Unnest a ts class

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0
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My data has multiple customers data with different start and end dates along with their sales data.So I did simple exponential smoothing.
My data set :

structure(list(customer_id = c("1-FI", "1-FI", "1-FI", "1-FI", 

"1-FI", "1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", 

"1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", 

"1-G0175", "1-G0175", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188"), sales = c(100.9418694, 121.80921729, 

131.13242701, 129.25146751, 130.9114891, 59.862175475, 26.242577152, 

26.242583584, 26.242582726, 26.242605024, 26.243207488, 26.244399981, 

26.24368903, 26.242590016, 26.242607168, 26.244073664, 26.242733235, 

26.252639373, 382.25686237, 383.5729855, 395.04823051, 410.71253335, 

380.97085, 415.60929042, 405.40406353, 389.73811453, 422.75106934, 

424.95123013, 396.27195067, 397.22035121, 403.07871072, 390.51585696, 

387.14589889, 356.47379073, 409.86190435, 362.1045076, 482.70803877, 

401.04191501, 396.80578737, 182.69071425, 182.90770549, 156.78630936, 

162.01545504, 154.59593421, 149.63253734, 183.18470086, 196.32791655, 

183.93584654, 186.03057785, 186.22590654, 156.09019587, 137.76343138, 

127.0869966, 137.34694566, 133.25311402, 122.55553768, 118.22456292, 

159.65747998, 122.77510258, 157.04492207, 35.161096589, 45.037465606, 

37.637919142, 35.049382182, 32.801385318, 39.203592294, 37.741972608, 

38.730897325, 72.049982746, 40.391500365, 41.502300762, 38.760239251, 

40.77839417, 36.989308973, 40.167455795, 33.865745389, 43.924857389, 

39.943200256, 38.908906355, 32.228421472, 40.341142093, 47.464460314, 

50.49858951, 57.964360275, 50.21179049, 60.817118221, 54.677239507, 

53.517382246, 51.296274573, 89.214368205, 51.205341958, 45.581040358, 

48.318404365, 56.420713722, 50.733345075, 47.746574266, 51.449188512, 

53.159378413, 51.672878035, 54.984310906, 49.853546957, 54.635080749, 

33.869158637, 36.420494624, 34.201671168, 31.169316346, 31.453926771, 

30.995599174, 34.941078022, 36.430641747, 72.9296608, 44.5318984, 

51.272563219, 40.981600774, 41.276944922, 34.307531597, 34.856211642, 

35.116862867, 53.886082496, 32.843276934, 67.787450893, 64.072083277, 

67.164756966, 37.15244679, 41.802139162, 45.057952384, 41.183183085, 

40.94067696, 44.759495578, 45.310676813, 42.227278496, 77.741274912, 

45.850713107, 37.290041421, 39.694496685, 43.410913574, 35.870854496, 

39.492859059, 39.508746528, 35.526071853, 30.332660653, 30.208349818, 

30.188126323, 33.049433254), Date = structure(c(17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727, 17587, 17594, 17601, 

17608, 17615, 17622, 17629, 17636, 17643, 17650, 17657, 17664, 

17671, 17678, 17685, 17692, 17699, 17706, 17713, 17720, 17727, 

17587, 17594, 17601, 17608, 17615, 17622, 17629, 17636, 17643, 

17650, 17657, 17664, 17671, 17678, 17685, 17692, 17699, 17706, 

17713, 17720, 17727, 17587, 17594, 17601, 17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727, 17587, 17594, 17601, 

17608, 17615, 17622, 17629, 17636, 17643, 17650, 17657, 17664, 

17671, 17678, 17685, 17692, 17699, 17706, 17713, 17720, 17727, 

17587, 17594, 17601, 17608, 17615, 17622, 17629, 17636, 17643, 

17650, 17657, 17664, 17671, 17678, 17685, 17692, 17699, 17706, 

17713, 17720, 17727, 17587, 17594, 17601, 17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727), class = "Date")), row.names = c(NA, 

144L), class = "data.frame")

and I applied the following code to apply ses

library(zoo)

library(forecast)



z <- read.zoo(data_set,FUN = function(x) as.Date(x) + seq_along(x) / 10^10 , index = "Date", split = "customer_id")

L <- lapply(as.list(z), function(x) ts(na.omit(x),frequency = 52))

HW <- lapply(L, ses)

