R：Shiny和Ggplot2使用相同的代碼顯示不同的情節
[英]R: Shiny and Ggplot2 show different plot with same code
問題描述
擁有2014年12月每天的數據。要根據日期選擇繪制條形圖：
原始數據：
structure(list(date = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
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18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 19L, 19L,
19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L,
19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L,
19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L,
19L, 19L, 19L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 20L, 20L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L,
21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L,
21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L,
21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L,
21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 22L, 22L, 22L, 22L, 22L,
22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L,
22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L,
22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L,
22L, 22L, 22L, 22L, 22L, 22L, 22L, 22L, 23L, 23L, 23L, 23L, 23L,
23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L,
23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L,
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24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L,
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27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L,
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27L, 27L, 27L, 27L, 27L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L,
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28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 29L, 29L,
29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L,
29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L,
29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L, 29L,
29L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 31L, 31L, 31L, 31L, 31L, 31L, 31L,
31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L,
31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L), .Label = c("2014-12-01",
"2014-12-02", "2014-12-03", "2014-12-04", "2014-12-05", "2014-12-06",
"2014-12-07", "2014-12-08", "2014-12-09", "2014-12-10", "2014-12-11",
"2014-12-12", "2014-12-13", "2014-12-14", "2014-12-15", "2014-12-16",
"2014-12-17", "2014-12-18", "2014-12-19", "2014-12-20", "2014-12-21",
"2014-12-22", "2014-12-23", "2014-12-24", "2014-12-25", "2014-12-26",
"2014-12-27", "2014-12-28", "2014-12-29", "2014-12-30", "2014-12-31"
), class = "factor"), sessions = c(197L, 1L, 7L, 13L, 1L, 1L,
10L, 1L, 3L, 3L, 5L, 3L, 566L, 1L, 27L, 159L, 7L, 1L, 6L, 1L,
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1L, 28L, 1L, 7L, 386L, 1L, 146L, 1L, 89L, 41L, 9L, 1L, 1L, 1L,
