purrr-map05

library(tidyverse)

Exercise

Erstellen Sie eine Tabelle mit mit folgenden Spalten:

• ID-Spalte: \(1,2,..., 10\)
• Eine Spalte, in der jede Zelle eine Tabelle mit einem Vektor \(x\), einer standardnormalverteilten Zufallszahlen (n=1000), enthält

Berechnen Sie den Mittelwert von jedem \(x\)! Diese Ergebnisse sollen als weitere Spalte der Tabelle hinzugefügt werden.

Solution

d <- tibble(
  id = 1:10) %>% 
  mutate(x = map(id, ~ rnorm(n = 1e3))
) 

str(d)

tibble [10 × 2] (S3: tbl_df/tbl/data.frame)
 $ id: int [1:10] 1 2 3 4 5 6 7 8 9 10
 $ x :List of 10
  ..$ : num [1:1000] 1.13 0.0391 -1.111 0.9633 1.8529 ...
  ..$ : num [1:1000] 0.286 -0.202 0.512 -0.818 2.291 ...
  ..$ : num [1:1000] -0.00874 -1.73109 -0.80031 0.08323 0.58919 ...
  ..$ : num [1:1000] -0.7134 0.327 0.7852 -0.7954 -0.0336 ...
  ..$ : num [1:1000] 0.1108 -1.444 -0.0823 -0.6374 -0.3509 ...
  ..$ : num [1:1000] 1.793 -0.735 0.407 -0.309 -1.184 ...
  ..$ : num [1:1000] 0.145 -2.144 -0.114 -1.099 1.179 ...
  ..$ : num [1:1000] -0.0448 -1.8064 0.6906 -0.3094 1.146 ...
  ..$ : num [1:1000] 0.5583 -1.6305 0.0383 -0.2991 0.9314 ...
  ..$ : num [1:1000] -0.23 1.695 0.234 -0.411 1.496 ...

So kann man sich die Mittelwerte ausgeben lassen:

d$x %>% 
  map(mean)

[[1]]
[1] 0.003790061

[[2]]
[1] -0.02829832

[[3]]
[1] 0.0140533

[[4]]
[1] -0.02764058

[[5]]
[1] 0.01011673

[[6]]
[1] -0.01683266

[[7]]
[1] 0.009744692

[[8]]
[1] -0.008774502

[[9]]
[1] -0.02438361

[[10]]
[1] 0.007858768

Jetzt fügen wir den letzten Schritt als Spalte hinzu:

d2 <-
  d %>% 
  mutate(x_mean = map_dbl(x, ~ mean(.x))) 

head(d2)

