pivot_wider 问题“values_from"中的值不是唯一标识的；输出将包含 list-cols" [英] pivot_wider issue "Values in `values_from` are not uniquely identified; output will contain list-cols"
本文介绍了pivot_wider 问题“values_from"中的值不是唯一标识的；输出将包含 list-cols"的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我的数据如下所示:
# A tibble: 6 x 4
name val time x1
<chr> <dbl> <date> <dbl>
1 C Farolillo 7 2016-04-20 51.5
2 C Farolillo 3 2016-04-21 56.3
3 C Farolillo 7 2016-04-22 56.3
4 C Farolillo 13 2016-04-23 57.9
5 C Farolillo 7 2016-04-24 58.7
6 C Farolillo 9 2016-04-25 59.0
我正在尝试使用 pivot_wider 函数来扩展基于 name 列的数据.我使用以下代码:
I am trying to use the pivot_wider function to expand out the data based on the name column. I use the following code:
yy <- d %>%
pivot_wider(., names_from = name, values_from = val)
这给了我以下警告信息:
Which gives me the following warning message:
Warning message:
Values in `val` are not uniquely identified; output will contain list-cols.
* Use `values_fn = list(val = list)` to suppress this warning.
* Use `values_fn = list(val = length)` to identify where the duplicates arise
* Use `values_fn = list(val = summary_fun)` to summarise duplicates
输出如下:
time x1 out1 out2
2016-04-20 51.50000 <dbl> <dbl>
2 2016-04-21 56.34615 <dbl> <dbl>
3 2016-04-22 56.30000 <dbl> <dbl>
4 2016-04-23 57.85714 <dbl> <dbl>
5 2016-04-24 58.70968 <dbl> <dbl>
6 2016-04-25 58.96774 <dbl> <dbl>
我知道这里 提到了这个问题，为了解决这个问题，他们建议使用汇总统计.但是我有时间序列数据，因此不想使用汇总统计数据，因为每天都有一个值(而不是多个值).
I know that here mentions the issue and to resolve it they suggest using summary statistics. However I have time series data and thus do not want to use summary statistics since each day has a single value (and not multiple values).
我知道问题是因为 val 列有重复(即在上面的例子中 7 出现了 3 次.
I know the problem is because the val column has duplicates (i.e. in the above example 7 occurs 3 times.
关于如何使用 pivot_wider 和克服这个问题的任何建议?
Any suggestions on how to pivot_wider and overcome this issue?
数据:
d <- structure(list(name = c("C Farolillo", "C Farolillo", "C Farolillo",
"C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo",
"C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo",
"C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo",
"C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo",
"C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo",
"C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo",
"C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo",
"C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo",
"C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo", "C Farolillo",
"C Farolillo", "C Farolillo", "C Farolillo", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica", "Plaza Eliptica",
"Plaza Eliptica", "Plaza Eliptica"), val = c(7, 3, 7, 13, 7,
9, 20, 19, 4, 5, 5, 2, 6, 6, 16, 13, 7, 6, 3, 3, 6, 10, 5, 3,
5, 3, 4, 4, 10, 11, 4, 13, 8, 2, 8, 10, 3, 10, 14, 4, 2, 4, 6,
6, 8, 8, 3, 3, 13, 10, 13, 32, 25, 31, 34, 26, 33, 35, 43, 22,
22, 21, 10, 33, 33, 48, 47, 27, 23, 11, 13, 25, 31, 20, 16, 10,
9, 23, 11, 23, 26, 16, 34, 17, 4, 24, 21, 10, 26, 32, 10, 5,
9, 19, 14, 27, 27, 10, 8, 28, 32, 25), time = structure(c(16911,
16912, 16913, 16914, 16915, 16916, 16917, 16918, 16919, 16920,
