How to fill missing data according to the date previous and next to it in R?










1















Two more questions about this topic:
A
B



Take Fig.1 as an example, we can see that data in 10/12/2016 12:07 is missing. I want to use the previous and next row of data (i.e., 10/10/2016 10:50 5.73; 10/24/2016 08:53 6.09) to linear interpolate this missing data (not the mean value of "5.73" and "6.09", but
according to the "date"). The example data file is attached below:



09/26/2016 11:57 5.42
10/10/2016 10:50 5.73
10/12/2016 12:07
10/24/2016 08:53 6.09
11/07/2016 11:25 6.43
11/21/2016 13:57 6.33
12/05/2016 14:01 7.97
12/19/2016 13:00 8.47


You can see Fig.2, we can use "Trend()" to attain this goal.



=TREND(M22:M23,L22:L23,O22)


I was wondering if there is a useful function as well in R?



Fig-1Fig-2










share|improve this question
























  • Pls post data no pictures! Check out ?dput.

    – vaettchen
    Nov 14 '18 at 4:02











  • You could do a weighted average, so if the previous date is closer to the missing date it's weighted more.

    – mickey
    Nov 14 '18 at 4:03











  • Have a look at difftime. Then you can get two time differences: "before and missing" and "missing and after". The value you can interpolate by "value before" + "value after" * diff1 / (diff1 + diff2)

    – CIAndrews
    Nov 14 '18 at 5:05











  • I'm so sorry I didn't post data. I have uploaded it.@vaettchen

    – T X
    Nov 14 '18 at 7:33











  • Thanks!@CIAndrews. Yet I'am afraid your equation should be: "value before" + "value after - value before" * diff1 / (diff1 + diff2)

    – T X
    Nov 14 '18 at 7:53















1















Two more questions about this topic:
A
B



Take Fig.1 as an example, we can see that data in 10/12/2016 12:07 is missing. I want to use the previous and next row of data (i.e., 10/10/2016 10:50 5.73; 10/24/2016 08:53 6.09) to linear interpolate this missing data (not the mean value of "5.73" and "6.09", but
according to the "date"). The example data file is attached below:



09/26/2016 11:57 5.42
10/10/2016 10:50 5.73
10/12/2016 12:07
10/24/2016 08:53 6.09
11/07/2016 11:25 6.43
11/21/2016 13:57 6.33
12/05/2016 14:01 7.97
12/19/2016 13:00 8.47


You can see Fig.2, we can use "Trend()" to attain this goal.



=TREND(M22:M23,L22:L23,O22)


I was wondering if there is a useful function as well in R?



Fig-1Fig-2










share|improve this question
























  • Pls post data no pictures! Check out ?dput.

    – vaettchen
    Nov 14 '18 at 4:02











  • You could do a weighted average, so if the previous date is closer to the missing date it's weighted more.

    – mickey
    Nov 14 '18 at 4:03











  • Have a look at difftime. Then you can get two time differences: "before and missing" and "missing and after". The value you can interpolate by "value before" + "value after" * diff1 / (diff1 + diff2)

    – CIAndrews
    Nov 14 '18 at 5:05











  • I'm so sorry I didn't post data. I have uploaded it.@vaettchen

    – T X
    Nov 14 '18 at 7:33











  • Thanks!@CIAndrews. Yet I'am afraid your equation should be: "value before" + "value after - value before" * diff1 / (diff1 + diff2)

    – T X
    Nov 14 '18 at 7:53













1












1








1








Two more questions about this topic:
A
B



Take Fig.1 as an example, we can see that data in 10/12/2016 12:07 is missing. I want to use the previous and next row of data (i.e., 10/10/2016 10:50 5.73; 10/24/2016 08:53 6.09) to linear interpolate this missing data (not the mean value of "5.73" and "6.09", but
according to the "date"). The example data file is attached below:



09/26/2016 11:57 5.42
10/10/2016 10:50 5.73
10/12/2016 12:07
10/24/2016 08:53 6.09
11/07/2016 11:25 6.43
11/21/2016 13:57 6.33
12/05/2016 14:01 7.97
12/19/2016 13:00 8.47


You can see Fig.2, we can use "Trend()" to attain this goal.



=TREND(M22:M23,L22:L23,O22)


I was wondering if there is a useful function as well in R?