Now my output class is list with uneven lengths.Can someone help me how to unnest or unlist the output in to a data frame and get the fitted values,actuals,residuals along with their dates,sales and customer_id.
Note : the reson I post my input data rather than data of HW is,the HW data is too large.
Can someone help me in R.

edited Nov 19 at 16:00

asked Nov 19 at 15:52

riyan

106

Please be clear, are you using forecast::ses?
– r2evans
Nov 19 at 15:58

1

Yes@r2evans and edited my question.Thanks!
– riyan
Nov 19 at 16:00

@G.Grothendieck I tried your method but it showed me like columns names like Point Forecast , Lo 80, Hi 80 basically it showed me the intervals other than the fitted values and actual values which we can see in dput(HW) or view of HW.
– riyan
Nov 19 at 17:30

In order to unlist your output, you need to convert each element from class forecast to data.frame, and then you can bind the list elements together using bind_rows from package dplyr
– Giorgi Chighladze
Nov 19 at 21:40

add a comment |

up vote
0
down vote

favorite

My data has multiple customers data with different start and end dates along with their sales data.So I did simple exponential smoothing.
My data set :

structure(list(customer_id = c("1-FI", "1-FI", "1-FI", "1-FI", 

"1-FI", "1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", 

"1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", 

"1-G0175", "1-G0175", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188"), sales = c(100.9418694, 121.80921729, 

131.13242701, 129.25146751, 130.9114891, 59.862175475, 26.242577152, 

26.242583584, 26.242582726, 26.242605024, 26.243207488, 26.244399981, 

26.24368903, 26.242590016, 26.242607168, 26.244073664, 26.242733235, 

26.252639373, 382.25686237, 383.5729855, 395.04823051, 410.71253335, 

380.97085, 415.60929042, 405.40406353, 389.73811453, 422.75106934, 

424.95123013, 396.27195067, 397.22035121, 403.07871072, 390.51585696, 

387.14589889, 356.47379073, 409.86190435, 362.1045076, 482.70803877, 

401.04191501, 396.80578737, 182.69071425, 182.90770549, 156.78630936, 

162.01545504, 154.59593421, 149.63253734, 183.18470086, 196.32791655, 

183.93584654, 186.03057785, 186.22590654, 156.09019587, 137.76343138, 

127.0869966, 137.34694566, 133.25311402, 122.55553768, 118.22456292, 

159.65747998, 122.77510258, 157.04492207, 35.161096589, 45.037465606, 

37.637919142, 35.049382182, 32.801385318, 39.203592294, 37.741972608, 

38.730897325, 72.049982746, 40.391500365, 41.502300762, 38.760239251, 

40.77839417, 36.989308973, 40.167455795, 33.865745389, 43.924857389, 

39.943200256, 38.908906355, 32.228421472, 40.341142093, 47.464460314, 

50.49858951, 57.964360275, 50.21179049, 60.817118221, 54.677239507, 

53.517382246, 51.296274573, 89.214368205, 51.205341958, 45.581040358, 

48.318404365, 56.420713722, 50.733345075, 47.746574266, 51.449188512, 

53.159378413, 51.672878035, 54.984310906, 49.853546957, 54.635080749, 

33.869158637, 36.420494624, 34.201671168, 31.169316346, 31.453926771, 

30.995599174, 34.941078022, 36.430641747, 72.9296608, 44.5318984, 

51.272563219, 40.981600774, 41.276944922, 34.307531597, 34.856211642, 

35.116862867, 53.886082496, 32.843276934, 67.787450893, 64.072083277, 

67.164756966, 37.15244679, 41.802139162, 45.057952384, 41.183183085, 

40.94067696, 44.759495578, 45.310676813, 42.227278496, 77.741274912, 

45.850713107, 37.290041421, 39.694496685, 43.410913574, 35.870854496, 

39.492859059, 39.508746528, 35.526071853, 30.332660653, 30.208349818, 

30.188126323, 33.049433254), Date = structure(c(17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727, 17587, 17594, 17601, 

17608, 17615, 17622, 17629, 17636, 17643, 17650, 17657, 17664, 

17671, 17678, 17685, 17692, 17699, 17706, 17713, 17720, 17727, 

17587, 17594, 17601, 17608, 17615, 17622, 17629, 17636, 17643, 

17650, 17657, 17664, 17671, 17678, 17685, 17692, 17699, 17706, 

17713, 17720, 17727, 17587, 17594, 17601, 17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727, 17587, 17594, 17601, 