16921, 16922, 16923, 16923, 16924, 16925, 16926, 16927, 16928,
16929, 16930, 16931, 16932, 16933, 16934, 16935, 16936, 16937,
16938, 16939, 16940, 16941, 16942, 16943, 16944, 16945, 16946,
16947, 16948, 16949, 16950, 16951, 16952, 16953, 16954, 16955,
16956, 16957, 16958, 16959, 16960, 16911, 16912, 16913, 16914,
16915, 16916, 16917, 16918, 16919, 16920, 16921, 16922, 16923,
16923, 16924, 16925, 16926, 16927, 16928, 16929, 16930, 16931,
16932, 16933, 16934, 16935, 16936, 16937, 16938, 16939, 16940,
16941, 16942, 16943, 16944, 16945, 16946, 16947, 16948, 16949,
16950, 16951, 16952, 16953, 16954, 16955, 16956, 16957, 16958,
16959, 16960), class = "Date"), x1 = c(51.5, 56.3461538461538,
56.3, 57.8571428571429, 58.7096774193548, 58.9677419354839, 64.4615384615385,
61.9310344827586, 60.3214285714286, 59.4137931034483, 59.5806451612903,
57.3448275862069, 64.0333333333333, 64.0333333333333, 70.15625,
71.3636363636364, 62.8125, 56.4375, 56.4516129032258, 51.741935483871,
52.84375, 53.09375, 52.969696969697, 54, 54.3870967741936, 60.3870967741936,
64.4516129032258, 66.2903225806452, 68.2333333333333, 69.7741935483871,
70.5806451612903, 73.8275862068966, 72.8181818181818, 64.6764705882353,
64.4838709677419, 68.7741935483871, 62.1764705882353, 68.969696969697,
70.1935483870968, 59.6774193548387, 59.9677419354839, 63.125,
67.5882352941177, 71.4705882352941, 73.8529411764706, 76.1935483870968,
72.6451612903226, 76.0645161290323, 76.4193548387097, 81.7741935483871,
85.0645161290323, 51.5, 56.3461538461538, 56.3, 57.8571428571429,
58.7096774193548, 58.9677419354839, 64.4615384615385, 61.9310344827586,
60.3214285714286, 59.4137931034483, 59.5806451612903, 57.3448275862069,
64.0333333333333, 64.0333333333333, 70.15625, 71.3636363636364,
62.8125, 56.4375, 56.4516129032258, 51.741935483871, 52.84375,
53.09375, 52.969696969697, 54, 54.3870967741936, 60.3870967741936,
64.4516129032258, 66.2903225806452, 68.2333333333333, 69.7741935483871,
70.5806451612903, 73.8275862068966, 72.8181818181818, 64.6764705882353,
64.4838709677419, 68.7741935483871, 62.1764705882353, 68.969696969697,
70.1935483870968, 59.6774193548387, 59.9677419354839, 63.125,
67.5882352941177, 71.4705882352941, 73.8529411764706, 76.1935483870968,
72.6451612903226, 76.0645161290323, 76.4193548387097, 81.7741935483871,
85.0645161290323)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA,
-102L))
推荐答案
为每个 name 创建一个唯一的标识符行，然后使用 pivot_wider
Create a unique identifier row for each name and then use pivot_wider
library(dplyr)
d %>%
group_by(name) %>%
mutate(row = row_number()) %>%
tidyr::pivot_wider(names_from = name, values_from = val) %>%
select(-row)
# A tibble: 51 x 4
# time x1 `C Farolillo` `Plaza Eliptica`
# <date> <dbl> <dbl> <dbl>
# 1 2016-04-20 51.5 7 32
# 2 2016-04-21 56.3 3 25
# 3 2016-04-22 56.3 7 31
# 4 2016-04-23 57.9 13 34
# 5 2016-04-24 58.7 7 26
# 6 2016-04-25 59.0 9 33
# 7 2016-04-26 64.5 20 35
# 8 2016-04-27 61.9 19 43
# 9 2016-04-28 60.3 4 22
#10 2016-04-29 59.4 5 22
# … with 41 more rows
这篇关于pivot_wider 问题“values_from"中的值不是唯一标识的；输出将包含 list-cols"的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
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