Fig-1Fig-2










share|improve this question
















Two more questions about this topic:
A
B



Take Fig.1 as an example, we can see that data in 10/12/2016 12:07 is missing. I want to use the previous and next row of data (i.e., 10/10/2016 10:50 5.73; 10/24/2016 08:53 6.09) to linear interpolate this missing data (not the mean value of "5.73" and "6.09", but
according to the "date"). The example data file is attached below:



09/26/2016 11:57 5.42
10/10/2016 10:50 5.73
10/12/2016 12:07
10/24/2016 08:53 6.09
11/07/2016 11:25 6.43
11/21/2016 13:57 6.33
12/05/2016 14:01 7.97
12/19/2016 13:00 8.47


You can see Fig.2, we can use "Trend()" to attain this goal.



=TREND(M22:M23,L22:L23,O22)


I was wondering if there is a useful function as well in R?



Fig-1Fig-2







r datetime






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 15 '18 at 7:25









zx8754

30.1k763100




30.1k763100










asked Nov 14 '18 at 3:41









T XT X

106116




106116












  • Pls post data no pictures! Check out ?dput.

    – vaettchen
    Nov 14 '18 at 4:02











  • You could do a weighted average, so if the previous date is closer to the missing date it's weighted more.

    – mickey
    Nov 14 '18 at 4:03











  • Have a look at difftime. Then you can get two time differences: "before and missing" and "missing and after". The value you can interpolate by "value before" + "value after" * diff1 / (diff1 + diff2)

    – CIAndrews
    Nov 14 '18 at 5:05











  • I'm so sorry I didn't post data. I have uploaded it.@vaettchen

    – T X
    Nov 14 '18 at 7:33











  • Thanks!@CIAndrews. Yet I'am afraid your equation should be: "value before" + "value after - value before" * diff1 / (diff1 + diff2)

    – T X
    Nov 14 '18 at 7:53

















  • Pls post data no pictures! Check out ?dput.

    – vaettchen
    Nov 14 '18 at 4:02











  • You could do a weighted average, so if the previous date is closer to the missing date it's weighted more.

    – mickey
    Nov 14 '18 at 4:03











  • Have a look at difftime. Then you can get two time differences: "before and missing" and "missing and after". The value you can interpolate by "value before" + "value after" * diff1 / (diff1 + diff2)

    – CIAndrews
    Nov 14 '18 at 5:05











  • I'm so sorry I didn't post data. I have uploaded it.@vaettchen

    – T X
    Nov 14 '18 at 7:33











  • Thanks!@CIAndrews. Yet I'am afraid your equation should be: "value before" + "value after - value before" * diff1 / (diff1 + diff2)

    – T X
    Nov 14 '18 at 7:53
















Pls post data no pictures! Check out ?dput.

– vaettchen
Nov 14 '18 at 4:02





Pls post data no pictures! Check out ?dput.

– vaettchen
Nov 14 '18 at 4:02













You could do a weighted average, so if the previous date is closer to the missing date it's weighted more.

– mickey
Nov 14 '18 at 4:03





You could do a weighted average, so if the previous date is closer to the missing date it's weighted more.

– mickey
Nov 14 '18 at 4:03













Have a look at difftime. Then you can get two time differences: "before and missing" and "missing and after". The value you can interpolate by "value before" + "value after" * diff1 / (diff1 + diff2)

– CIAndrews
Nov 14 '18 at 5:05





Have a look at difftime. Then you can get two time differences: "before and missing" and "missing and after". The value you can interpolate by "value before" + "value after" * diff1 / (diff1 + diff2)

– CIAndrews
Nov 14 '18 at 5:05













I'm so sorry I didn't post data. I have uploaded it.@vaettchen

– T X
Nov 14 '18 at 7:33





I'm so sorry I didn't post data. I have uploaded it.@vaettchen

– T X
Nov 14 '18 at 7:33













Thanks!@CIAndrews. Yet I'am afraid your equation should be: "value before" + "value after - value before" * diff1 / (diff1 + diff2)

– T X
Nov 14 '18 at 7:53





Thanks!@CIAndrews. Yet I'am afraid your equation should be: "value before" + "value after - value before" * diff1 / (diff1 + diff2)

