将数据集分配给数据框列表

Question

我每次通过一个迭代超过 4 年（2011、2013、2015、2017）的循环生成一组 6 个数据集，这样我总共将拥有 24 个数据集。我正在尝试使用分配粘贴将每个数据集的名称与相应的年份连接起来。 但是，我在循环结束时只得到 6 个数据集，而不是 6*4 =24。

我需要特殊的 [[]] 语法来创建数据框列表吗？为什么我无法将数据集分配给下面循环结构内的变量？

library(educationdata)
library(glue)

## Initialize lists
dates<-list("2011","2013","2015","2017")
frames<-list("df_ccdirectory","df_ccdenrollment","df_crdcteacher",
             "df_crdcmathscience","df_crdcsat","df_crdcfinance")
dflist <- list()



  for (j in dates){
    
    df_ccdirectory <- get_education_data(level = "schools",
                                source = "ccd",
                                topic = "directory",
                                filters = list(year = j,fips=10),
                                add_labels = TRUE)
    dflist[[1]]<- df_ccdirectory

    df_ccdenrollment <- get_education_data(level = "schools",
                                      source = "ccd",
                                      topic = "enrollment",
                                      filters = list(year = j,fips=10),
                                      add_labels = TRUE)
    dflist[[2]]<-   df_ccdenrollment
    df_crdcteacher<- get_education_data(level = "schools",
                           source = "crdc",
                           topic = "teachers-staff",
                           filters = list(year = j,fips=10),
                           add_labels = TRUE)
    dflist[[3]]<-    df_crdcteacher
    df_crdcmathscience <- get_education_data(level = "schools",
                                         source = "crdc",
                                         topic = "math-and-science",
                                         subtopic = c('race','sex'),
                                         filters = list(year = j,fips=10),
                                         add_labels = TRUE)
    dflist[[4]]<- df_crdcmathscience

    df_crdcsat <- get_education_data(level = "schools",
                           source = "crdc",
                           topic = "sat-act-participation",
                           subtopic = c('race','sex'),
                           filters = list(year = j,fips=10),
                           add_labels = TRUE)
    dflist[[5]] <-df_crdcsat

    df_crdcfinance <- get_education_data(level = "schools",
                                     source = "crdc",
                                     topic = "school-finance",
                                     filters = list(year = j,fips=10),
                                     add_labels = TRUE)
    dflist[[6]]<-df_crdcfinance

    
  
    ## Error catching...
    #print(dates[[j]],"\n")
    print(paste0("dataset 1"))
    cat("\n")
        head(dflist[[1]])
    cat("\n")
    print(paste0("dataset 6"))
    cat("\n")
    head(dflist[[6]])
    cat("\n")
    for (k in 1:6){
        assign(paste(frames[k], dates[j], sep = ""), dflist[[k]])
  
    }
  
 
 }
     

Answer 1

考虑几个调整：

1. 继续使用单个数据框列表，避免在您的全球环境中充斥许多独立的、类似结构的数据。对于调试和副作用问题，assign 应该很少在 R 中使用。相反，为您的数据框列表指定名称。
2. 避免使用更精简的 apply 系列方法记录 for 循环，这些方法隐藏循环并返回集合，在某些情况下，如下所示，sapply 命名集合。此外，Map（mapply 的包装）是家庭的元素成员。
3. 通过参数化六个不同的get_education_data 调用来保持代码干燥（D不要R重复Y我们自己）通过 source 和 topic 参数。

调整后的代码

# USER-DEFINED PARAMETERIZED METHOD
build_df <- function(year_param, source_param, topic_param) {
    get_education_data(
        level = "schools",
        source = source_param,
        topic = topic_param,
        filters = list(year = year_param, fips=10),
        add_labels = TRUE
    )
}

# INITIALIZE VECTORS
dates <- c("2011", "2013", "2015", "2017")
sources <- c("ccd", "ccd", "crdc", "crdc", "crdc", "crdc")
topics <- c(
    "directory", "enrollment", "teachers-staff",
    "math-and-science", "sat-act-participation",
    "school-finance"
)
frames <- c(
    "df_ccdirectory", "df_ccdenrollment", "df_crdcteacher",
    "df_crdcmathscience", "df_crdcsat", "df_crdcfinance"
)

# RETURN NESTED YEARLY LIST OF DATA FRAMES
df_list <- sapply(
    dates, 
    function(dt) setNames(Map(build_df, dt, sources, topics), frames),
    simplify = FALSE
)

输出

# ALL DATA FRAMES (N=24)
df_list$`2011`$df_ccdirectory
df_list$`2011`$df_ccdenrollment
...
df_list$`2017`$df_crdcsat
df_list$`2017`$df_crdcfinance


# ALL 2011 DATA FRAMES (N=6)
df_list$`2011`


# ALL ccdirectory DATA FRAMES (N=4)
lapply(df_list, `[[`, "df_ccdirectory")