17608, 17615, 17622, 17629, 17636, 17643, 17650, 17657, 17664, 

17671, 17678, 17685, 17692, 17699, 17706, 17713, 17720, 17727, 

17587, 17594, 17601, 17608, 17615, 17622, 17629, 17636, 17643, 

17650, 17657, 17664, 17671, 17678, 17685, 17692, 17699, 17706, 

17713, 17720, 17727, 17587, 17594, 17601, 17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727), class = "Date")), row.names = c(NA, 

144L), class = "data.frame")

and I applied the following code to apply ses

library(zoo)

library(forecast)



z <- read.zoo(data_set,FUN = function(x) as.Date(x) + seq_along(x) / 10^10 , index = "Date", split = "customer_id")

L <- lapply(as.list(z), function(x) ts(na.omit(x),frequency = 52))

HW <- lapply(L, ses)

edited Nov 19 at 16:00

asked Nov 19 at 15:52

riyan

106

Please be clear, are you using forecast::ses?
– r2evans
Nov 19 at 15:58

1

Yes@r2evans and edited my question.Thanks!
– riyan
Nov 19 at 16:00

@G.Grothendieck I tried your method but it showed me like columns names like Point Forecast , Lo 80, Hi 80 basically it showed me the intervals other than the fitted values and actual values which we can see in dput(HW) or view of HW.
– riyan
Nov 19 at 17:30

In order to unlist your output, you need to convert each element from class forecast to data.frame, and then you can bind the list elements together using bind_rows from package dplyr
– Giorgi Chighladze
Nov 19 at 21:40

add a comment |

up vote
0
down vote

favorite

My data has multiple customers data with different start and end dates along with their sales data.So I did simple exponential smoothing.
My data set :

structure(list(customer_id = c("1-FI", "1-FI", "1-FI", "1-FI", 

"1-FI", "1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", 

"1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", 

"1-G0175", "1-G0175", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188"), sales = c(100.9418694, 121.80921729, 

131.13242701, 129.25146751, 130.9114891, 59.862175475, 26.242577152, 

26.242583584, 26.242582726, 26.242605024, 26.243207488, 26.244399981, 

26.24368903, 26.242590016, 26.242607168, 26.244073664, 26.242733235, 

26.252639373, 382.25686237, 383.5729855, 395.04823051, 410.71253335, 

380.97085, 415.60929042, 405.40406353, 389.73811453, 422.75106934, 

424.95123013, 396.27195067, 397.22035121, 403.07871072, 390.51585696, 

387.14589889, 356.47379073, 409.86190435, 362.1045076, 482.70803877, 

401.04191501, 396.80578737, 182.69071425, 182.90770549, 156.78630936, 

162.01545504, 154.59593421, 149.63253734, 183.18470086, 196.32791655, 

183.93584654, 186.03057785, 186.22590654, 156.09019587, 137.76343138, 

127.0869966, 137.34694566, 133.25311402, 122.55553768, 118.22456292, 

159.65747998, 122.77510258, 157.04492207, 35.161096589, 45.037465606, 

37.637919142, 35.049382182, 32.801385318, 39.203592294, 37.741972608, 

38.730897325, 72.049982746, 40.391500365, 41.502300762, 38.760239251, 

40.77839417, 36.989308973, 40.167455795, 33.865745389, 43.924857389, 

39.943200256, 38.908906355, 32.228421472, 40.341142093, 47.464460314, 

50.49858951, 57.964360275, 50.21179049, 60.817118221, 54.677239507, 

53.517382246, 51.296274573, 89.214368205, 51.205341958, 45.581040358, 

48.318404365, 56.420713722, 50.733345075, 47.746574266, 51.449188512, 

53.159378413, 51.672878035, 54.984310906, 49.853546957, 54.635080749, 

33.869158637, 36.420494624, 34.201671168, 31.169316346, 31.453926771, 

30.995599174, 34.941078022, 36.430641747, 72.9296608, 44.5318984, 

51.272563219, 40.981600774, 41.276944922, 34.307531597, 34.856211642, 

35.116862867, 53.886082496, 32.843276934, 67.787450893, 64.072083277, 

67.164756966, 37.15244679, 41.802139162, 45.057952384, 41.183183085, 

40.94067696, 44.759495578, 45.310676813, 42.227278496, 77.741274912, 

45.850713107, 37.290041421, 39.694496685, 43.410913574, 35.870854496, 

39.492859059, 39.508746528, 35.526071853, 30.332660653, 30.208349818, 

30.188126323, 33.049433254), Date = structure(c(17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727, 17587, 17594, 17601, 

