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[英]How to apply ifelse function across multiple columns and create new columns in R
[英]How to apply a function to multiple columns to create multiple new columns in R?
我有這個序列列表aqi_range和一個數據幀df :
aqi_range = list(0:50,51:100,101:250)
df
PM10_mean PM10_min PM10_max PM2.5_mean PM2.5_min PM2.5_max
1 85.6 3 264 75.7 3 240
2 105. 6 243 76.4 3 191
3 95.8 19 287 48.4 8 134
4 85.5 50 166 64.8 32 103
5 55.9 24 117 46.7 19 77
6 37.5 6 116 31.3 3 87
7 26 5 69 15.5 3 49
8 82.3 34 169 49.6 25 120
9 170 68 272 133 67 201
10 254 189 323 226 173 269
現在我已經創建了這兩個非常簡單的函數,我想將它們應用到這個數據框來計算每種污染物的AQI=空氣質量指數。
#a = column from a dataframe **PM10_mean, PM2.5_mean**
#b = list of sequences defined above
min_max_diff <- function(a,b){
for (i in b){
if (a %in% i){
min_val = min(i)
max_val = max(i)
return (max_val - min_val)
}}}
#a = column from a dataframe **PM10_mean, PM2.5_mean**
#b = list of sequences defined above
c_low <- function(a,b){
for (i in b){
if (a %in% i){
min_val = min(i)
return(min_val)
}
}}
基本上,第一個函數“min_max_diff”獲取列 df$PM10_mean / df$PM2.5_mean 的值並在列表“aqi_range”中檢查它,然后返回一個特定值(它所在序列的最小值和最大值的差異)可用的)。 類似地,第二個函數“c_low”只返回序列的最小值。
我想將這種操作(下面定義的公式)應用於 PM10_mean 列以創建新列 PM10_AQI:
df$PM10_AQI = min_max_diff(df$PM10_mean,aqi_range) / (df$PM10_max - df$PM10_min) / * (df$PM10_mean - df$PM10_min) + c_low(df$PM10_mean,aqi_range)
我希望它能正確解釋。
如果您的問題只是如何計算數據幀中幾列的給定轉換,您可以編寫一個 for 循環,使用字符串轉換函數構造轉換中涉及的每個變量的名稱(在這種情況下sub()
很有用) ,並使用[
表示法(與$
表示法相反——因為[
表示法接受字符串來指定列)引用數據框中的列。
下面我展示了一個帶有 3 個觀察值的小樣本數據的代碼示例:
(請注意,我修改了 AQI 范圍值的定義(現在我只是定義了范圍變化的中斷點——假設它們都是整數),並且你的函數min_max_diff()
和c_low()
被折疊成一個返回找到值的 AQI 范圍的最小值和最大值 - 再次假設 AQI 值是整數值)
# Definition of the AQI ranges (which are assumed to be based on integer values)
# Note that if the number of AQI ranges is k, the number of breaks is k+1
# Each break value defines the minimum of the range
# The maximum of each range is computed as the "minimum of the NEXT range" - 1
# (again this assumes integer values in AQI ranges)
# The values (e.g. PM10_mean) whose AQI range is searched for are assumed
# to NOT be larger than or equal to the largest break value.
aqi_range_breaks = c(0, 51, 101, 251)
# Example data (top 3 rows of the data frame you provided)
df = data.frame(PM10_mean=c(85.6, 105.0, 95.8),
PM10_min=c(3, 6, 19),
PM10_max=c(264, 243, 287),
PM2.5_mean=c(75.7, 76.4, 48.4),
PM2.5_min=c(3, 3, 8),
PM2.5_max=c(240, 191, 134))
# Function that returns the minimum and maximum AQI values
# of the AQI range where the given values are found
# `values`: array of values that are searched for in the AQI ranges
# defined by the second parameter.
# `aqi_range_breaks`: breaks defining the minimum values of each AQI range
# plus one last value defining a value never attained by `values`.
# (all values in this parameter defining the AQI ranges are assumed integer values)
find_aqi_range_min_max <- function(values, aqi_range_breaks){
aqi_range_groups = findInterval(values, aqi_range_breaks)
return( list(min=aqi_range_breaks[aqi_range_groups],
max=aqi_range_breaks[aqi_range_groups + 1] - 1))
}
# Run the variable transformation on the selected `_mean` columns
vars_mean = c("PM10_mean", "PM2.5_mean")
for (vmean in vars_mean) {
vmin = sub("_mean$", "_min", vmean)
vmax = sub("_mean$", "_max", vmean)
vaqi = sub("_mean$", "_AQI", vmean)
aqi_range_min_max = find_aqi_range_min_max(df[,vmean], aqi_range_breaks)
df[,vaqi] = (aqi_range_min_max$max - aqi_range_min_max$min) /
(df[,vmax] - df[,vmin]) / (df[,vmean] - df[,vmin]) +
aqi_range_min_max$min
}
請注意findInterval()
函數如何用於查找值數組所在的范圍。 這是使您的轉換適用於數據框列的關鍵。
此過程的預期輸出是:
PM10_mean PM10_min PM10_max PM2.5_mean PM2.5_min PM2.5_max PM10_AQI PM2.5_AQI
1 85.6 3 264 75.7 3 240 51.00227 51.002843893
2 105.0 6 243 76.4 3 191 101.00635 51.003550930
3 95.8 19 287 48.4 8 134 51.00238 0.009822411
請檢查計算 AQI 的公式,因為其中存在語法錯誤(查找/ *
,我已在代碼的公式中將其替換為/
)。
請注意,在sub()
使用的正則表達式中使用$
來匹配字符串"_mean"
僅當"_mean"
字符串出現在變量名稱的末尾時才使用它來替換字符串。
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