Spreadsheets editor comments
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@ -19,6 +19,8 @@ The best practices presented in this paper will save you much headache when you
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## Excel
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Microsoft Excel is a widely used spreadsheet software program where data are organized in worksheets inside of spreadsheet files.
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### Prerequisites
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In this section, you'll learn how to load data from Excel spreadsheets in R with the **readxl** package.
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@ -30,7 +32,6 @@ Later, we'll also use the writexl package, which allows us to create Excel sprea
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library(readxl)
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library(tidyverse)
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library(writexl)
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```
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@ -45,7 +46,7 @@ Most of readxl's functions allow you to load Excel spreadsheets into R:
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These functions all have similar syntax just like other functions we have previously introduced for reading other types of files, e.g. `read_csv()`, `read_table()`, etc.
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For the rest of the chapter we will focus on using `read_excel()`.
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### Reading spreadsheets {#sec-reading-spreadsheets}
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### Reading Excel spreadsheets {#sec-reading-spreadsheets-excel}
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@fig-students-excel shows what the spreadsheet we're going to read into R looks like in Excel.
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@ -317,17 +318,17 @@ Confusingly, it's also possible to have something that looks like a number but i
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These differences between how the underlying data are stored vs. how they're displayed can cause surprises when the data are loaded into R.
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By default readxl will guess the data type in a given column.
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A recommended workflow is to let readxl guess the column types, confirm that you're happy with the guessed column types, and if not, go back and re-import specifying `col_types` as shown in @sec-reading-spreadsheets.
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A recommended workflow is to let readxl guess the column types, confirm that you're happy with the guessed column types, and if not, go back and re-import specifying `col_types` as shown in @sec-reading-spreadsheets-excel.
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Another challenge is when you have a column in your Excel spreadsheet that has a mix of these types, e.g. some cells are numeric, others text, others dates.
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When importing the data into R readxl has to make some decisions.
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In these cases you can set the type for this column to `"list"`, which will load the column as a list of length 1 vectors, where the type of each element of the vector is guessed.
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### Data not in cell values
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::: callout-note
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Sometimes data is stored in more exotic ways, like the color of the cell background, or whether or not the text is bold.
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In such cases, you might find the [tidyxl package](https://nacnudus.github.io/tidyxl/) useful.
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See <https://nacnudus.github.io/spreadsheet-munging-strategies/> for more on strategies for working with non-tabular data from Excel.
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:::
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### Writing to Excel {#sec-writing-to-excel}
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@ -507,6 +508,10 @@ A good way of familiarizing yourself with the coding style used in a new package
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## Google Sheets
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Google Sheets is another widely used spreadsheet program included.
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It's free and web-based.
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Just like with Excel, in Google Sheets data are organized in worksheets (also called sheets) inside of spreadsheet files.
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### Prerequisites
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This section will also focus on spreadsheets, but this time you'll be loading data from a Google Sheet with the **googlesheets4** package.
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Therefore, many of the tasks can be accomplished with simply swapping out `read_excel()` for `read_sheet()`.
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However you'll also see that Excel and Google Sheets don't behave in exactly the same way, therefore other tasks may require further updates to the function calls.
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### Read sheets
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### Reading Google Sheets
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@fig-students-googlesheets shows what the spreadsheet we're going to read into R looks like in Google Sheets.
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This is the same dataset as in @fig-students-excel, except it's stored in a Google Sheet instead of Excel.
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deaths
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```
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### Write sheets
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### Writing to Google Sheets
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You can write from R to Google Sheets with `write_sheet()`.
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The first argument is the data frame to write, and the second argument is the name (or other identifier) of the Google Sheet to write to:
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@ -652,7 +657,9 @@ For further authentication details, we recommend reading the documentation googl
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## Summary
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In this chapter you learned how to read data into R from spreadsheets: from Microsoft Excel with `read_excel()` from the readxl package and from Google Sheets with `read_sheet()` from the googlesheets4 package.
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Microsoft Excel and Google Sheets are two of the most popular spreadsheet systems.
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Being able to interact with data stored in Excel and Google Sheets files directly from R is a superpower!
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In this chapter you learned how to read data into R from spreadsheets from Excel with `read_excel()` from the readxl package and from Google Sheets with `read_sheet()` from the googlesheets4 package.
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These functions work very similarly to each other and have similar arguments for specifying column names, NA strings, rows to skip on top of the file you're reading in, etc.
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Additionally, both functions make it possible to read a single sheet from a spreadsheet as well.
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