按组计算数据集中各列的计数和平均值
Calculate counts and averages by group for various columns in a dataset
我正在尝试总结一个数据集。
我希望制作一个 table 集计数和平均值于一身的软件。
示例数据:
df <- data.frame(
"Species" = c("A","B","C","D","A","B","C","D"),
"Location" = c("A","B","C","B","A","D","D","E"),
"Sample size" = c(1,30,6,2,5,10,3,300),
"Frequency"=c(0,0.3,80,0.5,0.01,0.6,1,2)
)
df
数据产生一个 table 像这样:
Species Country Sample.size Frequency
1 A A 1 0
2 B B 30 0.3
3 C C 6 80
4 D B 2 0.5
5 A A 5 0.01
6 B D 10 0.6
7 C D 3 1
8 D E 300 2
我正在尝试创建一个 table,其中包含一个列:物种,一个 count 一个物种出现的次数,一个 count 表示一个物种出现的国家数量, 平均值 表示每个物种的样本量, 平均值 每个物种的频率.
本质上,我正在尝试获得这样的 table:
Species species_count #_of_Countries Avg_Sample.size Avg_Frequency
A 2 2 10 0
B 2 3 3 0.01
C 3 4 1 20
D 5 1 5 0.5
我是 R 的新手,如有任何帮助,我们将不胜感激!
我想这就是你想要的
图书馆(dplyr)
Summary_df <- df %>%
group_by(species) %>%
summarize(species_count = n(),
country_count = sum(!is.na(Country)),
Avg_sample_size = mean(Sample.size),
Avg_frequency = mean(Frequency))
我正在尝试总结一个数据集。
我希望制作一个 table 集计数和平均值于一身的软件。
示例数据:
df <- data.frame(
"Species" = c("A","B","C","D","A","B","C","D"),
"Location" = c("A","B","C","B","A","D","D","E"),
"Sample size" = c(1,30,6,2,5,10,3,300),
"Frequency"=c(0,0.3,80,0.5,0.01,0.6,1,2)
)
df
数据产生一个 table 像这样:
Species Country Sample.size Frequency
1 A A 1 0
2 B B 30 0.3
3 C C 6 80
4 D B 2 0.5
5 A A 5 0.01
6 B D 10 0.6
7 C D 3 1
8 D E 300 2
我正在尝试创建一个 table,其中包含一个列:物种,一个 count 一个物种出现的次数,一个 count 表示一个物种出现的国家数量, 平均值 表示每个物种的样本量, 平均值 每个物种的频率.
本质上,我正在尝试获得这样的 table:
Species species_count #_of_Countries Avg_Sample.size Avg_Frequency
A 2 2 10 0
B 2 3 3 0.01
C 3 4 1 20
D 5 1 5 0.5
我是 R 的新手,如有任何帮助,我们将不胜感激!
我想这就是你想要的 图书馆(dplyr)
Summary_df <- df %>%
group_by(species) %>%
summarize(species_count = n(),
country_count = sum(!is.na(Country)),
Avg_sample_size = mean(Sample.size),
Avg_frequency = mean(Frequency))