计算 R 中数据框列的平均值，忽略 NA 和 0 值

Question

我在 r 中有一个数据框，它有一个 date_time 列（每 10 分钟一次观察）和另一列 lux ..我想计算整个列的平均 lux，忽略 NA 和 0 值。

我还想计算平均每日勒克斯..

我该怎么做？

Answer 1

如果没有示例数据集，我只能通过提供来自另一个数据集的工作示例来提供帮助。复制粘贴以下内容，并将文件命名为：daily-min-temperatures.txt。

"Date","Temp"
"1981-01-10",20.0
"1981-01-11",0
"1981-01-12",13.3
"1981-01-13",NA
"1981-01-14",21.5
"1981-02-09",25.0
"1981-02-10",0
"1981-02-11",13.7
"1981-02-12",NA
"1981-03-08",16.3
"1981-03-09",16.1
"1981-03-10",11.8
"1981-03-11",12.2
"1981-03-12",0
"1981-03-13",0
"1981-03-14",NA
"1981-03-15",10.6
"1981-03-16",11.7

数据框与您的相似：不是每 10 分钟记录一次，而是每天的温度记录一些 NA 和 0。

这里是工作示例。通过一些调整，您可以根据自己的情况进行调整。

daily_min_temperatures <- read.csv("daily-min-temperatures.txt") #load sample dataframe
daily_min_temperatures$Date <- as.Date(daily_min_temperatures$Date) #format Date field

str(daily_min_temperatures) #view the structure of the loaded dataframe
summary(daily_min_temperatures) #view the summary of the loaded dataframe

library(tidyverse) #load the tidyverse library to get some nice to have tools :)
#part 1: average temp for full dataframe
na.omit(daily_min_temperatures) %>% #remove the NAs entries from the dataframe with the na.omit statement
filter(Temp != 0) %>% #remove the 0s entries from the dataframe with the filter statement
summarise(mean = mean(Temp)) #calculate the Temp mean

#part 2: average temp for monthly dataframe
na.omit(daily_min_temperatures) %>% #remove the NAs entries from the dataframe with the na.omit statement
filter(Temp != 0) %>% #remove the 0s entries from the dataframe with the filter statement
group_by(Grouped_Date = format(Date, format="%m/%Y")) %>% #Group by month year
summarise(mean = mean(Temp)) #calculate the Temp mean for each group