id	x	x_mean
1	1.129967218, 0.039082892, -1.110991626, 0.963305222, 1.852870661, 1.510573329, -0.528400433, 1.220485244, 0.318030059, -0.816448130, 1.025637380, 0.915494970, -0.450388473, -1.305825405, -0.786611772, -1.316948555, -0.461831683, 0.540257800, 1.393654064, 1.171380379, -0.892157806, -0.024515178, 0.136435431, 1.098061769, -2.197377401, 1.300823740, 0.670045146, -0.426523692, -0.854517941, 1.099605371, 1.504040110, 0.847705794, 0.510170385, -0.328402111, 0.592919535, -0.608226040, -0.627629610, 0.305000678, 2.026647427, 1.057585943, -0.125291620, -0.557331326, -1.250103237, -1.438773706, -0.847581772, 0.038457469, 1.859989746, -2.846900660, 0.699182408, 1.358251956, 0.241036754, 0.201835365, 1.045979791, -0.029048537, 1.105006595, 0.102657526, 1.365572948, -0.139392789, 0.366220545, -0.648249390, -0.260941781, -0.031464865, 0.203537095, 0.892117218, -0.133749011, 0.494395844, 1.152557971, 2.295697720, -0.152736386, 1.895861211, 1.785232176, -1.200307338, 1.696002950, 0.065712076, 1.126016136, 0.249685654, 0.166369840, 0.749613507, -0.653662831, 0.454460938, 0.179472330, 0.548301461, 0.777678065, 0.104919580, -2.124976061, 0.298960473, -0.143763184, -0.511598346, 0.319750225, -0.021363371, 0.704876792, -0.647839981, -0.258415332, -1.518134860, 0.728855482, -0.092621260, 0.908858348, -0.009648747, -1.324239993, -0.651122005, -0.916851495, -0.854200195, -0.334544127, -0.022515115, -0.445657020, 0.602186026, 2.258159826, 0.383361510, 0.394630295, -0.355604862, -0.757102309, 0.197263333, 0.814895336, -0.800532822, -1.269143880, 1.812920024, -0.752624588, -0.098348785, -0.482570679, 0.224027748, 0.140633273, -0.470958145, 0.145149874, -0.102401632, -1.286361002, -0.049713491, 2.646737350, 0.474319974, -0.064973494, 0.231694995, 0.358649218, 0.903135146, -0.786853583, 1.113797615, -0.486163793, 1.381860897, 0.456276600, -0.237615111, 0.615750310, 0.458893717, -1.235879902, 0.113891396, -1.507756905, 1.058283661, -0.812731219, 0.152592025, -1.344434832, 1.176973206, 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-1.3317483731, 0.3722882459, 1.5191511003, -0.9498703536, -0.4563881780, -0.6341833037, 2.1287373597, -0.9757670526, 0.0714019628, 0.5012889431, 2.1517635806, 0.3982388350, 0.2850022161, 0.7565230140, 1.5891810136, 1.2053199597, 0.9487632098, 0.6461415308, -0.9612068811, -0.6111983512, -0.8057581930, -2.2046321314, -0.1399848357, 1.1266223858, -1.2594926736, -0.4051924743, -0.7864227995, -0.0076392877, -1.2148865789, 0.0224146555, 0.3162899511, -0.7914808400, 0.9229611994, -0.8135240632, -0.8117200885, 0.4568334792, -0.3806423420, 0.5511202819, -0.2783127743, 1.0204399313, -1.1514821047, 0.7022908571, 0.0691098672, 0.3022300232, -1.0928488343, 1.5214550672, 0.5818621708, -0.5168615329, -1.3025574693, 1.3178292808, 0.3327174380, -1.0889328072, -0.7300780307, -0.7990240707, 0.1549466715, 0.7302019645, -0.9597759458, 1.4478382169, 0.6898823629, -0.4396606080, -0.8038030708, 0.8986606254, 1.4663799571, 0.4213099343, 1.0721915187, 0.0004270931, -1.8190060371, 0.9334040270, 0.6933457646, -0.9428803601, 1.5076887436, -1.0725358588, 0.3109695959, 0.6899589678, 0.4663364772, -1.2051674010, -0.8492449788, -0.8435402988, 0.2284364440, -0.4517366603, -0.1457986453, -0.8031141674, 1.9962589999, 0.9734472848, -1.7317208930, -0.2691687878, 1.7000762686, 0.9555035835, -0.6364228743, 0.5643430946, -0.3581462093, -0.4735592964, -0.1109767021, -0.7140245815, -1.1933989254, 1.3921219875, 0.1149336097, -0.9018754333, -0.4855101448, 0.1816603041, 0.0086196595, 0.1834025505, -2.9500764921, 0.8379839938, -0.1602575560, 0.2949079634, -1.2909311514, -1.0132604729, -0.2337856604, -0.5831928053, -1.8842571156, 0.0109578823, -1.2868838382, 0.7996299981, -0.7268257429, 1.1116232941, 0.5137587147, -0.0075185239, -1.1741442910, -1.0906749253, -1.1155707983, -0.3522219230, 0.3207591969, -1.0707626161, 0.0494070954, -0.7488658302, 0.9258771112, -0.4411833024, 1.4030242940, 1.7460849298, -0.9056847811, -3.1129201699, 0.0901076308, -0.3587376422, -0.8223680711, 0.3010386604, 0.5355436206, -1.6133009142, 0.0558011071, 0.5790166848, -1.7465442739, -0.9057910473, 0.5305155467, -2.6496090630, 1.5390646894, -1.0863986113, -1.5706771018, -2.0286487213, 0.2629739428, 2.1623874292, -0.2978498288, -0.2966696053, 0.4014788260, 0.1729803217, 0.2769837200, 1.4912276240, 1.3324490826, 1.0289211764, 1.5999464021, -1.0219275552, 0.8975337417, -0.2655790691, 1.5318114397, 1.0100245394, 0.4095373178, 1.5413297211, -0.3442066039, 0.1161455841, -0.8261079852, 0.4762477494, -0.4501155231, -0.5983399948, -1.1634510571, -0.7927315180, -0.7395624227, -1.4669508385, 0.0308158995, 1.7200221481, 1.0007276049, 0.4292327003, 0.6875987801, -1.0411680335, -0.4449264175, -0.3780266778, -0.2792342143, -1.0270984177, 1.2676084071, -0.5407293118, 1.1410835550, -0.3554195187, 1.1906525480, -0.7048658963, 2.0544178432, -0.7923599435, -0.0318257944, -0.5820648131, -0.3630288643, -0.3666679604, -0.3142407464, -1.1212414915, -0.9707628115, 0.3327088860, 0.1223212603, -0.7745332526, 0.3057860070, 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Hier hätten wir auch schreiben können:

