读取保存在 Jupyter 文件夹中的 Excel 文件

Question

I am trying to read my excel file using R that I dragged to the Jupyter lab folder (...Tabs.xlsx in this case). How do I use R or Python to read in that file?

Answer 1

In python you can use pandas, which has a built in function to make this easy:

import pandas as pd
pd.read_excel("my_excel.xlsx", sheet_name="my_sheet_name")

Answer 2

require(openxlsx)

# I wrote a function to read-in all sheets of a excel file
# assuming the excel sheets reflect 1 simple data frame each.
# I hope your excel sheets are very simple and don't need skipping
# data or leaving out some areas etc. Otherwise, you have to modify
# or use plain `read.xlsx` from `openxlsx`.
# This function returns a list of data frames 
# (for each sheet 1 data frame)
# the names of the elements of the list being the sheet-titles.

#############################
# read xlsx files to dfs list
#############################

xlsx2df.list <- function(xlsx.path, rowNames = TRUE, colNames = TRUE, ...) {
  wb <- loadWorkbook(xlsx.path)
  sheetNames <- names(wb)
  res <- lapply(sheetNames, function(sheetName) {
    read.xlsx(wb, sheet = sheetName, rowNames = rowNames, colNames = colNames, ...)
  })
  names(res) <- sheetNames
  res
}

dfs <- xlsx2df.list("path/to/my_excel.xlsx")

first.sheet.df <- dfs[[1]] # or dfs[["sheet1-title"]]
second.sheet.df <- dfs[[2]] # ...

I wrote this to not to have to check what is the sheet name and thus which sheet I have to read-in. This is one of the most frequently used functions I use at work, since biologists for which I do analysis, love excel sheets.

This function saves you time by calling the openxlsx` functions for you. (You don't have to learn them, thus, as long as your sheets are simple and regular enough ...).

Note: openxlsx is much less error prone than xlsx , since it avoids Java. I had problems with memory restriction by Java. xlsx -dependent functions got memory errors when the excel files were huge (Gbs). So: use -dependent functions got memory errors when the excel files were huge (Gbs). So: use openxslx , avoid xlsx` (Java-dependency)!