6L, 3L, 4L, 182L, 1L, 5L, 8L, 2L, 1L, 1L, 4L, 1L, 1L, 2L, 3L,
2L, 524L, 4L, 26L, 1L, 152L, 4L, 2L, 3L, 1L, 2L, 2L, 1L, 5L,
10L, 142L, 1L, 1L, 8L, 1L, 3L, 1L, 1L, 1L, 1L, 7L, 4L, 13L, 3L,
375L, 3L, 2L, 147L, 1L, 101L, 29L, 4L, 1L, 1L, 2L, 3L, 1L, 1L,
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4L, 632L, 2L, 2L, 32L, 1L, 138L, 1L, 1L, 9L, 5L, 1L, 1L, 1L,
2L, 1L, 6L, 3L, 139L, 4L, 1L, 9L, 1L, 1L, 5L, 9L, 8L, 36L, 1L,
537L, 1L, 2L, 5L, 3L, 174L, 1L, 106L, 39L, 9L, 2L, 2L, 2L, 3L,
1L, 6L, 3L, 2L, 689L, 1L, 14L, 2L, 2L, 35L, 1L, 15L, 1L, 1L,
1L, 3L, 20L, 465L, 1L, 3269L, 1L, 2L, 1L, 9L, 1L, 32L, 6L, 2L,
293L, 1L, 3L, 1L, 11L, 2L, 1L, 9L, 10L, 1L, 1L, 1L, 1L, 1L, 2L,
7L, 2L, 433L, 1L, 4L, 1L, 1L, 3L, 19L, 1L, 2L, 1L, 1L, 12L, 1L,
4L, 1L, 1L, 3L, 37L, 10L, 88L, 6L, 1808L, 5L, 4L, 451L, 5L, 219L,
112L, 4L, 3L, 1L, 6L, 1L, 2L, 3L, 5L, 10L, 2L, 264L, 8L, 1L,
1L, 1L, 17L, 1L, 1L, 7L, 1L, 1L, 4L, 6L, 516L, 1L, 948L, 2L,
1L, 2L, 1L, 33L, 1L, 1L, 133L, 1L, 2L, 1L, 5L, 11L, 1L, 4L, 1L,
1L, 1L, 6L, 10L, 5L, 168L, 1L, 1L, 5L, 1L, 10L, 1L, 1L, 3L, 9L,
1L, 2L, 1L, 8L, 3L, 98L, 1L, 548L, 1L, 1L, 177L, 97L, 17L, 4L,
1L, 6L, 2L, 1L, 2L, 1L, 1L, 5L, 4L, 5L, 235L, 1L, 2L, 9L, 2L,
19L, 1L, 2L, 2L, 1L, 1L, 3L, 6L, 5L, 396L, 1209L, 1L, 2L, 1L,
41L, 1L, 125L, 3L, 5L, 1L, 4L, 1L, 1L, 4L, 1L, 3L, 1L, 1L, 5L,
2L, 121L, 2L, 1L, 1L, 10L, 1L, 1L, 4L, 1L, 2L, 10L, 3L, 75L,
5L, 632L, 1L, 2L, 2L, 178L, 1L, 67L, 33L, 6L, 1L, 1L, 1L, 2L,
1L, 12L, 3L, 194L, 1L, 1L, 1L, 1L, 1L, 20L, 1L, 1L, 6L, 1L, 1L,
1L, 1L, 1L, 3L, 2L, 296L, 1L, 1L, 979L, 6L, 4L, 1L, 33L, 1L,
109L, 5L, 2L, 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 6L, 3L, 118L,
1L, 1L, 15L, 1L, 1L, 1L, 1L, 1L, 4L, 2L, 1L, 18L, 6L, 53L, 3L,
584L, 2L, 1L, 2L, 172L, 2L, 100L, 27L, 9L, 2L, 1L, 2L, 1L, 1L,
1L, 11L, 3L, 202L, 6L, 20L, 2L, 1L, 1L, 4L, 1L, 8L, 2L, 292L,
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7L, 3L, 139L, 4L, 1L, 2L, 17L, 1L, 2L, 3L, 2L, 20L, 53L, 3L,
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1L, 1L, 13L, 3L, 297L, 4L, 1L, 1L, 9L, 1L, 1L, 1L, 1L, 2L, 1L,
2L, 1L, 25L, 182L, 1L, 776L, 2L, 1L, 1L, 260L, 2L, 115L, 52L,
14L, 2L, 4L, 3L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 14L,
2L, 731L, 7L, 2L, 1L, 16L, 1L, 1L, 3L, 2L, 1L, 1L, 11L, 6L, 294L,
1L, 1135L, 1L, 3L, 1L, 6L, 1L, 36L, 1L, 1L, 126L, 4L, 1L, 1L,
4L, 11L, 1L, 2L, 1L, 2L, 2L, 1L, 6L, 355L, 3L, 9L, 1L, 4L, 1L,
13L, 2L, 1L, 1L, 7L, 1L, 1L, 22L, 5L, 67L, 1L, 2L, 926L, 1L,
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2L, 4L, 2L, 1L, 1L, 1L, 1L, 8L, 9L, 1L, 198L, 1L, 8L, 13L, 2L,
4L, 1L, 4L, 2L, 205L, 568L, 1L, 1L, 19L, 94L, 2L, 3L, 8L, 1L,
1L, 1L, 1L, 1L, 1L, 8L, 157L, 4L, 1L, 1L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 12L, 28L, 3L, 444L, 3L, 1L, 2L, 118L, 2L, 75L, 27L,
