Stefano Sofia
2016-Sep-07 11:09 UTC
[R] how to manage missing values correctly when importing a data frame
Dear R users, I have a data frame with 22 columns, called Storia_RM_RT. Here the first 4 rows: Station_RM Sensor_RM Place_RM Y_init_RM M_init_RM D_init_RM Long_cent_RM Lat_cent_RM Height_RM Continues Station_RT Sensor_RT Place_RT Name1_RT Name2_RT Long_cent_RT Lat_cent_RT Height_RT Actual_net Notes Test_20141231 Test_20151231 1400 2701 Novafeltria 1959 1 1 12.289552 43.890057 293 NO NA NA NA NA NA NA NA NA CAE NA NO NO 1460 2702 Carpegna 1963 1 1 12.332614 43.778107 748 SI 702 2954 Carpegna Carpegna Carpegna 12.340618 43.780575 715 RT NA NO NO 1500 2703 Pesaro 1957 1 1 12.909822 43.910889 11 SI 112 1229 Pesaro Villa_Fastiggi Villa_Fastiggi 12.86939 43.890610 22 RT NA YES YES 1520 2704 Fano 1957 1 1 13.017591 43.840054 4 SI 152 2671 Fano Foce_Metauro Metaurilia 13.053796 43.826328 7.12 RT NA YES YES I load it with Storia_RM_RT <- read.table(file="Storia_RM_RT.txt", header = TRUE, sep=" ", dec = ".", stringsAsFactors = FALSE) print(Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RM == 1500]) gives [1] "YES" while print(Storia_RM_RT$Omogenea_20151231[Storia_RM_RT$Station_RT == 112]) gives [1] NA "YES" print(lapply(Storia_RM_RT, class)) gives $Station_RM [1] "integer" $Sensor_RM [1] "integer" $Place_RM [1] "character" $Y_init_RM [1] "integer" $M_init_RM [1] "integer" $D_init_RM [1] "integer" $Long_cent_RM [1] "numeric" $Lat_cent_RM [1] "numeric" $Height_RM [1] "integer" $Continues [1] "character" $Station_RT [1] "integer" $Sensor_RT [1] "integer" $Place_RT [1] "character" $Name1_RT [1] "character" $Name2_RT [1] "character" $Long_cent_RT [1] "numeric" $Lat_cent_RT [1] "numeric" $Quota_RT [1] "numeric" $Actual_net [1] "character" $Notes [1] "logical" $Test_20141231 [1] "character" $Test_20151231 [1] "character" I am struggling to understand why the query through the field Station_RT does not work. Could please somebody help me to manage correctly the missing values? Is the mistake somewhere else? Thank you Stefano Sofia ________________________________ AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu? contenere informazioni confidenziali, pertanto ? destinato solo a persone autorizzate alla ricezione. I messaggi di posta elettronica per i client di Regione Marche possono contenere informazioni confidenziali e con privilegi legali. Se non si ? il destinatario specificato, non leggere, copiare, inoltrare o archiviare questo messaggio. Se si ? ricevuto questo messaggio per errore, inoltrarlo al mittente ed eliminarlo completamente dal sistema del proprio computer. Ai sensi dell?art. 6 della DGR n. 1394/2008 si segnala che, in caso di necessit? ed urgenza, la risposta al presente messaggio di posta elettronica pu? essere visionata da persone estranee al destinatario. IMPORTANT NOTICE: This e-mail message is intended to be received only by persons entitled to receive the confidential information it may contain. E-mail messages to clients of Regione Marche may contain information that is confidential and legally privileged. Please do not read, copy, forward, or store this message unless you are an intended recipient of it. If you have received this message in error, please forward it to the sender and delete it completely from your computer system. [[alternative HTML version deleted]]
Sarah Goslee
2016-Sep-07 13:11 UTC
[R] how to manage missing values correctly when importing a data frame
R is refusing to make unwarranted assumptions about your data.
See inline.