17608, 17615, 17622, 17629, 17636, 17643, 17650, 17657, 17664, 

17671, 17678, 17685, 17692, 17699, 17706, 17713, 17720, 17727, 

17587, 17594, 17601, 17608, 17615, 17622, 17629, 17636, 17643, 

17650, 17657, 17664, 17671, 17678, 17685, 17692, 17699, 17706, 

17713, 17720, 17727, 17587, 17594, 17601, 17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727, 17587, 17594, 17601, 

17608, 17615, 17622, 17629, 17636, 17643, 17650, 17657, 17664, 

17671, 17678, 17685, 17692, 17699, 17706, 17713, 17720, 17727, 

17587, 17594, 17601, 17608, 17615, 17622, 17629, 17636, 17643, 

17650, 17657, 17664, 17671, 17678, 17685, 17692, 17699, 17706, 

17713, 17720, 17727, 17587, 17594, 17601, 17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727), class = "Date")), row.names = c(NA, 

144L), class = "data.frame")

and I applied the following code to apply ses

library(zoo)

library(forecast)



z <- read.zoo(data_set,FUN = function(x) as.Date(x) + seq_along(x) / 10^10 , index = "Date", split = "customer_id")

L <- lapply(as.list(z), function(x) ts(na.omit(x),frequency = 52))

HW <- lapply(L, ses)

edited Nov 19 at 16:00

asked Nov 19 at 15:52

riyan

106

My data has multiple customers data with different start and end dates along with their sales data.So I did simple exponential smoothing.
My data set :

structure(list(customer_id = c("1-FI", "1-FI", "1-FI", "1-FI", 

"1-FI", "1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", 

"1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", "1-G0175", 

"1-G0175", "1-G0175", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", 

"1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0182", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", "1-H0183", 

"1-H0183", "1-H0183", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", 

"1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0184", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", "1-H0185", 

"1-H0185", "1-H0185", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", 

"1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0186", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", "1-H0188", 

"1-H0188", "1-H0188"), sales = c(100.9418694, 121.80921729, 

131.13242701, 129.25146751, 130.9114891, 59.862175475, 26.242577152, 

26.242583584, 26.242582726, 26.242605024, 26.243207488, 26.244399981, 

26.24368903, 26.242590016, 26.242607168, 26.244073664, 26.242733235, 

26.252639373, 382.25686237, 383.5729855, 395.04823051, 410.71253335, 

380.97085, 415.60929042, 405.40406353, 389.73811453, 422.75106934, 

424.95123013, 396.27195067, 397.22035121, 403.07871072, 390.51585696, 

387.14589889, 356.47379073, 409.86190435, 362.1045076, 482.70803877, 

401.04191501, 396.80578737, 182.69071425, 182.90770549, 156.78630936, 

162.01545504, 154.59593421, 149.63253734, 183.18470086, 196.32791655, 

183.93584654, 186.03057785, 186.22590654, 156.09019587, 137.76343138, 

127.0869966, 137.34694566, 133.25311402, 122.55553768, 118.22456292, 

159.65747998, 122.77510258, 157.04492207, 35.161096589, 45.037465606, 

37.637919142, 35.049382182, 32.801385318, 39.203592294, 37.741972608, 

38.730897325, 72.049982746, 40.391500365, 41.502300762, 38.760239251, 

40.77839417, 36.989308973, 40.167455795, 33.865745389, 43.924857389, 

39.943200256, 38.908906355, 32.228421472, 40.341142093, 47.464460314, 

50.49858951, 57.964360275, 50.21179049, 60.817118221, 54.677239507, 

53.517382246, 51.296274573, 89.214368205, 51.205341958, 45.581040358, 

48.318404365, 56.420713722, 50.733345075, 47.746574266, 51.449188512, 

53.159378413, 51.672878035, 54.984310906, 49.853546957, 54.635080749, 

33.869158637, 36.420494624, 34.201671168, 31.169316346, 31.453926771, 

30.995599174, 34.941078022, 36.430641747, 72.9296608, 44.5318984, 

51.272563219, 40.981600774, 41.276944922, 34.307531597, 34.856211642, 

35.116862867, 53.886082496, 32.843276934, 67.787450893, 64.072083277, 

67.164756966, 37.15244679, 41.802139162, 45.057952384, 41.183183085, 

40.94067696, 44.759495578, 45.310676813, 42.227278496, 77.741274912, 

45.850713107, 37.290041421, 39.694496685, 43.410913574, 35.870854496, 

39.492859059, 39.508746528, 35.526071853, 30.332660653, 30.208349818, 

30.188126323, 33.049433254), Date = structure(c(17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727, 17587, 17594, 17601, 

