How to conver daily data over the period of 30 years to Monthly data for a multivariate series?
0
I have data frame as shown below:
str(Rainfall_Complete)
'data.frame': 8221 obs. of 18 variables:
$ Date : Date, format: "1985-04-29" "1985-04-30" "1985-05-01" ...
$ Month : Ord.factor w/ 12 levels "Jan"<"Feb"<"Mar"<..:
$ Season : Factor w/ 4 levels "Monsoon","PostMonsoon",..:.
$ Year : chr "1985" "1985" "1985" "1985" ...
$ Stn A : num 0 8.8 0 15 26.2 0 2.5 0 0 0 ...
$ Stn B : num 0 0 26 11 13.8 20 0.26 0 0 0 ...
$ Stn C : num 0.1 0 0 0 13.5 27 16 5 0 0 …
I want to convert the above daily time series to monthly time series
I want my data to look something like this
Year Month StnA StnB StnC……..
1985 Jan 150 100 120
1985 Feb 120 98 58
….
2010 Jan 200 100 87
2010 Feb 140 145 120
I tried the following, however it works only for univariate series
library(dplyr)
Monthly_rainfall <- Rainfall_Complete %>% group_by(Year,Month)%>% summarise()
Any help would be appreciated
r dplyr xts lubridate
asked Nov 21 '18 at 10:19
Vasker SharmaVasker Sharma
328
add a comment |
0
I have data frame as shown below:
str(Rainfall_Complete)
'data.frame': 8221 obs. of 18 variables:
$ Date : Date, format: "1985-04-29" "1985-04-30" "1985-05-01" ...
$ Month : Ord.factor w/ 12 levels "Jan"<"Feb"<"Mar"<..:
$ Season : Factor w/ 4 levels "Monsoon","PostMonsoon",..:.
$ Year : chr "1985" "1985" "1985" "1985" ...
$ Stn A : num 0 8.8 0 15 26.2 0 2.5 0 0 0 ...
$ Stn B : num 0 0 26 11 13.8 20 0.26 0 0 0 ...
$ Stn C : num 0.1 0 0 0 13.5 27 16 5 0 0 …
I want to convert the above daily time series to monthly time series
I want my data to look something like this
Year Month StnA StnB StnC……..
1985 Jan 150 100 120
1985 Feb 120 98 58
….
2010 Jan 200 100 87
2010 Feb 140 145 120
I tried the following, however it works only for univariate series
library(dplyr)
Monthly_rainfall <- Rainfall_Complete %>% group_by(Year,Month)%>% summarise()
Any help would be appreciated
r dplyr xts lubridate
asked Nov 21 '18 at 10:19
Vasker SharmaVasker Sharma
328
you need to convert year and month into proper date format 1st,later use your code you will be able to convert it
– Hunaidkhan
Nov 21 '18 at 10:23
If you want to usesummariseon multiple columns trysummarise_at. You'll be able to get thesumof multiple columns at the same time, based on your grouping.
– AntoniosK
Nov 21 '18 at 10:30
Maybepadr::thicken()could be of help.
– meriops
Nov 21 '18 at 11:16
Please take a look at how to make a reproducible example to make it easier to help
– camille
Nov 21 '18 at 14:46
add a comment |
0
0
0
0
I have data frame as shown below:
str(Rainfall_Complete)
'data.frame': 8221 obs. of 18 variables:
$ Date : Date, format: "1985-04-29" "1985-04-30" "1985-05-01" ...
$ Month : Ord.factor w/ 12 levels "Jan"<"Feb"<"Mar"<..:
$ Season : Factor w/ 4 levels "Monsoon","PostMonsoon",..:.
$ Year : chr "1985" "1985" "1985" "1985" ...
$ Stn A : num 0 8.8 0 15 26.2 0 2.5 0 0 0 ...
$ Stn B : num 0 0 26 11 13.8 20 0.26 0 0 0 ...
$ Stn C : num 0.1 0 0 0 13.5 27 16 5 0 0 …
I want to convert the above daily time series to monthly time series
I want my data to look something like this
Year Month StnA StnB StnC……..
1985 Jan 150 100 120
1985 Feb 120 98 58
….
2010 Jan 200 100 87
2010 Feb 140 145 120
I tried the following, however it works only for univariate series
library(dplyr)
Monthly_rainfall <- Rainfall_Complete %>% group_by(Year,Month)%>% summarise()
Any help would be appreciated
r dplyr xts lubridate
asked Nov 21 '18 at 10:19
Vasker SharmaVasker Sharma
328
I have data frame as shown below:
str(Rainfall_Complete)
'data.frame': 8221 obs. of 18 variables:
$ Date : Date, format: "1985-04-29" "1985-04-30" "1985-05-01" ...