1L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 6L, 7L, 166L, 1L, 1L, 11L, 1L,
1L, 3L, 1L, 1L, 1L, 3L, 203L, 644L, 2L, 1L, 1L, 2L, 26L, 1L,
4L, 75L, 1L, 4L, 2L, 5L, 1L, 1L, 1L, 1L, 1L, 4L, 155L, 1L, 1L,
1L, 3L, 4L, 1L, 2L, 6L, 1L, 36L, 1L, 2L, 446L, 3L, 1L, 99L, 86L,
27L, 1L, 2L, 1L, 1L, 3L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 7L,
1L, 7L, 159L, 1L, 3L, 12L, 1L, 3L, 1L, 1L, 8L, 174L, 733L, 1L,
1L, 1L, 1L, 22L, 2L, 84L, 1L, 1L, 6L, 3L, 1L, 1L, 1L, 3L, 1L,
100L, 6L, 2L, 3L, 1L, 8L, 3L, 38L, 7L, 502L, 2L, 1L, 86L, 6L,
83L, 24L, 6L, 1L, 1L, 1L, 2L, 2L, 321L, 8L, 11L, 1L, 4L, 1L,
2L, 2L, 13L, 191L, 1L, 5L, 1417L, 1L, 6L, 1L, 1L, 28L, 2L, 1L,
150L, 1L, 1L, 7L, 1L, 3L, 2L, 1L, 1L, 3L, 1L, 2L, 1L, 1L, 1L,
4L, 1L, 218L, 3L, 1L, 1L, 8L, 1L, 2L, 1L, 1L, 16L, 4L, 45L, 1L,
3L, 879L, 3L, 1L, 1L, 2L, 207L, 2L, 115L, 44L, 1L, 3L, 1L, 1L,
3L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 171L, 4L, 1L, 1L, 7L, 1L, 5L,
4L, 178L, 614L, 3L, 1L, 3L, 1L, 5L, 20L, 1L, 94L, 3L, 4L, 8L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 121L, 1L, 1L, 6L, 1L, 1L, 3L,
2L, 1L, 7L, 3L, 31L, 1L, 1L, 433L, 1L, 3L, 23L, 94L, 79L, 25L,
1L, 2L, 2L, 6L, 2L, 160L, 3L, 6L, 1L, 3L, 2L, 2L, 3L, 1L, 568L,
1L, 2L, 5L, 15L, 5L, 86L, 1L, 2L, 4L, 8L, 3L, 4L, 1L, 1L, 2L,
1L, 118L, 9L, 7L, 1L, 2L, 2L, 11L, 3L, 10L, 1L, 530L, 2L, 3L,
2L, 121L, 1L, 1L, 72L, 34L, 3L, 3L, 1L, 3L, 1L, 1L, 1L, 7L, 4L,
326L, 13L, 1L, 1L, 18L, 1L, 2L, 8L, 4L, 2L, 2L, 1L, 1271L, 1L,
1L, 1L, 2L, 3L, 17L, 2L, 161L, 3L, 1L, 14L, 1L, 1L, 2L, 1L, 1L,
4L, 1L, 1L, 10L, 1L, 195L, 1L, 6L, 1L, 1L, 1L, 1L, 23L, 1L, 1L,
2L, 1L, 1L, 2L, 20L, 4L, 10L, 1L, 1050L, 1L, 1L, 3L, 1L, 1L,
1L, 19L, 1L, 196L, 134L, 52L, 4L, 1L, 1L, 1L, 1L, 2L, 3L, 3L,
1L, 1L, 5L, 6L, 1L, 120L, 1L, 3L, 6L, 1L, 1L, 2L, 1L, 2L, 371L,
1L, 1L, 7L, 74L, 2L, 11L, 1L, 3L, 84L, 1L, 1L, 3L, 4L, 14L, 2L,
1L, 5L, 1L, 6L, 1L, 382L, 3L, 1L, 2L, 6L, 2L, 69L, 1L, 54L, 17L,
2L, 1L, 1L, 3L, 7L, 1L, 168L, 2L, 1L, 7L, 1L, 1L, 1L, 1L, 2L,
1L, 5L, 374L, 2L, 5L, 7L, 2L, 69L, 1L, 10L, 6L, 85L, 1L, 1L,
16L, 1L, 1L, 1L, 5L, 2L, 2L, 393L, 3L, 17L, 53L, 75L, 22L, 2L,
2L, 1L, 1L, 1L, 7L, 3L, 1L, 136L, 1L, 7L, 3L, 3L, 2L, 1L, 2L,
488L, 1L, 4L, 25L, 1L, 71L, 1L, 1L, 1L, 3L, 1L, 1L, 2L, 2L, 126L,
5L, 1L, 8L, 2L, 1L, 1L, 1L, 1L, 1L, 10L, 1L, 4L, 1L, 1L, 445L,
1L, 1L, 90L, 1L, 77L, 20L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L,
248L, 8L, 1L, 1L, 19L, 1L, 2L, 1L, 1L, 1L, 4L, 1L, 3L, 981L,
2L, 2L, 1L, 3L, 1L, 14L, 1L, 2L, 134L, 3L, 2L, 1L, 1L, 3L, 1L,
1L, 2L, 5L, 194L, 5L, 1L, 16L, 1L, 1L, 2L, 2L, 1L, 9L, 3L, 8L,
850L, 1L, 1L, 155L, 1L, 117L, 43L, 4L, 4L, 4L, 3L, 5L, 124L,
1L, 1L, 4L, 6L, 1L, 1L, 2L, 3L, 1L, 2L, 373L, 4L, 1L, 2L, 8L,
1L, 63L, 1L, 2L, 12L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 125L, 7L, 2L,