17608, 17615, 17622, 17629, 17636, 17643, 17650, 17657, 17664, 

17671, 17678, 17685, 17692, 17699, 17706, 17713, 17720, 17727, 

17587, 17594, 17601, 17608, 17615, 17622, 17629, 17636, 17643, 

17650, 17657, 17664, 17671, 17678, 17685, 17692, 17699, 17706, 

17713, 17720, 17727, 17587, 17594, 17601, 17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727, 17587, 17594, 17601, 

17608, 17615, 17622, 17629, 17636, 17643, 17650, 17657, 17664, 

17671, 17678, 17685, 17692, 17699, 17706, 17713, 17720, 17727, 

17587, 17594, 17601, 17608, 17615, 17622, 17629, 17636, 17643, 

17650, 17657, 17664, 17671, 17678, 17685, 17692, 17699, 17706, 

17713, 17720, 17727, 17587, 17594, 17601, 17608, 17615, 17622, 

17629, 17636, 17643, 17650, 17657, 17664, 17671, 17678, 17685, 

17692, 17699, 17706, 17713, 17720, 17727), class = "Date")), row.names = c(NA, 

144L), class = "data.frame")

and I applied the following code to apply ses

library(zoo)

library(forecast)



z <- read.zoo(data_set,FUN = function(x) as.Date(x) + seq_along(x) / 10^10 , index = "Date", split = "customer_id")

L <- lapply(as.list(z), function(x) ts(na.omit(x),frequency = 52))

HW <- lapply(L, ses)

r dataframe time-series exponential unnest

edited Nov 19 at 16:00

asked Nov 19 at 15:52

riyan

106

edited Nov 19 at 16:00

asked Nov 19 at 15:52

riyan

106

edited Nov 19 at 16:00

asked Nov 19 at 15:52

riyan

106

asked Nov 19 at 15:52

riyan

106

asked Nov 19 at 15:52

riyan

106

Please be clear, are you using forecast::ses?
– r2evans
Nov 19 at 15:58

1

Yes@r2evans and edited my question.Thanks!
– riyan
Nov 19 at 16:00

@G.Grothendieck I tried your method but it showed me like columns names like Point Forecast , Lo 80, Hi 80 basically it showed me the intervals other than the fitted values and actual values which we can see in dput(HW) or view of HW.
– riyan
Nov 19 at 17:30

In order to unlist your output, you need to convert each element from class forecast to data.frame, and then you can bind the list elements together using bind_rows from package dplyr
– Giorgi Chighladze
Nov 19 at 21:40

add a comment |

Please be clear, are you using forecast::ses?
– r2evans
Nov 19 at 15:58

1

Yes@r2evans and edited my question.Thanks!
– riyan
Nov 19 at 16:00

@G.Grothendieck I tried your method but it showed me like columns names like Point Forecast , Lo 80, Hi 80 basically it showed me the intervals other than the fitted values and actual values which we can see in dput(HW) or view of HW.
– riyan
Nov 19 at 17:30

In order to unlist your output, you need to convert each element from class forecast to data.frame, and then you can bind the list elements together using bind_rows from package dplyr
– Giorgi Chighladze
Nov 19 at 21:40

Please be clear, are you using forecast::ses?
– r2evans
Nov 19 at 15:58

Yes@r2evans and edited my question.Thanks!
– riyan
Nov 19 at 16:00

@G.Grothendieck I tried your method but it showed me like columns names like Point Forecast , Lo 80, Hi 80 basically it showed me the intervals other than the fitted values and actual values which we can see in dput(HW) or view of HW.
– riyan
Nov 19 at 17:30

In order to unlist your output, you need to convert each element from class forecast to data.frame, and then you can bind the list elements together using bind_rows from package dplyr
– Giorgi Chighladze
Nov 19 at 21:40

add a comment |

1 Answer
1

active

oldest

votes

up vote
1
down vote

I would use tidyverse package to handle this problem.

map(HW, ~ .x %>% 

      as.data.frame %>%             # convert each element of the list to data.frame

      rownames_to_column) %>%       # add row names as columns within each element

  bind_rows(.id = "customer_id")    # bind all elements and add customer ID

I am not sure how to relate dates and actual sales to your output (HW). If you explain it I might provide solution to that part of the problem too.