# it's nicer to use dput() instead of pasting raw data
Storia_RM_RT <- structure(list(Station_RM = c(1400L, 1460L, 1500L,
1520L), Sensor_RM = 2701:2704,
Place_RM = c("Novafeltria", "Carpegna",
"Pesaro", "Fano"),
Y_init_RM = c(1959L, 1963L, 1957L, 1957L), M_init_RM = c(1L,
1L, 1L, 1L), D_init_RM = c(1L, 1L, 1L, 1L), Long_cent_RM = c(12.289552,
12.332614, 12.909822, 13.017591), Lat_cent_RM = c(43.890057,
43.778107, 43.910889, 43.840054), Height_RM = c(293L, 748L,
11L, 4L), Continues = c("NO", "SI", "SI",
"SI"), Station_RT = c(NA,
702L, 112L, 152L), Sensor_RT = c(NA, 2954L, 1229L, 2671L),
Place_RT = c(NA, "Carpegna", "Pesaro",
"Fano"), Name1_RT = c(NA,
"Carpegna", "Villa_Fastiggi", "Foce_Metauro"),
Name2_RT = c(NA,
"Carpegna", "Villa_Fastiggi", "Metaurilia"),
Long_cent_RT = c(NA,
12.340618, 12.86939, 13.053796), Lat_cent_RT = c(NA, 43.780575,
43.89061, 43.826328), Height_RT = c(NA, 715, 22, 7.12), Actual_net
= c("CAE",
"RT", "RT", "RT"), Notes = c(NA, NA, NA, NA),
Test_20141231 = c("NO",
"NO", "YES", "YES"), Test_20151231 =
c("NO", "NO", "YES",
"YES")), .Names = c("Station_RM", "Sensor_RM",
"Place_RM",
"Y_init_RM", "M_init_RM", "D_init_RM",
"Long_cent_RM", "Lat_cent_RM",
"Height_RM", "Continues", "Station_RT",
"Sensor_RT", "Place_RT",
"Name1_RT", "Name2_RT", "Long_cent_RT",
"Lat_cent_RT", "Height_RT",
"Actual_net", "Notes", "Test_20141231",
"Test_20151231"), class "data.frame", row.names = c(NA,
-4L))
> Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RM == 1500]
[1] "YES"
# Storia_RM_RT$Omogenea_20151231[Storia_RM_RT$Station_RT == 112]
# there's no such column; you probably mean Test_20151231
> Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RT == 112]
[1] NA "YES"
# What do you expect to have happen when Station_RT is NA? R has no idea
# whether it is 112 or not, so R returns an "I don't know" value
that
# lets the user decide how to handle the missing data, rather than making
# assumptions.
# But you probably want one of these constructions:
Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RT == 112 &
!is.na(Storia_RM_RT$Station_RT)]
# subset automatically handles NAs, making the assumption I'm assuming you
want.
subset(Storia_RM_RT, Station_RT == 112 )$Test_20151231
# This is the first form, somewhat more elegantly
with(Storia_RM_RT, Test_20151231[Station_RT == 112 & !is.na(Station_RT)])
On Wed, Sep 7, 2016 at 7:09 AM, Stefano Sofia
<stefano.sofia at regione.marche.it> wrote:> Dear R users,
> I have a data frame with 22 columns, called Storia_RM_RT. Here the first 4
rows:
>
> Station_RM Sensor_RM Place_RM Y_init_RM M_init_RM D_init_RM Long_cent_RM
Lat_cent_RM Height_RM Continues Station_RT Sensor_RT Place_RT Name1_RT Name2_RT
Long_cent_RT Lat_cent_RT Height_RT Actual_net Notes Test_20141231 Test_20151231
> 1400 2701 Novafeltria 1959 1 1 12.289552 43.890057 293 NO NA NA NA NA NA NA
NA NA CAE NA NO NO
> 1460 2702 Carpegna 1963 1 1 12.332614 43.778107 748 SI 702 2954 Carpegna
Carpegna Carpegna 12.340618 43.780575 715 RT NA NO NO
> 1500 2703 Pesaro 1957 1 1 12.909822 43.910889 11 SI 112 1229 Pesaro
Villa_Fastiggi Villa_Fastiggi 12.86939 43.890610 22 RT NA YES YES
> 1520 2704 Fano 1957 1 1 13.017591 43.840054 4 SI 152 2671 Fano Foce_Metauro
Metaurilia 13.053796 43.826328 7.12 RT NA YES YES
>
> I load it with
> Storia_RM_RT <- read.table(file="Storia_RM_RT.txt", header =
TRUE, sep=" ", dec = ".", stringsAsFactors = FALSE)
>
> print(Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RM == 1500]) gives
> [1] "YES"
>
> while
> print(Storia_RM_RT$Omogenea_20151231[Storia_RM_RT$Station_RT == 112]) gives
> [1] NA "YES"
>
>
> print(lapply(Storia_RM_RT, class)) gives
>
> $Station_RM
> [1] "integer"
>
> $Sensor_RM
> [1] "integer"
>
> $Place_RM
> [1] "character"
>
> $Y_init_RM
> [1] "integer"
>
> $M_init_RM
> [1] "integer"
>
> $D_init_RM
> [1] "integer"
>
> $Long_cent_RM
> [1] "numeric"
>
> $Lat_cent_RM
> [1] "numeric"
>
> $Height_RM
> [1] "integer"
>
> $Continues
> [1] "character"
>
> $Station_RT
> [1] "integer"
>
> $Sensor_RT
> [1] "integer"
>
> $Place_RT
> [1] "character"
>
> $Name1_RT
> [1] "character"
>
> $Name2_RT
> [1] "character"
>
> $Long_cent_RT
> [1] "numeric"
>
> $Lat_cent_RT
> [1] "numeric"
> $Quota_RT
> [1] "numeric"
>
> $Actual_net
> [1] "character"
>
> $Notes
> [1] "logical"
>
> $Test_20141231
> [1] "character"
>
> $Test_20151231
> [1] "character"
>
> I am struggling to understand why the query through the field Station_RT
does not work.
