Thank you David
Min. 1st Qu. Median Mean 3rd Qu. Max.
"1977-07-16" "1984-03-13" "1990-08-16" "1990-12-28" "1997-07-29" "2002-12-31"
WHP
From: David Winsemius [mailto:dwinsem...@comcast.net]
Sent: Thursday, July 12, 2018 11:29 AM
To: Bill Poling <bill.pol...@zelis.com>
Cc: r-help (r-help@r-project.org) <r-help@r-project.org>
Subject: Re: [R] Help with replace()
On Jul 12, 2018, at 8:17 AM, Bill Poling
<bill.pol...@zelis.com<mailto:bill.pol...@zelis.com>> wrote:
R version 3.5.1 (2018-07-02) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
Hi.
I have data set with day month year integers. I am creating a date column from
those using lubridate.
a hundred or so rows failed to parse.
The problem is April and September have day = 31.
paste(df1$year, df1$month, df1$day, sep = "-")
ymd(paste(df1$year, df1$month, df1$day, sep = "-"))#Warning message: 129 failed
to parse. As expected in tutorial
#The resulting Date vector can be added to df1 as a new column called date:
df1$date <- ymd(paste(df1$year, df1$month, df1$day, sep = "-"))#Same warning
head(df1)
sapply(df1$date,class) #"date"
summary(df1$date)
# Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
#"1977-07-16" "1984-03-12" "1990-07-22" "1990-12-15" "1997-07-29" "2002-12-31"
"129"
is_missing_date <- is.na(df1$date)
View(is_missing_date)
date_columns <- c("year", "month", "day")
missing_dates <- df1[is_missing_date, date_columns]
head(missing_dates)
# year month day
# 3144 2000 9 31
# 3817 2000 4 31
# 3818 2000 4 31
# 3819 2000 4 31
# 3820 2000 4 31
# 3856 2000 9 31
I am trying to replace those with 30.
Seems like a fairly straightforward application of "[<-" with a conditional
argument. (No need for tidyverse.)
missing_dates$day[ missing_dates$day==31 & ( missing_dates$month %in% c(4,9) )]
<- 30
missing_dates
year month day
3144 2000 9 30
3817 2000 4 30
3818 2000 4 30
3819 2000 4 30
3820 2000 4 30
3856 2000 9 30
Best;
David.
I am all over the map in Google looking for a fix, but haven't found one. I am
sure I have over complicated my attempts with ideas(below) from these and other
sites.
https://stackoverflow.com/questions/14737773/replacing-occurrences-of-a-number-in-multiple-columns-of-data-frame-with-another?noredirect=1&lq=1<https://stackoverflow.com/questions/14737773/replacing-occurrences-of-a-number-in-multiple-columns-of-data-frame-with-another?noredirect=1&lq=1>
https://www.rdocumentation.org/packages/base/versions/3.5.1/topics/replace<https://www.rdocumentation.org/packages/base/versions/3.5.1/topics/replace>
https://stackoverflow.com/questions/48714625/error-in-data-frame-unused-argument<https://stackoverflow.com/questions/48714625/error-in-data-frame-unused-argument>
The following are screwy attempts at this simple repair,
??mutate_if
??replace
is_missing_date <- is.na(df1$date)
View(is_missing_date)
date_columns <- c("year", "month", "day")
missing_dates <- df1[is_missing_date, date_columns]
head(missing_dates)
#year month day
# 3144 2000 9 31
# 3817 2000 4 31
# 3818 2000 4 31
# 3819 2000 4 31
# 3820 2000 4 31
# 3856 2000 9 31
#So need those months with 30 days that are 31 to be 30
View(missing_dates)
install.packages("dplyr")
library(dplyr)
View(missing_dates)
# ..those were the values you're going to replace
I thought this function from stackover would work, but get error when I try to
add filter
#https://stackoverflow.com/questions/14737773/replacing-occurrences-of-a-number-in-multiple-columns-of-data-frame-with-another?noredirect=1&lq=1<https://stackoverflow.com/questions/14737773/replacing-occurrences-of-a-number-in-multiple-columns-of-data-frame-with-another?noredirect=1&lq=1>
df.Rep <- function(.data_Frame, .search_Columns, .search_Value, .sub_Value){
.data_Frame[, .search_Columns] <- ifelse(.data_Frame[,
.search_Columns]==.search_Value,.sub_Value/.search_Value,1) * .data_Frame[,
.search_Columns]
return(.data_Frame)
}
df.Rep(missing_dates, 3, 31, 30)
#--So I should be able to apply this to the complete df1 data somehow?
head(df1)
df.Rep(df1, filter(month == c(4,9)), 31, 30)
#Error in month == c(4, 9) : comparison (1) is possible only for atomic and
list types
Other screwy attempts:
select(df1, month, day, year)
str(df1)
#'data.frame': 34786 obs. of 14 variables:
#To choose rows, use filter():
#mutate_if(df1, month =4,9), day = 30)
filter(df1, month == c(4,9), day == 31)
df1 %>%
group_by(month == c(4,9), day == 31) %>%
tally()
# 1 FALSE FALSE 31161
# 2 FALSE TRUE 576
# 3 TRUE FALSE 2981
# 4 TRUE TRUE 68
df1 %>%
mutate(day=replace(day, month == c(4,9), 30)) %>%
as.data.frame()
View(as.list(df1, month == 4))
View(df1, month == c(4,9), day == 31)
df1 %>%
group_by(month == c(4,9), day == 31) %>%
tally()
View(df1, month == c(4,9))
# df1 %>%
# group_by(month == c(4,9), day == 30) %>%
I know there is a simple solution and it is driving me mad that it eludes me,
despite being new to R.
Thank you for any advice.
WHP
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PLEASE do read the posting guide
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and provide commented, minimal, self-contained, reproducible code.
David Winsemius
Alameda, CA, USA
'Any technology distinguishable from magic is insufficiently advanced.' -Gehm's
Corollary to Clarke's Third Law
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and provide commented, minimal, self-contained, reproducible code.
