581797 23.258303??? X68???? 1.5842384 23.802459??? X69???? 1.6108635 15.824673??? X70???? 1.6365393 19.016228??? X71???? 1.6618322 20.957593??? X72???? 1.6876948 19.105363??? X73???? 1.7134712 19.759288??? X74???? 1.7392598 27.315595??? X75???? 1.7652725 24.882263??? X76???? 1.7913807 25.813408??? X77???? 1.8173818 23.658997??? X78???? 1.8434211 24.223432??? X79???? 1.8695911 23.560818??? X80???? 1.8960611 28.057708??? X81???? 1.9228969 26.996265??? X82???? 1.9493552 26.659719??? X83???? 1.9759324 22.723687??? X84???? 2.0026666 30.977267??? X85???? 2.0290137 29.384326??? X86???? 2.0549359 24.840383??? X87???? 2.0811679 26.952620??? X88???? 2.1081763 29.894790??? X89???? 2.1349227 25.224040??? X90???? 2.1613017 27.722623
??? >IPSLLRRCP8.5PL
??????? get6.teratons?? pland21??? X1????? 0.5300411? 8.128827??? X2????? 0.5401701? 6.683660??? X3????? 0.5503503 12.344974??? X4????? 0.5607762 11.322411??? X5????? 0.5714146 14.250646??? X6????? 0.5825357 10.013592??? X7????? 0.5937966? 9.437394??? X8????? 0.6051673? 8.138396??? X9????? 0.6168960? 9.767765??? X10???? 0.6290367? 8.166579??? X11???? 0.6413864 12.307348??? X12???? 0.6539184 12.623931??? X13???? 0.6667360 11.182448??? X14???? 0.6800060 12.585040??? X15???? 0.6935350 13.408614??? X16???? 0.7071757? 9.352335??? X17???? 0.7211951 12.743725??? X18???? 0.7356089 11.625612??? X19???? 0.7502665 10.240418??? X20???? 0.7650959 12.394282??? X21???? 0.7800845 16.963066??? X22???? 0.7953119 16.380090??? X23???? 0.8107459 10.510501??? X24???? 0.8260236 12.645911??? X25???? 0.8414439 14.134851??? X26???? 0.8572960 18.924963??? X27???? 0.8732313 17.849050??? X28???? 0.8892344 10.941533??? X29???? 0.9057380 12.034925??? X30???? 0.9223530 15.897904??? X31???? 0.9391578 19.707692??? X32???? 0.9563358 16.690375??? X33???? 0.9738711 18.098571??? X34???? 0.9916517 16.588447??? X35???? 1.0096934 16.125172??? X36???? 1.0279473 19.108647??? X37???? 1.0463864 16.972994??? X38???? 1.0653421 22.869403??? X39???? 1.0842487 21.228874??? X40???? 1.1035309 25.509754??? X41???? 1.1230403 15.579367??? X42???? 1.1426743 21.259726??? X43???? 1.1626806 26.061262??? X44???? 1.1833831 21.918530??? X45???? 1.2045888 22.369094??? X46???? 1.2262981 21.480456??? X47???? 1.2481395 20.503543??? X48???? 1.2703019 27.717028??? X49???? 1.2929382 26.295449??? X50???? 1.3157745 28.271455??? X51???? 1.3390449 31.595651??? X52???? 1.3626052 26.188018??? X53???? 1.3863833 26.326999??? X54???? 1.4102701 26.902272??? X55???? 1.4343871 25.308764??? X56???? 1.4584666 23.789699??? X57???? 1.4831504 26.916504??? X58???? 1.5080384 32.921638??? X59???? 1.5331210 29.753267??? X60???? 1.5582794 29.567720??? X61???? 1.5832585 31.454097??? X62???? 1.6085002 26.602191??? X63???? 1.6339502 35.873728??? X64???? 1.6594560 34.222654??? X65???? 1.6851070 36.290959??? X66???? 1.7109757 31.623912??? X67???? 1.7368503 31.965520??? X68???? 1.7626750 41.490310??? X69???? 1.7883216 35.645934??? X70???? 1.8141292 35.639422??? X71???? 1.8405670 37.085608??? X72???? 1.8672313 44.812777??? X73???? 1.8939987 40.044602??? X74???? 1.9208222 37.834526??? X75???? 1.9478806 44.497335??? X76???? 1.9750195 39.839740??? X77???? 2.0024118 38.300529??? X78???? 2.0302205 52.116649??? X79???? 2.0581589 59.189047??? X80???? 2.0861536 51.559857??? X81???? 2.1141780 43.305779??? X82???? 2.1421791 47.950074??? X83???? 2.1703249 46.252149??? X84???? 2.1985953 47.536605??? X85???? 2.2266540 49.422466??? X86???? 2.2547762 44.577399??? X87???? 2.2827062 49.720523??? X88???? 2.3102098 47.138244??? X89???? 2.3379090 51.882832??? X90???? 2.3656370 51.413472
Etc...
Any help with this would be greatly appreciated!
Thanks,
??????? [[alternative HTML version deleted]]
_______________________________________________
R-sig-Geo mailing list
R-sig-Geo at r-project.org
https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-sig-geo&data=05%7C01%7Cailich%40usf.edu%7Cb59e2f81076143e9b0a408db50af0b78%7C741bf7dee2e546df8d6782607df9deaa%7C0%7C0%7C638192484981183656%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=iwGeEZIJDfmhJ5TkfQxq5htErTGihLIrl7T5nJ6fIC0%3D&reserved=0
[EXTERNAL EMAIL] DO NOT CLICK links or attachments unless you recognize the sender and know the content is safe.
[EXTERNAL EMAIL] DO NOT CLICK links or attachments unless you recognize the sender and know the content is safe.