Question

我有一个包含多个工作表的excel文件，每个工作表有几列，所以我不想单独指定列的类型，而是自动指定。我想以stringsAsFactors= FALSE的方式阅读它们，因为它正确地解释了列的类型。在我当前的方法中，列宽“0.492±0.6”被解释为数字，返回NA，“因为”stringsAsFactors选项在read_excel中不可用。所以在这里，我写了一个解决方法，或多或少有效，但我不能在现实生活中使用，因为我不允许创建一个新文件。注意：我需要其他列作为数字或整数，还有其他只有文字作为字符的列，stringsAsFactors在我的read.csv示例中。

library(readxl)
file= "myfile.xlsx"
firstread<-read_excel(file, sheet = "mysheet", col_names = TRUE, na = "", skip = 0)
#firstread has the problem of the a column with "0.492 ± 0.6", 
#being interpreted as number (returns NA)
colna<-colnames(firstread)

# read every column as character
colnumt<-ncol(firstread)
textcol<-rep("text", colnumt)
secondreadchar<-read_excel(file, sheet = "mysheet", col_names = TRUE, 
col_types = textcol, na = "", skip = 0)
# another column, with the number 0.532, is now 0.5319999999999999 
# and several other similar cases.

# read again with stringsAsFactors 
# critical step, in real life, I "cannot" write a csv file.
write.csv(secondreadchar, "allcharac.txt", row.names = FALSE)
stringsasfactor<-read.csv("allcharac.txt", stringsAsFactors = FALSE)
colnames(stringsasfactor)<-colna
# column with "0.492 ± 0.6" now is character, as desired, others numeric as desired as well

Answer 1

这是一个导入excel文件中所有数据的脚本。它将每个工作表的数据放在list dfs：

中

library(readxl)

# Get all the sheets
all_sheets <- excel_sheets("myfile.xlsx")

# Loop through the sheet names and get the data in each sheet
dfs <- lapply(all_sheets, function(x) {

  #Get the number of column in current sheet
  col_num <- NCOL(read_excel(path = "myfile.xlsx", sheet = x))

  # Get the dataframe with columns as text
  df <- read_excel(path = "myfile.xlsx", sheet = x, col_types = rep('text',col_num))

  # Convert to data.frame
  df <- as.data.frame(df, stringsAsFactors = FALSE)

  # Get numeric fields by trying to convert them into
  # numeric values. If it returns NA then not a numeric field.
  # Otherwise numeric.
  cond <- apply(df, 2, function(x) {
    x <- x[!is.na(x)]
    all(suppressWarnings(!is.na(as.numeric(x))))
  })
  numeric_cols <- names(df)[cond]
  df[,numeric_cols] <- sapply(df[,numeric_cols], as.numeric)

  # Return df in desired format
  df
})

# Just for convenience in order to remember
# which sheet is associated with which dataframe
names(dfs) <- all_sheets

该过程如下：

首先，使用excel_sheets获取文件中的所有工作表，然后循环工作表名称以创建数据框。对于每个数据框，您最初通过将text参数设置为col_types将数据导入为text。将数据框的列作为文本后，您可以将结构从tibble转换为data.frame。之后，您会找到实际为数字列的列，并将它们转换为数值。

编辑：

截至4月底，readxl的新版本已发布，read_excel功能获得了与此问题相关的两项增强功能。第一个是你可以让函数用你的参数猜测列类型＆＃34; guess＆＃34;提供给col_types参数。第二个增强（第一个的推论）是guess_max参数被添加到read_excel函数。此新参数允许您设置用于猜测列类型的行数。基本上，我上面写的内容可以用以下内容缩短：

library(readxl)

# Get all the sheets
all_sheets <- excel_sheets("myfile.xlsx")

dfs <- lapply(all_sheets, function(sheetname) {
    suppressWarnings(read_excel(path = "myfile.xlsx", 
                                sheet = sheetname, 
                                col_types = 'guess', 
                                guess_max = Inf))
})

# Just for convenience in order to remember
# which sheet is associated with which dataframe
names(dfs) <- all_sheets

我建议您将readxl更新为最新版本，以缩短您的脚本，从而避免可能的烦恼。

我希望这会有所帮助。

自动获取Excel工作表的列类型

1 个答案:

编辑：