$ Month : Ord.factor w/ 12 levels "Jan"<"Feb"<"Mar"<..:
$ Season : Factor w/ 4 levels "Monsoon","PostMonsoon",..:.
$ Year : chr "1985" "1985" "1985" "1985" ...
$ Stn A : num 0 8.8 0 15 26.2 0 2.5 0 0 0 ...
$ Stn B : num 0 0 26 11 13.8 20 0.26 0 0 0 ...
$ Stn C : num 0.1 0 0 0 13.5 27 16 5 0 0 …
I want to convert the above daily time series to monthly time series
I want my data to look something like this
Year Month StnA StnB StnC……..
1985 Jan 150 100 120
1985 Feb 120 98 58
….
2010 Jan 200 100 87
2010 Feb 140 145 120
I tried the following, however it works only for univariate series
library(dplyr)
Monthly_rainfall <- Rainfall_Complete %>% group_by(Year,Month)%>% summarise()
Any help would be appreciated
r dplyr xts lubridate
r dplyr xts lubridate
asked Nov 21 '18 at 10:19
Vasker SharmaVasker Sharma
328
asked Nov 21 '18 at 10:19
Vasker SharmaVasker Sharma
328
asked Nov 21 '18 at 10:19
Vasker SharmaVasker Sharma
328
asked Nov 21 '18 at 10:19
Vasker SharmaVasker Sharma
328
asked Nov 21 '18 at 10:19
Vasker SharmaVasker Sharma
328
328
you need to convert year and month into proper date format 1st,later use your code you will be able to convert it
– Hunaidkhan
Nov 21 '18 at 10:23
If you want to usesummariseon multiple columns trysummarise_at. You'll be able to get thesumof multiple columns at the same time, based on your grouping.
– AntoniosK
Nov 21 '18 at 10:30
Maybepadr::thicken()could be of help.
– meriops
Nov 21 '18 at 11:16
Please take a look at how to make a reproducible example to make it easier to help
– camille
Nov 21 '18 at 14:46
add a comment |
you need to convert year and month into proper date format 1st,later use your code you will be able to convert it
– Hunaidkhan
Nov 21 '18 at 10:23
If you want to usesummariseon multiple columns trysummarise_at. You'll be able to get thesumof multiple columns at the same time, based on your grouping.
– AntoniosK
Nov 21 '18 at 10:30
Maybepadr::thicken()could be of help.
– meriops
Nov 21 '18 at 11:16
Please take a look at how to make a reproducible example to make it easier to help
– camille
Nov 21 '18 at 14:46
you need to convert year and month into proper date format 1st,later use your code you will be able to convert it
– Hunaidkhan
Nov 21 '18 at 10:23
you need to convert year and month into proper date format 1st,later use your code you will be able to convert it
– Hunaidkhan
Nov 21 '18 at 10:23
If you want to use
summarise on multiple columns try summarise_at. You'll be able to get the sum of multiple columns at the same time, based on your grouping.– AntoniosK
Nov 21 '18 at 10:30
If you want to use
summarise on multiple columns try summarise_at. You'll be able to get the sum of multiple columns at the same time, based on your grouping.– AntoniosK
Nov 21 '18 at 10:30
Maybe
padr::thicken() could be of help.– meriops
Nov 21 '18 at 11:16
Maybe
padr::thicken() could be of help.– meriops
Nov 21 '18 at 11:16
Please take a look at how to make a reproducible example to make it easier to help
– camille
Nov 21 '18 at 14:46
Please take a look at how to make a reproducible example to make it easier to help
– camille
Nov 21 '18 at 14:46
add a comment |
1 Answer
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Your attempt uses dplyr, but the question is tagged with xts and lubridate, thus here is a solution using those packages with a reprex.
library(lubridate)
library(xts)
## Create some basic data
ans6 <- xts(anscombe[, 1:6], order.by = as.Date("2018-01-28") + 1:nrow(anscombe))
## Summary by month
mon6 <- apply.monthly(ans6, FUN = mean)
## Re-format
df6 <- as.data.frame(mon6)
df6$year <- year(rownames(df6))
df6$month <- month(rownames(df6), label = TRUE)
df6
## x1 x2 x3 x4 y1 y2 year month
## 2018-01-31 10.33333 10.33333 10.33333 8.000 7.523333 8.673333 2018 Jan
## 2018-02-08 8.50000 8.50000 8.50000 9.375 7.492500 7.061250 2018 Feb
answered Dec 12 '18 at 0:49
jmuhlenkampjmuhlenkamp
1,452525
add a comment |
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1 Answer
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1 Answer
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active
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Your attempt uses dplyr, but the question is tagged with xts and lubridate, thus here is a solution using those packages with a reprex.
