在 R 数据框中没有值的地方输入 0答案

【问题标题】：Input 0 where there is no value in R data frame在 R 数据框中没有值的地方输入 0
【发布时间】：2020-01-09 00:29:16
【问题描述】：

我想获得如下所示的 data.frame，但包括每个主题的所有年份。我制作的这个按年份计算每个主题的项目数，但是当某年没有项目时，它只是不会为该特定主题创建该行，并且在最终图表中为空白。谁能告诉我如何为没有价值的主题添加 Count == 0 的缺失年份？

dtd2 <- structure(list(Topic = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L), .Label = c("Topic 1", 
"Topic 10", "Topic 11", "Topic 12", "Topic 2", "Topic 3", "Topic 4", 
"Topic 5", "Topic 6", "Topic 7", "Topic 8", "Topic 9"), class = "factor"), 
    Year = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 2L, 
    3L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
    3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
    9L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 
    8L, 9L, 1L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 6L, 7L, 8L, 
    9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 
    6L, 7L, 8L, 9L, 2L, 3L, 4L, 5L, 6L, 7L, 8L), .Label = c("2011", 
    "2012", "2013", "2014", "2015", "2016", "2017", "2018", "2019"
    ), class = "factor"), Count = c(3L, 3L, 3L, 5L, 5L, 11L, 
    17L, 14L, 4L, 1L, 1L, 4L, 2L, 3L, 9L, 4L, 2L, 1L, 3L, 4L, 
    5L, 18L, 23L, 19L, 15L, 1L, 5L, 6L, 8L, 11L, 17L, 7L, 1L, 
    3L, 6L, 4L, 20L, 21L, 18L, 12L, 3L, 1L, 1L, 2L, 5L, 5L, 11L, 
    5L, 2L, 1L, 1L, 2L, 2L, 5L, 7L, 23L, 9L, 1L, 1L, 2L, 3L, 
    6L, 4L, 9L, 8L, 1L, 1L, 6L, 2L, 3L, 3L, 1L, 3L, 2L, 5L, 7L, 
    11L, 11L, 28L, 11L, 2L, 1L, 2L, 2L, 5L, 6L, 5L, 16L, 3L, 
    4L, 2L, 2L, 7L, 6L, 8L, 6L)), row.names = c(NA, -96L), class = "data.frame")

ggplot(dtd2, aes(x = Year, y = Count, colour = Topic, group = Topic)) + geom_point() + geom_line() + labs(x = "Year", y = NULL, title = "Timeline")

【问题讨论】：

标签： r count

【解决方案1】：

我们可以使用tidyr 中的complete 来添加缺失的年份并用0 填充Count 值。

tidyr::complete(dtd2, Topic, Year = unique(Year), fill = list(Count = 0))

#A tibble: 108 x 3
#   Topic    Year  Count
#   <fct>    <fct> <dbl>
# 1 Topic 1  2011      3
# 2 Topic 1  2012      3
# 3 Topic 1  2013      3
# 4 Topic 1  2014      5
# 5 Topic 1  2015      5
# 6 Topic 1  2016     11
# 7 Topic 1  2017     17
# 8 Topic 1  2018     14
# 9 Topic 1  2019      4
#10 Topic 10 2011      0
# … with 98 more rows

并在ggplot2 中使用它，以便连接线

library(ggplot2)
 tidyr::complete(dtd2, Topic, Year = unique(Year), fill = list(Count = 0)) %>%
   ggplot(., aes(x = Year, y = Count, colour = Topic, group = Topic)) + 
   geom_point() + geom_line() + labs(x = "Year", y = NULL, title = "Timeline")

【讨论】：

【解决方案2】：

时间序列方法可以是

library(tidyverse)
library(lubridate)
#> 
#> Attaching package: 'lubridate'
#> The following object is masked from 'package:base':
#> 
#>     date
library(tsibble)
#> 
#> Attaching package: 'tsibble'
#> The following objects are masked from 'package:lubridate':
#> 
#>     interval, new_interval
#> The following object is masked from 'package:dplyr':
#> 
#>     id


dtd2 <- structure(list(Topic = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
  1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
  3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
  5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
  7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 
  10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 
  11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L), .Label = c("Topic 1", 
    "Topic 10", "Topic 11", "Topic 12", "Topic 2", "Topic 3", "Topic 4", 
    "Topic 5", "Topic 6", "Topic 7", "Topic 8", "Topic 9"), class = "factor"), 
  Year = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 2L, 
    3L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
    3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 
    9L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 
    8L, 9L, 1L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 6L, 7L, 8L, 
    9L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L, 2L, 3L, 4L, 5L, 
    6L, 7L, 8L, 9L, 2L, 3L, 4L, 5L, 6L, 7L, 8L), .Label = c("2011", 
      "2012", "2013", "2014", "2015", "2016", "2017", "2018", "2019"
    ), class = "factor"), Count = c(3L, 3L, 3L, 5L, 5L, 11L, 
      17L, 14L, 4L, 1L, 1L, 4L, 2L, 3L, 9L, 4L, 2L, 1L, 3L, 4L, 
      5L, 18L, 23L, 19L, 15L, 1L, 5L, 6L, 8L, 11L, 17L, 7L, 1L, 
      3L, 6L, 4L, 20L, 21L, 18L, 12L, 3L, 1L, 1L, 2L, 5L, 5L, 11L, 
      5L, 2L, 1L, 1L, 2L, 2L, 5L, 7L, 23L, 9L, 1L, 1L, 2L, 3L, 
      6L, 4L, 9L, 8L, 1L, 1L, 6L, 2L, 3L, 3L, 1L, 3L, 2L, 5L, 7L, 
      11L, 11L, 28L, 11L, 2L, 1L, 2L, 2L, 5L, 6L, 5L, 16L, 3L, 
      4L, 2L, 2L, 7L, 6L, 8L, 6L)), row.names = c(NA, -96L), class = "data.frame")
tsibble2 <- dtd2 %>%
  mutate(Year = as_date(str_c(Year,"01",'01'))) %>% 
  as_tsibble(index = Year,key = Topic) %>%
  tsibble::fill_gaps(.full = TRUE) %>%
  group_by_key() %>% 
  index_by(year = Year %>% year) %>% 
  summarise(Count = Count %>% sum(na.rm = T)) %>% 
  as_tibble() %>% 
  mutate(year = year %>% as_factor())

tsibble2 %>% 
  ggplot() +
  aes(x = year,y = Count,color = Topic,group = Topic) +
  geom_line() +
  geom_point()

^{由reprex package (v0.3.0) 于 2020-01-08 创建}

【讨论】：

【解决方案3】：

我们可以使用expand

library(dplyr)
library(tidyr)
library(ggplot2)
dtd2 %>%
    expand(Topic = factor(Topic, levels = gtools::mixedsort(levels(Topic))) ,
                 Year = unique(Year)) %>% 
    left_join(dtd2) %>% 
    mutate(Count = replace_na(Count, 0)) %>%
    ggplot(aes(x = Year, y = Count, colour = Topic, group = Topic)) + 
         geom_point() +
         geom_line() +
         labs(x = "Year", y = NULL, title = "Timeline")

-输出

【讨论】：