[英]How do I generate a frequency table on R via dplyr and plot its values with ggplot?
我需要從兩個分類變量列中做一個頻率表,其中一個是 5 歲年齡組,另一個是來自 brfss2013 數據集的健康狀況(五個州),我從中提取了感興趣的列:
> hlthgrpq1 <- brfss2013 %>% select(genhlth, X_ageg5yr)
因此生成了一個兩列框架,2 個變量的 491775 個觀察值。
genhlth X_ageg5yr
1 Fair Age 60 to 64
2 Good Age 50 to 54
3 Good Age 55 to 59
4 Very good Age 60 to 64
5 Good Age 65 to 69
我可以使用 'by' 函數生成一個匯總表:
> by(hlthgrpq1$genhlth, hlthgrpq1$X_ageg5yr, summary)
hlthgrpq1$X_ageg5yr: Age 18 to 24
Excellent Very good Good Fair Poor NA's
6896 10266 7795 1873 303 69
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 25 to 29
Excellent Very good Good Fair Poor NA's
5779 8488 6521 1751 325 46
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 30 to 34
Excellent Very good Good Fair Poor NA's
6412 9958 7977 2295 496 75
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 35 to 39
Excellent Very good Good Fair Poor NA's
6366 10169 8236 2637 638 61
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 40 to 44
Excellent Very good Good Fair Poor NA's
6689 11130 9193 3334 1067 95
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 45 to 49
Excellent Very good Good Fair Poor NA's
7051 12278 10611 4343 1815 112
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 50 to 54
Excellent Very good Good Fair Poor NA's
8545 15254 13761 6354 3120 139
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 55 to 59
Excellent Very good Good Fair Poor NA's
8500 16759 15394 7643 3998 197
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 60 to 64
Excellent Very good Good Fair Poor NA's
8283 16825 16266 8101 3955 229
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 65 to 69
Excellent Very good Good Fair Poor NA's
7479 15764 15600 7749 3200 205
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 70 to 74
Excellent Very good Good Fair Poor NA's
5491 11943 13125 6491 2721 196
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 75 to 79
Excellent Very good Good Fair Poor NA's
3320 8501 10128 5545 2426 173
----------------------------------------------------------------------------------------------------------------
hlthgrpq1$X_ageg5yr: Age 80 or older
Excellent Very good Good Fair Poor NA's
3697 10285 14400 8116 3695 322
這就是我陷入困境的地方。 我已經嘗試了幾個小時試圖到達這里:
謝謝你的幫助。
(這是針對特定任務的,因此我只能使用 dplyr 和 ggplot2,因此,沒有 reshape2 或 tidyr。)
首先:對於將來的發布,最好始終包含示例數據。 請參閱此處如何提供包含樣本數據的最小可重現示例/嘗試。
基礎 R 中的解決方案。
as.data.frame.matrix(t(table(df)));
# Fair Good Very good
#Age 50 to 54 0 1 0
#Age 55 to 59 0 1 0
#Age 60 to 64 1 0 1
#Age 65 to 69 0 1 0
或者像這樣的tidyverse
方法?
library(tidyverse);
df %>% count(genhlth, X_ageg5yr) %>% spread(genhlth, n);
## A tibble: 4 x 4
# X_ageg5yr Fair Good `Very good`
# <fct> <int> <int> <int>
#1 Age 50 to 54 NA 1 NA
#2 Age 55 to 59 NA 1 NA
#3 Age 60 to 64 1 NA 1
#4 Age 65 to 69 NA 1 NA
或者,如果您堅持只使用dplyr
而不是tidyr
,您可以這樣做:
df2 <- df %>%
count(genhlth, X_ageg5yr);
df2 <- as.data.frame.matrix(xtabs(n ~ X_ageg5yr + genhlth, data = df2));
# Fair Good Very good
#Age 50 to 54 0 1 0
#Age 55 to 59 0 1 0
#Age 60 to 64 1 0 1
#Age 65 to 69 0 1 0
這基本上歸結為從寬到長的重新格式化,因此圍繞該主題進行了大量討論(例如here )。
df <- read.table(text =
"genhlth X_ageg5yr
Fair 'Age 60 to 64'
Good 'Age 50 to 54'
Good 'Age 55 to 59'
'Very good' 'Age 60 to 64'
Good 'Age 65 to 69'", header = T)
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