Unnest a ts class
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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.
r dataframe time-series exponential unnest
asked Nov 19 at 15:52
riyan
106
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)
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.
r dataframe time-series exponential unnest
asked Nov 19 at 15:52
riyan
106
Please be clear, are you usingforecast::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 likePoint Forecast,Lo 80,Hi 80basically 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 classforecasttodata.frame, and then you can bind the list elements together usingbind_rowsfrom packagedplyr
– Giorgi Chighladze
Nov 19 at 21:40
add a comment |
up vote
0
down vote
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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)
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.
r dataframe time-series exponential unnest
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)
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.
r dataframe time-series exponential unnest
r dataframe time-series exponential unnest
asked Nov 19 at 15:52
riyan
106
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
106
Please be clear, are you usingforecast::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 likePoint Forecast,Lo 80,Hi 80basically 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 classforecasttodata.frame, and then you can bind the list elements together usingbind_rowsfrom packagedplyr
– Giorgi Chighladze
Nov 19 at 21:40
add a comment |
Please be clear, are you usingforecast::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 likePoint Forecast,Lo 80,Hi 80basically 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 classforecasttodata.frame, and then you can bind the list elements together usingbind_rowsfrom packagedplyr
– Giorgi Chighladze
Nov 19 at 21:40
Please be clear, are you using
forecast::ses?– r2evans
Nov 19 at 15:58
Please be clear, are you using
forecast::ses?– r2evans
Nov 19 at 15:58
1
1
Yes@r2evans and edited my question.Thanks!
– riyan
Nov 19 at 16:00
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
@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
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 |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
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
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
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
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
@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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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 80basically 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
forecasttodata.frame, and then you can bind the list elements together usingbind_rowsfrom packagedplyr– Giorgi Chighladze
Nov 19 at 21:40