1L, 1L, 7L, 2L, 5L, 1L, 2L, 287L, 2L, 3L, 1L, 54L, 1L, 49L, 19L,
2L, 2L, 3L, 5L, 8L, 1L, 91L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 2L,
289L, 1L, 1L, 1L, 12L, 61L, 1L, 1L, 14L, 2L, 1L, 91L, 1L, 1L,
1L, 7L, 2L, 1L, 4L, 1L, 241L, 1L, 5L, 42L, 1L, 51L, 9L, 4L, 1L,
1L, 4L, 98L, 2L, 4L, 2L, 2L, 251L, 1L, 12L, 1L, 47L, 3L, 1L,
2L, 1L, 1L, 1L, 3L, 2L, 73L, 2L, 3L, 1L, 1L, 11L, 2L, 3L, 1L,
214L, 2L, 1L, 40L, 41L, 17L, 3L, 2L, 103L, 1L, 8L, 5L, 1L, 2L,
1L, 270L, 1L, 1L, 3L, 21L, 60L, 2L, 1L, 2L, 2L, 73L, 4L, 2L,
2L, 1L, 1L, 4L, 1L, 2L, 1L, 219L, 1L, 55L, 60L, 13L, 1L, 2L,
1L, 1L, 168L, 3L, 7L, 1L, 7L, 1L, 1L, 1L, 404L, 8L, 8L, 1L, 99L,
3L, 3L, 11L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 3L, 1L, 115L,
1L, 2L, 3L, 2L, 2L, 1L, 1L, 1L, 1L, 5L, 3L, 6L, 362L, 1L, 2L,
64L, 2L, 88L, 15L, 1L, 4L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 104L, 2L, 1L, 9L, 1L, 5L, 1L, 2L, 1L, 1L, 343L, 1L, 1L, 1L,
3L, 10L, 64L, 2L, 10L, 1L, 1L, 1L, 1L, 1L, 4L, 106L, 3L, 1L,
1L, 1L, 2L, 6L, 286L, 1L, 2L, 43L, 2L, 56L, 24L, 1L, 1L, 1L,
1L, 1L, 2L, 1L, 1L, 1L, 140L, 1L, 4L, 2L, 1L, 2L, 2L, 479L, 1L,
1L, 4L, 20L, 87L, 1L, 2L, 1L, 1L, 3L, 3L, 1L, 3L, 1L, 118L, 5L,
1L, 9L, 4L, 1L, 14L, 4L, 1L, 1L, 389L, 1L, 1L, 66L, 1L, 75L,
13L, 1L, 1L, 2L, 1L, 1L, 1L, 98L, 3L, 1L, 8L, 2L, 2L, 1L, 1L,
341L, 3L, 1L, 21L, 101L, 2L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 85L,
1L, 1L, 1L, 2L, 2L, 4L, 1L, 1L, 4L, 278L, 10L, 67L, 2L, 54L,
15L, 1L, 1L, 1L, 1L, 1L, 98L, 1L, 6L, 3L, 2L, 1L, 315L, 1L, 1L,
6L, 13L, 1L, 59L, 2L, 3L, 1L, 1L, 1L, 1L, 1L, 4L, 2L, 90L, 1L,
4L, 1L, 1L, 1L, 1L, 2L, 7L, 1L, 235L, 1L, 1L, 1L, 2L, 53L, 72L,
18L, 3L, 2L, 1L, 1L, 68L, 1L, 1L, 4L, 2L, 1L, 2L, 1L, 1L, 241L,
1L, 1L, 4L, 9L, 37L, 1L, 1L, 66L, 1L, 1L, 7L, 5L, 4L, 2L, 1L,
2L, 197L, 47L, 39L, 19L, 1L), Fuentes = structure(c(3L, 5L, 6L,
6L, 4L, 5L, 5L, 5L, 5L, 7L, 7L, 1L, 6L, 7L, 5L, 5L, 4L, 5L, 5L,
5L, 5L, 5L, 5L, 6L, 7L, 3L, 5L, 6L, 6L, 5L, 6L, 5L, 5L, 5L, 5L,
7L, 7L, 6L, 1L, 6L, 5L, 5L, 4L, 5L, 5L, 4L, 6L, 5L, 5L, 5L, 5L,
7L, 3L, 5L, 6L, 6L, 4L, 6L, 5L, 5L, 4L, 4L, 5L, 7L, 7L, 6L, 7L,
5L, 4L, 5L, 4L, 2L, 2L, 6L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 4L, 6L,
4L, 5L, 5L, 5L, 5L, 4L, 5L, 7L, 7L, 1L, 6L, 7L, 5L, 5L, 4L, 5L,
5L, 4L, 2L, 2L, 5L, 5L, 5L, 4L, 5L, 4L, 5L, 6L, 7L, 3L, 6L, 6L,
5L, 5L, 5L, 5L, 7L, 7L, 1L, 6L, 7L, 5L, 5L, 7L, 5L, 4L, 2L, 2L,
5L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 4L, 6L, 4L, 4L, 5L, 5L,
7L, 7L, 1L, 6L, 5L, 5L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 2L, 5L, 5L,
5L, 4L, 5L, 6L, 7L, 3L, 5L, 6L, 6L, 5L, 6L, 5L, 5L, 5L, 5L, 5L,
5L, 7L, 7L, 1L, 6L, 5L, 5L, 5L, 7L, 5L, 5L, 7L, 4L, 5L, 5L, 4L,
2L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 5L,