– T X
Nov 14 '18 at 7:53












1 Answer
1






active

oldest

votes


















2














Example data:



df <- data.frame(date = mdy_hm(
c("10/10/2016 10:50",
"10/12/2016 12:07",
"10/24/2016 08:53")),
figure = c(5.73, NA_real_, 6.09))


Using the zoo package:



library(zoo) 
library(magrittr)

zoo(df$figure, df$date) %>%
na.approx() %>%
as.data.frame()


Using lubridate and dplyr



library(dplyr)
library(lubridate)

df %>%
mutate(figure = ifelse(is.na(figure),
lag(figure, 1) + (lead(figure, 1) - lag(figure, 1)) *
as.numeric(difftime(date, lag(date, 1))) /
as.numeric((difftime(lead(date, 1), date) + difftime(date, lag(date, 1)))),
figure)) %>%
mutate(figure = round(figure, 2))





share|improve this answer

























  • Appreciate it. I tried your code, and the result is "13.92" for "2016-10-12 12:07:00". However, I think this value may be wrong. Because what I want to fill is like CIAndrews says in Comments. So the result should be "5.78". You can see my edited question, I have changed it with an example in Excel.

    – T X
    Nov 14 '18 at 8:00











  • Updated following your comment.

    – Jay Achar
    Nov 14 '18 at 8:46











  • I was wondering if you could see the question (stackoverflow.com/questions/53302125/…) when you have time. This extra question is another 50% part of the whole "missing data" problem.

    – T X
    Nov 14 '18 at 14:11










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1 Answer
1






active

oldest

votes








1 Answer
1






active

oldest

votes









active

oldest

votes






active

oldest

votes









2














Example data:



df <- data.frame(date = mdy_hm(
c("10/10/2016 10:50",
"10/12/2016 12:07",
"10/24/2016 08:53")),
figure = c(5.73, NA_real_, 6.09))


Using the zoo package:



library(zoo) 
library(magrittr)

zoo(df$figure, df$date) %>%
na.approx() %>%
as.data.frame()


Using lubridate and dplyr



library(dplyr)
library(lubridate)

df %>%
mutate(figure = ifelse(is.na(figure),
lag(figure, 1) + (lead(figure, 1) - lag(figure, 1)) *
as.numeric(difftime(date, lag(date, 1))) /
as.numeric((difftime(lead(date, 1), date) + difftime(date, lag(date, 1)))),
figure)) %>%
mutate(figure = round(figure, 2))





share|improve this answer

























  • Appreciate it. I tried your code, and the result is "13.92" for "2016-10-12 12:07:00". However, I think this value may be wrong. Because what I want to fill is like CIAndrews says in Comments. So the result should be "5.78". You can see my edited question, I have changed it with an example in Excel.

    – T X
    Nov 14 '18 at 8:00











  • Updated following your comment.

    – Jay Achar
    Nov 14 '18 at 8:46











  • I was wondering if you could see the question (stackoverflow.com/questions/53302125/…) when you have time. This extra question is another 50% part of the whole "missing data" problem.

    – T X
    Nov 14 '18 at 14:11















2














Example data:



df <- data.frame(date = mdy_hm(
c("10/10/2016 10:50",
"10/12/2016 12:07",
"10/24/2016 08:53")),
figure = c(5.73, NA_real_, 6.09))


Using the zoo package:



library(zoo) 
library(magrittr)

zoo(df$figure, df$date) %>%
na.approx() %>%
as.data.frame()


Using lubridate and dplyr



library(dplyr)
library(lubridate)

df %>%
mutate(figure = ifelse(is.na(figure),
lag(figure, 1) + (lead(figure, 1) - lag(figure, 1)) *
as.numeric(difftime(date, lag(date, 1))) /
as.numeric((difftime(lead(date, 1), date) + difftime(date, lag(date, 1)))),
figure)) %>%
mutate(figure = round(figure, 2))





share|improve this answer

























  • Appreciate it. I tried your code, and the result is "13.92" for "2016-10-12 12:07:00". However, I think this value may be wrong. Because what I want to fill is like CIAndrews says in Comments. So the result should be "5.78". You can see my edited question, I have changed it with an example in Excel.

    – T X
    Nov 14 '18 at 8:00











  • Updated following your comment.

    – Jay Achar
    Nov 14 '18 at 8:46











  • I was wondering if you could see the question (stackoverflow.com/questions/53302125/…) when you have time. This extra question is another 50% part of the whole "missing data" problem.

