我有序列aqi_range和数据框df的列表：
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
现在，我已经创建了这两个非常简单的函数，我希望将此函数应用于此数据框，以计算每种污染物的AQI =空气质量指数。
#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，第一个函数“ min_max_diff”采用列df $ PM10_mean / df $ PM2.5_mean的值，并在列表“ aqi_range”中进行检查，然后返回某个值（该值所在的序列的最小值和最大值之间的差可用）。同样，第二个函数“ c_low”仅返回序列的最小值。
我想对PM10_mean列应用这种操作（下面定义的公式）以创建新列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$PM10_mean,aqi_range)
我希望它能正确解释。
如果您的问题只是如何将给定的转换计算到数据帧中的几列，则可以编写一个for循环，使用字符串转换函数（在这种情况下sub()非常有用）构造转换中涉及的每个变量的名称，使用[表示法（与表示法相反，$因为该[表示法接受字符串来指定列）。
下面，我展示了这样的代码示例，其中包含少量样本数据和3个观察结果：
（请注意，我修改了AQI范围值（现在我只是定义了出现时间点的范围内改变--assuming他们都是整数）的定义，你的功能min_max_diff()和c_low()它们合并为一个单一的函数返回的最小值和最大值找到该值的AQI范围-再次假设AQI值为整数值）
# 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
}
请注意如何使用该findInterval()函数来查找值数组落在的范围。这是使转换适用于数据框列的关键。
该过程的预期输出为：
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
请检查用于计算AQI的公式，因为其中存在语法错误（请查找/ *，/我的代码中的公式已将其替换为）。
请注意，仅在字符串出现在变量名的末尾时，才$使用in中sub()用于匹配字符串的正则表达式"_mean"替换"_mean"字符串。
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