6L, 4L, 4L, 4L, 6L, 4L, 4L, 4L, 5L, 5L, 4L, 5L, 5L, 5L, 4L, 5L,
7L, 7L, 1L, 6L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 6L, 7L, 3L, 6L, 6L, 4L, 4L, 6L, 4L, 4L, 5L, 4L, 5L, 5L,
7L, 7L, 5L, 6L, 5L, 5L, 7L, 7L, 5L, 5L, 5L, 5L, 6L, 4L, 5L, 2L,
2L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 5L, 5L, 6L, 4L, 6L, 4L,
4L, 4L, 5L, 4L, 5L, 4L, 5L, 7L, 7L, 6L, 6L, 7L, 5L, 5L, 5L, 5L,
4L, 2L, 5L, 5L, 5L, 4L, 4L, 5L, 5L, 6L, 7L, 3L, 5L, 5L, 6L, 6L,
6L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 7L, 7L, 6L, 5L, 5L, 7L, 5L, 4L,
5L, 4L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 5L,
6L, 6L, 6L, 4L, 4L, 5L, 5L, 4L, 5L, 7L, 7L, 1L, 6L, 5L, 7L, 5L,
5L, 4L, 5L, 5L, 4L, 6L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 5L, 6L, 6L,
6L, 4L, 6L, 5L, 4L, 5L, 4L, 5L, 7L, 7L, 4L, 5L, 7L, 7L, 5L, 1L,
6L, 5L, 7L, 5L, 5L, 4L, 5L, 4L, 2L, 2L, 6L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 6L, 7L, 3L, 6L, 4L, 6L, 4L, 4L, 5L, 5L, 4L, 4L, 5L, 4L,
5L, 7L, 7L, 1L, 6L, 5L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 6L, 5L, 5L,
5L, 5L, 5L, 6L, 7L, 3L, 6L, 6L, 5L, 5L, 4L, 5L, 4L, 5L, 7L, 7L,
6L, 5L, 5L, 7L, 5L, 5L, 4L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 6L, 7L,
3L, 6L, 6L, 4L, 6L, 4L, 4L, 5L, 5L, 5L, 7L, 1L, 6L, 5L, 5L, 5L,
5L, 5L, 5L, 4L, 6L, 5L, 5L, 4L, 5L, 6L, 3L, 6L, 6L, 4L, 6L, 5L,
4L, 4L, 5L, 4L, 5L, 5L, 7L, 7L, 6L, 1L, 6L, 5L, 5L, 7L, 5L, 5L,
4L, 2L, 5L, 5L, 5L, 5L, 5L, 4L, 6L, 7L, 3L, 6L, 4L, 4L, 6L, 4L,
4L, 5L, 5L, 5L, 5L, 5L, 4L, 5L, 7L, 1L, 6L, 5L, 7L, 5L, 5L, 4L,
5L, 5L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 5L, 5L, 5L, 5L,
6L, 7L, 3L, 6L, 6L, 4L, 6L, 4L, 4L, 5L, 5L, 7L, 4L, 5L, 7L, 7L,
1L, 6L, 5L, 5L, 5L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 5L, 5L, 2L, 2L,
6L, 5L, 5L, 5L, 5L, 5L, 6L, 3L, 5L, 6L, 4L, 4L, 4L, 6L, 4L, 4L,
4L, 5L, 5L, 4L, 5L, 7L, 7L, 5L, 1L, 6L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 4L, 5L, 5L, 5L, 4L, 5L, 4L, 5L, 5L, 5L, 5L, 4L, 4L, 5L, 5L,
5L, 6L, 7L, 3L, 5L, 6L, 6L, 4L, 5L, 4L, 5L, 7L, 7L, 6L, 5L, 7L,
5L, 5L, 4L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 3L, 6L, 6L, 6L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 7L, 1L, 6L, 5L, 5L, 5L, 5L,
4L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 6L, 3L, 5L, 5L,
6L, 5L, 5L, 5L, 4L, 5L, 5L, 7L, 7L, 6L, 5L, 5L, 7L, 5L, 5L, 7L,
5L, 5L, 6L, 4L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 6L, 3L, 6L, 6L, 4L,
6L, 5L, 4L, 5L, 5L, 7L, 7L, 5L, 1L, 6L, 5L, 5L, 5L, 5L, 5L, 4L,
4L, 5L, 2L, 5L, 5L, 5L, 5L, 4L, 4L, 5L, 2L, 4L, 5L, 4L, 6L, 3L,
5L, 6L, 6L, 5L, 5L, 5L, 5L, 7L, 7L, 6L, 5L, 7L, 5L, 7L, 5L, 5L,
5L, 2L, 5L, 2L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 5L, 5L, 4L, 5L,
7L, 7L, 1L, 6L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 2L, 2L, 5L, 6L, 7L,