answered Nov 19 at 22:10

Giorgi Chighladze

665

Still no luck,the output is showing only Lo and Hi values.I just want the actual values(from input),dates(from input) alsong with their customer_id and their exponential values in a data frame.
– riyan
yesterday

@riyan, can you show what the final table should look like. For instance, for customer "I-H0188" how do you want to combine HW and input data.
– Giorgi Chighladze
8 hours ago

add a comment |

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1 Answer
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active

oldest

votes

1 Answer
1

active

oldest

votes

up vote
1
down vote

I would use tidyverse package to handle this problem.

map(HW, ~ .x %>% 

      as.data.frame %>%             # convert each element of the list to data.frame

      rownames_to_column) %>%       # add row names as columns within each element

  bind_rows(.id = "customer_id")    # bind all elements and add customer ID

I am not sure how to relate dates and actual sales to your output (HW). If you explain it I might provide solution to that part of the problem too.

answered Nov 19 at 22:10

Giorgi Chighladze

665

Still no luck,the output is showing only Lo and Hi values.I just want the actual values(from input),dates(from input) alsong with their customer_id and their exponential values in a data frame.
– riyan
yesterday

@riyan, can you show what the final table should look like. For instance, for customer "I-H0188" how do you want to combine HW and input data.
– Giorgi Chighladze
8 hours ago

add a comment |

up vote
1
down vote

I would use tidyverse package to handle this problem.

map(HW, ~ .x %>% 

      as.data.frame %>%             # convert each element of the list to data.frame

      rownames_to_column) %>%       # add row names as columns within each element

  bind_rows(.id = "customer_id")    # bind all elements and add customer ID

I am not sure how to relate dates and actual sales to your output (HW). If you explain it I might provide solution to that part of the problem too.

answered Nov 19 at 22:10

Giorgi Chighladze

665

Still no luck,the output is showing only Lo and Hi values.I just want the actual values(from input),dates(from input) alsong with their customer_id and their exponential values in a data frame.
– riyan
yesterday

@riyan, can you show what the final table should look like. For instance, for customer "I-H0188" how do you want to combine HW and input data.
– Giorgi Chighladze
8 hours ago

add a comment |

up vote
1
down vote

I would use tidyverse package to handle this problem.

map(HW, ~ .x %>% 

      as.data.frame %>%             # convert each element of the list to data.frame

      rownames_to_column) %>%       # add row names as columns within each element

  bind_rows(.id = "customer_id")    # bind all elements and add customer ID

I am not sure how to relate dates and actual sales to your output (HW). If you explain it I might provide solution to that part of the problem too.

answered Nov 19 at 22:10

Giorgi Chighladze

665

I would use tidyverse package to handle this problem.

map(HW, ~ .x %>% 

      as.data.frame %>%             # convert each element of the list to data.frame

      rownames_to_column) %>%       # add row names as columns within each element

  bind_rows(.id = "customer_id")    # bind all elements and add customer ID

I am not sure how to relate dates and actual sales to your output (HW). If you explain it I might provide solution to that part of the problem too.

answered Nov 19 at 22:10

Giorgi Chighladze

665

answered Nov 19 at 22:10

Giorgi Chighladze

665

answered Nov 19 at 22:10

Giorgi Chighladze

665

answered Nov 19 at 22:10

Giorgi Chighladze

665

Still no luck,the output is showing only Lo and Hi values.I just want the actual values(from input),dates(from input) alsong with their customer_id and their exponential values in a data frame.
– riyan
yesterday

@riyan, can you show what the final table should look like. For instance, for customer "I-H0188" how do you want to combine HW and input data.
– Giorgi Chighladze
8 hours ago

add a comment |

Still no luck,the output is showing only Lo and Hi values.I just want the actual values(from input),dates(from input) alsong with their customer_id and their exponential values in a data frame.
– riyan
yesterday

@riyan, can you show what the final table should look like. For instance, for customer "I-H0188" how do you want to combine HW and input data.
– Giorgi Chighladze
8 hours ago

Still no luck,the output is showing only Lo and Hi values.I just want the actual values(from input),dates(from input) alsong with their customer_id and their exponential values in a data frame.
– riyan
yesterday

@riyan, can you show what the final table should look like. For instance, for customer "I-H0188" how do you want to combine HW and input data.
– Giorgi Chighladze
8 hours ago

add a comment |

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