library(lubridate)
library(xts)
## Create some basic data
ans6 <- xts(anscombe[, 1:6], order.by = as.Date("2018-01-28") + 1:nrow(anscombe))
## Summary by month
mon6 <- apply.monthly(ans6, FUN = mean)
## Re-format
df6 <- as.data.frame(mon6)
df6$year <- year(rownames(df6))
df6$month <- month(rownames(df6), label = TRUE)
df6
## x1 x2 x3 x4 y1 y2 year month
## 2018-01-31 10.33333 10.33333 10.33333 8.000 7.523333 8.673333 2018 Jan
## 2018-02-08 8.50000 8.50000 8.50000 9.375 7.492500 7.061250 2018 Feb
answered Dec 12 '18 at 0:49
jmuhlenkampjmuhlenkamp
1,452525
add a comment |
0
Your attempt uses dplyr, but the question is tagged with xts and lubridate, thus here is a solution using those packages with a reprex.
library(lubridate)
library(xts)
## Create some basic data
ans6 <- xts(anscombe[, 1:6], order.by = as.Date("2018-01-28") + 1:nrow(anscombe))
## Summary by month
mon6 <- apply.monthly(ans6, FUN = mean)
## Re-format
df6 <- as.data.frame(mon6)
df6$year <- year(rownames(df6))
df6$month <- month(rownames(df6), label = TRUE)
df6
## x1 x2 x3 x4 y1 y2 year month
## 2018-01-31 10.33333 10.33333 10.33333 8.000 7.523333 8.673333 2018 Jan
## 2018-02-08 8.50000 8.50000 8.50000 9.375 7.492500 7.061250 2018 Feb
answered Dec 12 '18 at 0:49
jmuhlenkampjmuhlenkamp
1,452525
add a comment |
0
0
0
Your attempt uses dplyr, but the question is tagged with xts and lubridate, thus here is a solution using those packages with a reprex.
library(lubridate)
library(xts)
## Create some basic data
ans6 <- xts(anscombe[, 1:6], order.by = as.Date("2018-01-28") + 1:nrow(anscombe))
## Summary by month
mon6 <- apply.monthly(ans6, FUN = mean)
## Re-format
df6 <- as.data.frame(mon6)
df6$year <- year(rownames(df6))
df6$month <- month(rownames(df6), label = TRUE)
df6
## x1 x2 x3 x4 y1 y2 year month
## 2018-01-31 10.33333 10.33333 10.33333 8.000 7.523333 8.673333 2018 Jan
## 2018-02-08 8.50000 8.50000 8.50000 9.375 7.492500 7.061250 2018 Feb
answered Dec 12 '18 at 0:49
jmuhlenkampjmuhlenkamp
1,452525
Your attempt uses dplyr, but the question is tagged with xts and lubridate, thus here is a solution using those packages with a reprex.
library(lubridate)
library(xts)
## Create some basic data
ans6 <- xts(anscombe[, 1:6], order.by = as.Date("2018-01-28") + 1:nrow(anscombe))
## Summary by month
mon6 <- apply.monthly(ans6, FUN = mean)
## Re-format
df6 <- as.data.frame(mon6)
df6$year <- year(rownames(df6))
df6$month <- month(rownames(df6), label = TRUE)
df6
## x1 x2 x3 x4 y1 y2 year month
## 2018-01-31 10.33333 10.33333 10.33333 8.000 7.523333 8.673333 2018 Jan
## 2018-02-08 8.50000 8.50000 8.50000 9.375 7.492500 7.061250 2018 Feb
answered Dec 12 '18 at 0:49
jmuhlenkampjmuhlenkamp
1,452525
answered Dec 12 '18 at 0:49
jmuhlenkampjmuhlenkamp
1,452525
answered Dec 12 '18 at 0:49
jmuhlenkampjmuhlenkamp
1,452525
answered Dec 12 '18 at 0:49
jmuhlenkampjmuhlenkamp
1,452525
1,452525
add a comment |
add a comment |
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you need to convert year and month into proper date format 1st,later use your code you will be able to convert it
– Hunaidkhan
Nov 21 '18 at 10:23
If you want to use
summariseon multiple columns trysummarise_at. You'll be able to get thesumof multiple columns at the same time, based on your grouping.– AntoniosK
Nov 21 '18 at 10:30
Maybe
padr::thicken()could be of help.– meriops
Nov 21 '18 at 11:16
Please take a look at how to make a reproducible example to make it easier to help
– camille
Nov 21 '18 at 14:46