3L, 6L, 6L, 5L, 5L, 5L, 7L, 5L, 7L, 7L, 5L, 5L, 6L, 5L, 5L, 5L,
5L, 5L, 4L, 5L, 5L, 4L, 5L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 6L, 5L, 3L, 6L, 6L, 4L, 6L, 5L, 5L, 5L, 5L, 5L, 7L,
7L, 5L, 1L, 6L, 5L, 5L, 7L, 5L, 5L, 4L, 5L, 5L, 5L, 4L, 5L, 6L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 3L, 6L, 6L, 4L, 6L, 5L, 5L, 7L,
7L, 6L, 5L, 5L, 7L, 5L, 5L, 5L, 5L, 5L, 4L, 2L, 2L, 5L, 5L, 5L,
5L, 5L, 5L, 6L, 7L, 3L, 6L, 4L, 6L, 5L, 4L, 5L, 5L, 4L, 5L, 7L,
7L, 5L, 1L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 6L, 3L,
6L, 6L, 4L, 5L, 5L, 7L, 7L, 1L, 6L, 7L, 5L, 5L, 5L, 5L, 5L, 5L,
4L, 2L, 2L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 6L, 5L, 5L, 5L, 5L,
7L, 7L, 5L, 6L, 7L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 4L, 4L, 5L,
5L, 5L, 4L, 5L, 6L, 3L, 6L, 6L, 4L, 6L, 4L, 5L, 5L, 5L, 5L, 7L,
6L, 6L, 5L, 5L, 7L, 5L, 5L, 5L, 5L, 5L, 4L, 2L, 2L, 6L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 5L, 6L, 4L, 4L, 4L, 5L, 6L, 4L,
4L, 5L, 4L, 5L, 4L, 5L, 7L, 7L, 1L, 6L, 5L, 5L, 5L, 5L, 7L, 5L,
5L, 5L, 5L, 5L, 5L, 4L, 4L, 2L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
6L, 7L, 3L, 5L, 6L, 6L, 5L, 4L, 5L, 5L, 7L, 6L, 5L, 5L, 5L, 5L,
2L, 2L, 5L, 6L, 3L, 5L, 5L, 6L, 4L, 6L, 5L, 4L, 5L, 7L, 7L, 1L,
6L, 5L, 7L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 7L,
3L, 6L, 6L, 6L, 4L, 5L, 5L, 5L, 5L, 7L, 7L, 6L, 5L, 5L, 5L, 5L,
5L, 2L, 2L, 6L, 3L, 6L, 4L, 6L, 4L, 5L, 4L, 5L, 7L, 1L, 6L, 5L,
5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 2L, 5L, 6L, 7L, 3L, 6L, 6L, 5L,
5L, 5L, 7L, 7L, 6L, 5L, 5L, 5L, 5L, 5L, 4L, 5L, 2L, 2L, 5L, 5L,
5L, 6L, 3L, 6L, 4L, 6L, 4L, 5L, 5L, 4L, 4L, 5L, 5L, 7L, 7L, 5L,
1L, 6L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 4L, 5L, 6L, 5L, 5L, 6L,
7L, 3L, 6L, 4L, 5L, 6L, 5L, 5L, 5L, 5L, 4L, 5L, 7L, 7L, 6L, 5L,
5L, 7L, 5L, 5L, 5L, 4L, 5L, 5L, 4L, 2L, 2L, 5L, 5L, 5L, 5L, 4L,
6L, 3L, 6L, 6L, 6L, 4L, 5L, 5L, 5L, 4L, 5L, 7L, 7L, 6L, 5L, 5L,
5L, 4L, 5L, 5L, 4L, 5L, 5L, 5L, 6L, 3L, 5L, 5L, 6L, 6L, 5L, 4L,
5L, 5L, 7L, 7L, 6L, 5L, 5L, 5L, 5L, 4L, 5L, 4L, 2L, 2L, 5L, 5L,
5L, 5L, 5L, 6L, 5L, 3L, 6L, 4L, 5L, 5L, 5L, 7L, 7L, 5L, 1L, 6L,
5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 4L, 5L, 5L, 6L, 7L, 3L, 5L, 6L,
6L, 5L, 5L, 5L, 5L, 7L, 6L, 7L, 5L, 5L, 5L, 5L, 4L, 2L, 2L, 5L,
7L, 3L, 6L, 4L, 5L, 6L, 5L, 5L, 5L, 7L, 6L, 5L, 5L, 5L, 4L, 5L,
5L, 4L, 5L, 5L, 6L, 3L, 6L, 6L, 5L, 1L, 6L, 5L, 5L, 4L, 5L, 4L,
2L, 2L, 5L, 5L, 5L, 5L, 6L, 3L, 6L, 6L, 5L, 5L, 5L, 7L, 7L, 5L,
6L, 5L, 5L, 5L, 5L, 5L, 4L, 6L, 3L, 6L, 6L, 5L, 5L, 7L, 7L, 6L,
5L, 5L, 5L, 5L, 5L, 4L, 2L, 2L, 6L, 3L, 6L, 5L, 6L, 4L, 4L, 5L,
7L, 7L, 1L, 6L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 3L, 6L, 6L, 5L,