    – T X
    Nov 14 '18 at 14:11













2












2








2







Example data:



df <- data.frame(date = mdy_hm(
c("10/10/2016 10:50",
"10/12/2016 12:07",
"10/24/2016 08:53")),
figure = c(5.73, NA_real_, 6.09))


Using the zoo package:



library(zoo) 
library(magrittr)

zoo(df$figure, df$date) %>%
na.approx() %>%
as.data.frame()


Using lubridate and dplyr



library(dplyr)
library(lubridate)

df %>%
mutate(figure = ifelse(is.na(figure),
lag(figure, 1) + (lead(figure, 1) - lag(figure, 1)) *
as.numeric(difftime(date, lag(date, 1))) /
as.numeric((difftime(lead(date, 1), date) + difftime(date, lag(date, 1)))),
figure)) %>%
mutate(figure = round(figure, 2))





share|improve this answer















Example data:



df <- data.frame(date = mdy_hm(
c("10/10/2016 10:50",
"10/12/2016 12:07",
"10/24/2016 08:53")),
figure = c(5.73, NA_real_, 6.09))


Using the zoo package:



library(zoo) 
library(magrittr)

zoo(df$figure, df$date) %>%
na.approx() %>%
as.data.frame()


Using lubridate and dplyr



library(dplyr)
library(lubridate)

df %>%
mutate(figure = ifelse(is.na(figure),
lag(figure, 1) + (lead(figure, 1) - lag(figure, 1)) *
as.numeric(difftime(date, lag(date, 1))) /
as.numeric((difftime(lead(date, 1), date) + difftime(date, lag(date, 1)))),
figure)) %>%
mutate(figure = round(figure, 2))






share|improve this answer














share|improve this answer



share|improve this answer








edited Nov 14 '18 at 10:21

























answered Nov 14 '18 at 6:53









Jay AcharJay Achar

1357




1357












  • Appreciate it. I tried your code, and the result is "13.92" for "2016-10-12 12:07:00". However, I think this value may be wrong. Because what I want to fill is like CIAndrews says in Comments. So the result should be "5.78". You can see my edited question, I have changed it with an example in Excel.

    – T X
    Nov 14 '18 at 8:00











  • Updated following your comment.

    – Jay Achar
    Nov 14 '18 at 8:46











  • I was wondering if you could see the question (stackoverflow.com/questions/53302125/…) when you have time. This extra question is another 50% part of the whole "missing data" problem.

    – T X
    Nov 14 '18 at 14:11

















  • Appreciate it. I tried your code, and the result is "13.92" for "2016-10-12 12:07:00". However, I think this value may be wrong. Because what I want to fill is like CIAndrews says in Comments. So the result should be "5.78". You can see my edited question, I have changed it with an example in Excel.

    – T X
    Nov 14 '18 at 8:00











  • Updated following your comment.

    – Jay Achar
    Nov 14 '18 at 8:46











  • I was wondering if you could see the question (stackoverflow.com/questions/53302125/…) when you have time. This extra question is another 50% part of the whole "missing data" problem.

    – T X
    Nov 14 '18 at 14:11
















Appreciate it. I tried your code, and the result is "13.92" for "2016-10-12 12:07:00". However, I think this value may be wrong. Because what I want to fill is like CIAndrews says in Comments. So the result should be "5.78". You can see my edited question, I have changed it with an example in Excel.

– T X
Nov 14 '18 at 8:00





Appreciate it. I tried your code, and the result is "13.92" for "2016-10-12 12:07:00". However, I think this value may be wrong. Because what I want to fill is like CIAndrews says in Comments. So the result should be "5.78". You can see my edited question, I have changed it with an example in Excel.

– T X
Nov 14 '18 at 8:00













Updated following your comment.

– Jay Achar
Nov 14 '18 at 8:46





Updated following your comment.

– Jay Achar
Nov 14 '18 at 8:46













I was wondering if you could see the question (stackoverflow.com/questions/53302125/…) when you have time. This extra question is another 50% part of the whole "missing data" problem.

– T X
Nov 14 '18 at 14:11





I was wondering if you could see the question (stackoverflow.com/questions/53302125/…) when you have time. This extra question is another 50% part of the whole "missing data" problem.

– T X
Nov 14 '18 at 14:11



















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