d %>% 
  mutate(x_mean = map(x, mean)) %>% 
  unnest(x_mean) %>% 
  head()

id	x	x_mean
1	1.129967218, 0.039082892, -1.110991626, 0.963305222, 1.852870661, 1.510573329, -0.528400433, 1.220485244, 0.318030059, -0.816448130, 1.025637380, 0.915494970, -0.450388473, -1.305825405, -0.786611772, -1.316948555, -0.461831683, 0.540257800, 1.393654064, 1.171380379, -0.892157806, -0.024515178, 0.136435431, 1.098061769, -2.197377401, 1.300823740, 0.670045146, -0.426523692, -0.854517941, 1.099605371, 1.504040110, 0.847705794, 0.510170385, -0.328402111, 0.592919535, -0.608226040, -0.627629610, 0.305000678, 2.026647427, 1.057585943, -0.125291620, -0.557331326, -1.250103237, -1.438773706, -0.847581772, 0.038457469, 1.859989746, -2.846900660, 0.699182408, 1.358251956, 0.241036754, 0.201835365, 1.045979791, -0.029048537, 1.105006595, 0.102657526, 1.365572948, -0.139392789, 0.366220545, -0.648249390, -0.260941781, -0.031464865, 0.203537095, 0.892117218, -0.133749011, 0.494395844, 1.152557971, 2.295697720, -0.152736386, 1.895861211, 1.785232176, -1.200307338, 1.696002950, 0.065712076, 1.126016136, 0.249685654, 0.166369840, 0.749613507, -0.653662831, 0.454460938, 0.179472330, 0.548301461, 0.777678065, 0.104919580, -2.124976061, 0.298960473, -0.143763184, -0.511598346, 0.319750225, -0.021363371, 0.704876792, -0.647839981, -0.258415332, -1.518134860, 0.728855482, -0.092621260, 0.908858348, -0.009648747, -1.324239993, -0.651122005, -0.916851495, -0.854200195, -0.334544127, -0.022515115, -0.445657020, 0.602186026, 2.258159826, 0.383361510, 0.394630295, -0.355604862, -0.757102309, 0.197263333, 0.814895336, -0.800532822, -1.269143880, 1.812920024, -0.752624588, -0.098348785, -0.482570679, 0.224027748, 0.140633273, -0.470958145, 0.145149874, -0.102401632, -1.286361002, -0.049713491, 2.646737350, 0.474319974, -0.064973494, 0.231694995, 0.358649218, 0.903135146, -0.786853583, 1.113797615, -0.486163793, 1.381860897, 0.456276600, -0.237615111, 0.615750310, 0.458893717, -1.235879902, 0.113891396, -1.507756905, 1.058283661, -0.812731219, 0.152592025, -1.344434832, 1.176973206, 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Categories:

• programming
• loop