5L, 5L, 5L, 7L, 6L, 5L, 5L, 4L, 5L, 4L, 2L, 2L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 4L, 6L, 7L, 3L, 5L, 6L, 6L, 4L, 5L, 5L, 5L, 4L,
4L, 5L, 7L, 7L, 6L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 4L, 2L, 5L, 5L,
5L, 4L, 4L, 5L, 5L, 4L, 6L, 3L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 7L,
5L, 6L, 5L, 5L, 7L, 5L, 5L, 5L, 2L, 2L, 5L, 5L, 5L, 5L, 5L, 6L,
3L, 6L, 4L, 4L, 5L, 4L, 5L, 6L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 5L,
4L, 2L, 5L, 5L, 4L, 4L, 6L, 3L, 6L, 6L, 5L, 5L, 5L, 7L, 6L, 5L,
5L, 5L, 5L, 5L, 4L, 2L, 5L, 5L, 5L, 5L, 5L, 6L, 7L, 3L, 6L, 4L,
6L, 5L, 5L, 5L, 7L, 5L, 1L, 6L, 7L, 5L, 5L, 4L, 5L, 5L, 4L, 5L,
5L, 5L, 6L, 7L, 3L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 6L, 5L, 5L, 5L,
5L, 4L, 5L, 2L, 5L, 5L, 5L, 5L, 6L, 3L, 5L, 4L, 4L, 6L, 4L, 5L,
5L, 5L, 7L, 6L, 5L, 5L, 4L, 5L, 5L, 4L, 4L, 5L, 5L, 5L, 3L, 6L,
6L, 5L, 5L, 7L, 6L, 5L, 5L, 5L, 5L, 7L, 5L, 4L, 2L, 5L, 5L, 5L,
5L, 5L, 6L, 7L, 3L, 4L, 6L, 5L, 5L, 4L, 5L, 5L, 7L, 1L, 6L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 5L, 6L, 3L, 6L, 6L, 6L, 5L, 5L,
5L, 5L, 7L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 3L, 6L, 4L, 6L, 5L,
5L, 7L, 7L, 5L, 6L, 5L, 5L, 5L, 5L), .Label = c("Adwords", "Campañas",
"Directo", "Email", "Referencias", "SEO", "Social Media"), class = "factor")), .Names = c("date",
"sessions", "Fuentes"), class = "data.frame", row.names = c(NA,
-1724L))
我的數據后的匯總功能：
Fuentes sessions
1 Adwords 71
2 Campa�as 280
3 Directo 11610
4 Email 437
5 Referencias 13143
6 SEO 39837
7 Social Media 5981
為什么我的閃亮代碼無法正確顯示我的情節？
1）在Shiny中使用時，標簽看起來像是模糊的：
在繪制之前進行總結（請參見下面的代碼）：
server.R文件：
library(ggplot2)
library(dplyr)
require(scales)
Visitas_Por_Fuente <- read.csv("D:\\RCoursera\\Movistar-App-2\\Visitas_Por_Fuente_Dic.csv")
labelsF = c("Directo", "Email", "Referencias", "SEO", "Social Media", "Campañas", "Adwords")
Visitas_Por_Fuente$date <- as.Date(Visitas_Por_Fuente$date)
shinyServer(
function(input, output) {
output$VisitasFuente <- renderPlot({
# Filter the data based on user selection month
date_seq <- seq(input$dates[1], input$dates[2], by = "day")
VisitasData <- filter(Visitas_Por_Fuente, date %in% date_seq & Fuentes %in% labelsF)
VisitasData %>% group_by(Fuentes) %>%
summarise(sessions = sum(sessions))
ggplot(VisitasData, aes(factor(Fuentes), sessions, fill = Fuentes)) +
geom_bar(stat="identity", position = "dodge") +
geom_text(aes(label = comma(sessions)), position=position_dodge(width=0.9), vjust=-0.25) +
scale_fill_manual(breaks = c("0", "1", "3", "6", "9", "12", "15"),
labels = labelsF,
values = c("#E69F00", "#56B4E9", "#009E73",
"#F0E442", "#0072B2", "#A082F8", "#F072A2"))
})
}）
2）然后我使用相同的代碼，但不是在閃亮的內，只是ggplot2代碼：
ggplot(VisitasData, aes(factor(Fuentes), sessions, fill = Fuentes)) +
geom_bar(stat="identity", position = "dodge") +