> Could please somebody help me to manage correctly the missing values? Is
the mistake somewhere else?
>
> Thank you
> Stefano Sofia
>
>
--
Sarah Goslee
http://www.functionaldiversity.org
PIKAL Petr
2016-Sep-07 13:49 UTC
[R] how to manage missing values correctly when importing a data frame
Hi Although you did not present your data in suitable format I do not see any problem. See in line> -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Stefano > Sofia > Sent: Wednesday, September 7, 2016 1:09 PM > To: r-help at r-project.org > Subject: [R] how to manage missing values correctly when importing a data > frame > > Dear R users, > I have a data frame with 22 columns, called Storia_RM_RT. Here the first 4 > rows: > > Station_RM Sensor_RM Place_RM Y_init_RM M_init_RM D_init_RM > Long_cent_RM Lat_cent_RM Height_RM Continues Station_RT Sensor_RT > Place_RT Name1_RT Name2_RT Long_cent_RT Lat_cent_RT Height_RT > Actual_net Notes Test_20141231 Test_20151231 > 1400 2701 Novafeltria 1959 1 1 12.289552 43.890057 293 NO NA NA NA NA NA > NA NA NA CAE NA NO NO > 1460 2702 Carpegna 1963 1 1 12.332614 43.778107 748 SI 702 2954 Carpegna > Carpegna Carpegna 12.340618 43.780575 715 RT NA NO NO > 1500 2703 Pesaro 1957 1 1 12.909822 43.910889 11 SI 112 1229 Pesaro > Villa_Fastiggi Villa_Fastiggi 12.86939 43.890610 22 RT NA YES YES > 1520 2704 Fano 1957 1 1 13.017591 43.840054 4 SI 152 2671 Fano > Foce_Metauro Metaurilia 13.053796 43.826328 7.12 RT NA YES YES > > I load it with > Storia_RM_RT <- read.table(file="Storia_RM_RT.txt", header = TRUE, sep=" > ", dec = ".", stringsAsFactors = FALSE) > > print(Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RM == 1500]) > gives [1] "YES"So you have unique value here> > while > print(Storia_RM_RT$Omogenea_20151231[Storia_RM_RT$Station_RT => 112]) gives > [1] NA "YES"and two values here, one is NA see dat<-data.frame(x1=c("a", "a", "b", NA), x2=c(1,2,3,3)) dat$x1<-as.character(dat$x1)> dat$x1[dat$x2==1][1] "a"> dat$x1[dat$x2==2][1] "a"> dat$x1[dat$x2==3][1] "b" NA>You should consult R intro to understand basic object types, their distinctions and language basics. Cheers Petr> > > print(lapply(Storia_RM_RT, class)) gives > > $Station_RM > [1] "integer" > > $Sensor_RM > [1] "integer" > > $Place_RM > [1] "character" > > $Y_init_RM > [1] "integer" > > $M_init_RM > [1] "integer" > > $D_init_RM > [1] "integer" > > $Long_cent_RM > [1] "numeric" > > $Lat_cent_RM > [1] "numeric" > > $Height_RM > [1] "integer" > > $Continues > [1] "character" > > $Station_RT > [1] "integer" > > $Sensor_RT > [1] "integer" > > $Place_RT > [1] "character" > > $Name1_RT > [1] "character" > > $Name2_RT > [1] "character" > > $Long_cent_RT > [1] "numeric" > > $Lat_cent_RT > [1] "numeric" > $Quota_RT > [1] "numeric" > > $Actual_net > [1] "character" > > $Notes > [1] "logical" > > $Test_20141231 > [1] "character" > > $Test_20151231 > [1] "character" > > I am struggling to understand why the query through the field Station_RT > does not work. > Could please somebody help me to manage correctly the missing values? Is > the mistake somewhere else? > > Thank you > Stefano Sofia > > > ________________________________ > > AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu? contenere > informazioni confidenziali, pertanto ? destinato solo a persone autorizzate > alla ricezione. I messaggi di posta elettronica per i client di Regione Marche > possono contenere informazioni confidenziali e con privilegi legali. Se non si ? > il destinatario specificato, non leggere, copiare, inoltrare o archiviare questo > messaggio. Se si ? ricevuto questo messaggio per errore, inoltrarlo al > mittente ed eliminarlo completamente dal sistema del proprio computer. Ai > sensi dell?art. 6 della DGR n. 1394/2008 si segnala che, in caso di necessit? ed > urgenza, la risposta al presente messaggio di posta elettronica pu? essere > visionata da persone estranee al destinatario. > IMPORTANT NOTICE: This e-mail message is intended to be received only by > persons entitled to receive the confidential information it may contain. E-mail > messages to clients of Regione Marche may contain information that is > confidential and legally privileged. Please do not read, copy, forward, or store > this message unless you are an intended recipient of it. If you have received > this message in error, please forward it to the sender and delete it > completely from your computer system. