具有条件（针对每个变量）的按时间顺序排列的数据，并根据条件（针对每个变量）在数据帧中循环

发布于 2025-01-20 12:24:24 字数 1022 浏览 1 评论 0原文

我想按时间顺序将降雨时间序列数据组织到每个雨量计（按代码列）中。雨量仪位于同一列中，与示例中的行相同，并且有一个月，年和降雨信息的专栏。

组织数据后，我需要进行统计测试，并且由于大量的雨量测量值，循环可以使其更容易。是否有一种方法可以通过在测试中重复的变量在Rain_gauge列中按代码指定每个雨量表？

rain_gauge = c(rep(1442032, 40), rep(1442035, 30), rep(1442036, 30),rep(1442039, 45),rep(1442049, 40),rep(1442032, 40),rep(1442045, 35))
year = runif(260, 1978,2020)
month = runif(260,1,12)
rainfall = runif(260, 50,202)

df = data.frame(rain_gauge, year, month, rainfall)#data frame to be organized in chronological order by "code" category
head(df)

#Examples of tests to apply to the series of each rain gauge in the rain_gauge column.
library(modifiedmk)
mmkh(as.vector(subset(df,rain_gauge=="1442032"))$rainfall)

pvalue_mk = mmkh(as.vector(subset(df,rain_gauge=="1442032"))$rainfall)[[2]]#Result to be save in a data frame results

library(tseries)
adf.test(subset(df,rain_gauge=="1442032")$rainfall)
pvalue_df = adf.test(subset(df,rain_gauge=="1442032")$rainfall)[[2]]#Result to be save in a data frame results

非常感谢！

原文

I would like to organize the rainfall time series data into each rain gauge (by code column) chronologically.
The rain gauges are in the same column, specified in lines as in the example, and there are columns with the month, year and rainfall informations.

After organizing the data, I need to perform statistical tests and a loop can make it easier, due to the large number of rain gauges. Is there a way to loop specifying each rain gauge by code in the rain_gauge column, as the variable to be repeated in the tests?

rain_gauge = c(rep(1442032, 40), rep(1442035, 30), rep(1442036, 30),rep(1442039, 45),rep(1442049, 40),rep(1442032, 40),rep(1442045, 35))
year = runif(260, 1978,2020)
month = runif(260,1,12)
rainfall = runif(260, 50,202)

df = data.frame(rain_gauge, year, month, rainfall)#data frame to be organized in chronological order by "code" category
head(df)

#Examples of tests to apply to the series of each rain gauge in the rain_gauge column.
library(modifiedmk)
mmkh(as.vector(subset(df,rain_gauge=="1442032"))$rainfall)

pvalue_mk = mmkh(as.vector(subset(df,rain_gauge=="1442032"))$rainfall)[[2]]#Result to be save in a data frame results

library(tseries)
adf.test(subset(df,rain_gauge=="1442032")$rainfall)
pvalue_df = adf.test(subset(df,rain_gauge=="1442032")$rainfall)[[2]]#Result to be save in a data frame results

Many thanks!

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静若繁花 2025-01-27 12:24:24

考虑by，面向对象的包装器tapply，它允许您按因子对数据帧进行切片并对子集运行进程以返回简化的对象（即、向量、矩阵）或任何输出的列表：

library(modifiedmk)
library(tseries)

get_pvalues <- function(sub) {
    mmkh_obj <- mmkh(sub$rainfall)
    adf_obj <- adf.test(sub$rainfall)    

    # NAMED VECTOR
    c(pvalue_mmkh = mmkh_obj[, "p.value"], pvalue_adf = adf_obj[, "p.value"])
}

# NAMED MATRIX
pvalues_matrix <- by(df, df$rain_gauge, get_pvalues)

Consider by, object-oriented wrapper to tapply, that allows you to slice a data frame by factor(s) and run processes on the subsets to return a simplified object (i.e., vector, matrix), or a list of any output:

library(modifiedmk)
library(tseries)

get_pvalues <- function(sub) {
    mmkh_obj <- mmkh(sub$rainfall)
    adf_obj <- adf.test(sub$rainfall)    

    # NAMED VECTOR
    c(pvalue_mmkh = mmkh_obj[, "p.value"], pvalue_adf = adf_obj[, "p.value"])
}

# NAMED MATRIX
pvalues_matrix <- by(df, df$rain_gauge, get_pvalues)

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