geom_text(aes(label = comma(sessions)), position=position_dodge(width=0.9), vjust=-0.25) +
scale_fill_manual(breaks = c("0", "1", "3", "6", "9", "12", "15"),
labels = labelsF,
values = c("#E69F00", "#56B4E9", "#009E73",
"#F0E442", "#0072B2", "#A082F8", "#F072A2"))
並得到我所需要的：
我還嘗試了使用反應性函數（如注釋中的建議），但得到：
Error : ggplot2 doesn't know how to deal with data of class reactive
用谷歌搜索發現：
但是現在，打印一張空白紙：
這是我的代碼與反應函數：
function(input, output) {
dataSeq <- reactive({
date_seq <- seq(input$dates[1], input$dates[2], by = "day")
})
VisitasData <- reactive({
VisitasData <- filter(Visitas_Por_Fuente, date %in% dataSeq & Fuentes %in% labelsF)
VisitasData %>% group_by(Fuentes) %>%
summarise(sessions = sum(sessions))
})
output$VisitasFuente <- renderPlot({
# Bar graph using ggplot2 library
ggplot(ggplot(selectedData(VisitasData), aes(factor(VisitasData$Fuentes), VisitasData$sessions,
fill = Fuentes)) +
geom_bar(stat="identity", position = "dodge") +
geom_text(aes(label = comma(sessions)), position=position_dodge(width=0.9), vjust=-0.25) +
scale_fill_manual(breaks = c("0", "1", "3", "6", "9", "12", "15"),
labels = labelsF,
values = c("#E69F00", "#56B4E9", "#009E73",
"#F0E442", "#0072B2", "#A082F8", "#F072A2"))
})
})
1 個解決方案
解決方案1
1 已采納 2015-02-08 05:45:05
假設您想在首次通話中顯示這些號碼
Fuentes sessions
1 Adwords 71
2 Campa�as 280
3 Directo 11610
4 Email 437
5 Referencias 13143
6 SEO 39837
7 Social Media 5981
您在這里犯了一個小錯誤：
VisitasData %>% group_by(Fuentes) %>%
summarise(sessions = sum(sessions))
您創建了一個新的數據框，但未將其分配給任何對象。 您想要的是：
VisitasData <- VisitasData %>% group_by(Fuentes) %>%
summarise(sessions = sum(sessions))
然后，您無需做任何反應，只需使用您在上面首次發布時所執行的代碼即可。
library(ggplot2)
library(dplyr)
require(scales)
Visitas_Por_Fuente <- read.csv("D:\\RCoursera\\Movistar-App-2\\Visitas_Por_Fuente_Dic.csv")
labelsF = c("Directo", "Email", "Referencias", "SEO", "Social Media", "Campañas", "Adwords")
Visitas_Por_Fuente$date <- as.Date(Visitas_Por_Fuente$date)
shinyServer(
function(input, output) {
output$VisitasFuente <- renderPlot({
# Filter the data based on user selection month
date_seq <- seq(input$dates[1], input$dates[2], by = "day")
VisitasData <- filter(Visitas_Por_Fuente, date %in% date_seq & Fuentes %in% labelsF)
VisitasData <- VisitasData %>% group_by(Fuentes) %>%
summarise(sessions = sum(sessions))
# Bar graph using ggplot2 library
ggplot(VisitasData, aes(factor(Fuentes), sessions, fill = Fuentes)) +
geom_bar(stat="identity", position = "dodge") +
geom_text(aes(label = comma(sessions)), position=position_dodge(width=0.9), vjust=-0.25) +
scale_fill_manual(breaks = c("0", "1", "3", "6", "9", "12", "15"),
labels = labelsF,
values = c("#E69F00", "#56B4E9", "#009E73",
"#F0E442", "#0072B2", "#A082F8", "#F072A2"))
})
})
這是您想要的嗎？
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