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code.________________________________ Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a jsou ur?eny pouze jeho adres?t?m. Jestli?e jste obdr?el(a) tento e-mail omylem, informujte laskav? neprodlen? jeho odes?latele. Obsah tohoto emailu i s p??lohami a jeho kopie vyma?te ze sv?ho syst?mu. Nejste-li zam??len?m adres?tem tohoto emailu, nejste opr?vn?ni tento email jakkoliv u??vat, roz?i?ovat, kop?rovat ?i zve?ej?ovat. 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Stefano Sofia
2016-Sep-07 14:26 UTC
[R] how to manage missing values correctly when importing a data frame
Thank you for your explanations, and your patience.
With all the humbleness that I can have, I am not a beginner in R. Said that I
am really sorry if my question shows a big lack in understanding some basic
object types and their distinctions.
I still find difficult to understand your comments (which are obviously
correct), and I beg your pardon if I keep asking you the same question.
In my query to the data frame, Station_RT is exactly 112, and there is only one
row where Station_RT is equal to 112. I would expect a unique value for
Test_20151231.
Why R should expect to handle the possibility of having Station_RT = NA?
# > Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RT == 112]
# What do you expect to have happen when Station_RT is NA? R has no idea
# whether it is 112 or not, so R returns an "I don't know" value
that
# lets the user decide how to handle the missing data, rather than making
# assumptions.
Again, sorry for my question
Stefano
________________________________________
Da: Sarah Goslee [sarah.goslee at gmail.com]
Inviato: mercoled? 7 settembre 2016 15.11
A: Stefano Sofia
Cc: r-help at r-project.org
Oggetto: Re: [R] how to manage missing values correctly when importing a data
frame
R is refusing to make unwarranted assumptions about your data.
See inline.
# it's nicer to use dput() instead of pasting raw data
Storia_RM_RT <- structure(list(Station_RM = c(1400L, 1460L, 1500L,
1520L), Sensor_RM = 2701:2704,
Place_RM = c("Novafeltria", "Carpegna",
"Pesaro", "Fano"),
Y_init_RM = c(1959L, 1963L, 1957L, 1957L), M_init_RM = c(1L,
1L, 1L, 1L), D_init_RM = c(1L, 1L, 1L, 1L), Long_cent_RM = c(12.289552,
12.332614, 12.909822, 13.017591), Lat_cent_RM = c(43.890057,
43.778107, 43.910889, 43.840054), Height_RM = c(293L, 748L,
11L, 4L), Continues = c("NO", "SI", "SI",
"SI"), Station_RT = c(NA,
702L, 112L, 152L), Sensor_RT = c(NA, 2954L, 1229L, 2671L),
Place_RT = c(NA, "Carpegna", "Pesaro",
"Fano"), Name1_RT = c(NA,
"Carpegna", "Villa_Fastiggi", "Foce_Metauro"),
Name2_RT = c(NA,
"Carpegna", "Villa_Fastiggi", "Metaurilia"),
Long_cent_RT = c(NA,
12.340618, 12.86939, 13.053796), Lat_cent_RT = c(NA, 43.780575,
43.89061, 43.826328), Height_RT = c(NA, 715, 22, 7.12), Actual_net
= c("CAE",
"RT", "RT", "RT"), Notes = c(NA, NA, NA, NA),
Test_20141231 = c("NO",
"NO", "YES", "YES"), Test_20151231 =
c("NO", "NO", "YES",
"YES")), .Names = c("Station_RM", "Sensor_RM",
"Place_RM",
"Y_init_RM", "M_init_RM", "D_init_RM",
"Long_cent_RM", "Lat_cent_RM",
"Height_RM", "Continues", "Station_RT",
"Sensor_RT", "Place_RT",
"Name1_RT", "Name2_RT", "Long_cent_RT",
"Lat_cent_RT", "Height_RT",
"Actual_net", "Notes", "Test_20141231",
"Test_20151231"), class "data.frame", row.names = c(NA,
-4L))
> Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RM == 1500]
[1] "YES"
# Storia_RM_RT$Omogenea_20151231[Storia_RM_RT$Station_RT == 112]
# there's no such column; you probably mean Test_20151231
> Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RT == 112]
[1] NA "YES"
# What do you expect to have happen when Station_RT is NA? R has no idea
# whether it is 112 or not, so R returns an "I don't know" value
that
# lets the user decide how to handle the missing data, rather than making
# assumptions.
# But you probably want one of these constructions:
Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RT == 112 &
!is.na(Storia_RM_RT$Station_RT)]
# subset automatically handles NAs, making the assumption I'm assuming you
want.
subset(Storia_RM_RT, Station_RT == 112 )$Test_20151231
# This is the first form, somewhat more elegantly
with(Storia_RM_RT, Test_20151231[Station_RT == 112 & !is.na(Station_RT)])
On Wed, Sep 7, 2016 at 7:09 AM, Stefano Sofia
<stefano.sofia at regione.marche.it> wrote:> Dear R users,
> I have a data frame with 22 columns, called Storia_RM_RT. Here the first 4
rows:
>
> Station_RM Sensor_RM Place_RM Y_init_RM M_init_RM D_init_RM Long_cent_RM
Lat_cent_RM Height_RM Continues Station_RT Sensor_RT Place_RT Name1_RT Name2_RT
Long_cent_RT Lat_cent_RT Height_RT Actual_net Notes Test_20141231 Test_20151231
> 1400 2701 Novafeltria 1959 1 1 12.289552 43.890057 293 NO NA NA NA NA NA NA
NA NA CAE NA NO NO
> 1460 2702 Carpegna 1963 1 1 12.332614 43.778107 748 SI 702 2954 Carpegna
Carpegna Carpegna 12.340618 43.780575 715 RT NA NO NO
> 1500 2703 Pesaro 1957 1 1 12.909822 43.910889 11 SI 112 1229 Pesaro
Villa_Fastiggi Villa_Fastiggi 12.86939 43.890610 22 RT NA YES YES
> 1520 2704 Fano 1957 1 1 13.017591 43.840054 4 SI 152 2671 Fano Foce_Metauro
Metaurilia 13.053796 43.826328 7.12 RT NA YES YES
>
> I load it with
> Storia_RM_RT <- read.table(file="Storia_RM_RT.txt", header =
TRUE, sep=" ", dec = ".", stringsAsFactors = FALSE)
>
> print(Storia_RM_RT$Test_20151231[Storia_RM_RT$Station_RM == 1500]) gives
> [1] "YES"
>
> while
> print(Storia_RM_RT$Omogenea_20151231[Storia_RM_RT$Station_RT == 112]) gives
> [1] NA "YES"
>
>
> print(lapply(Storia_RM_RT, class)) gives
>
> $Station_RM
> [1] "integer"
>
> $Sensor_RM
> [1] "integer"
>
> $Place_RM
> [1] "character"
>
> $Y_init_RM
> [1] "integer"
>
> $M_init_RM
> [1] "integer"
>
> $D_init_RM
> [1] "integer"
>
> $Long_cent_RM
> [1] "numeric"
>
> $Lat_cent_RM
> [1] "numeric"
>
> $Height_RM
> [1] "integer"
>
> $Continues
> [1] "character"
>
> $Station_RT
> [1] "integer"
>
> $Sensor_RT
> [1] "integer"
>
> $Place_RT
> [1] "character"
>
> $Name1_RT
> [1] "character"
>
> $Name2_RT
> [1] "character"
>
> $Long_cent_RT
> [1] "numeric"
>
> $Lat_cent_RT
> [1] "numeric"
> $Quota_RT
> [1] "numeric"
>
> $Actual_net
> [1] "character"
>
> $Notes
> [1] "logical"
>
> $Test_20141231
> [1] "character"
>
> $Test_20151231
> [1] "character"
>
> I am struggling to understand why the query through the field Station_RT
does not work.
> Could please somebody help me to manage correctly the missing values? Is
the mistake somewhere else?
>
> Thank you
> Stefano Sofia
>
>
--
Sarah Goslee
http://www.functionaldiversity.org
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