---
title: "Read Raw Text Information from Excel Files"
author: "Hauke Sonnenberg"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Tutorial}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

This package provides functions to read spreadsheet data from Microsoft Excel
files. To achieve this, it uses functions from the package
[readxl](https://readxl.tidyverse.org/). 

In contrast to the default behaviour of the readxl functions, this package reads
the raw text information from spreadsheets. No type conversions are performed.
Being all of the same type (character) the text values are returned in a matrix
and not in a data frame as it is the case for the readxl package.

Also, when using this package, all values keep their original position. By
default, the readxl-functions remove empty rows at the beginning of a sheet.
This leads to row numbers in the returned data frame that do not correspond to 
the original row numbers in the Excel sheet. For validation purposes, I prefer 
that all values appear at the same positions in the returned matrix as they have 
in the sheet. This is what this package does.

## Reading Table Data from a Spreadsheet Program

MS Excel is a spreadsheet program. It does not "know" where a table starts
and where it ends and it does not clearly assign a type to a column. Instead,
each cell can have its own type so that there can be cells of different types in
the same column. However, functions such as `readxl::read_excel()` try
to communicate with Excel as if it was a database management system. For each
column, the values in the first few rows of the column are inspected and based
on the found type the whole column is then converted accordingly. This may lead 
to conversion errors, e.g. if the first few values look numeric but further 
values cannot be interpreted as numeric, such as `">1000"`. In these cases the
readxl functions return a data frame in which the text values are removed, i.e.
set to `NA`. This package avoids these data losses as it keeps the original
(text) information and lets the user decide what to do.

## Read MS spreadsheet with readxl

We demonstrate this behaviour by reading a sheet from an example Excel file. The
top and bottom parts of the "table" look as follows:

[![table top](images/example_2_top.png)]()
[![table top](images/example_2_bottom.png)]()

We first read this sheet with the `read_excel()` function from the readxl 
package:

```{r}
# Path to example Excel file
file <- system.file("extdata/example_2.xlsx", package = "kwb.readxl")

# Read the first sheet with readxl::read_excel
data <- readxl::read_excel(file)

# The first empty rows were skipped and both columns are numeric (double)
head(data)
```

As described above, the two empty rows on top were skipped. Also, column B was
assumed to be numeric (double \<dbl\>) even though it contains a text value in
row 1004 (see image above).

## Read sheet with kwb.readxl

Now we read the same spreadsheet with `get_raw_text_from_xlsx()` from this 
package:

```{r}
# Read the sheet into a list of character matrices
sheets <- kwb.readxl::get_raw_text_from_xlsx(file, sheets = "two_empty_rows")

# Show the first rows of the first matrix
head(sheets$sheet_01)

# Show the last rows of the first matrix
tail(sheets$sheet_01)
```

The first two empty rows are kept so that the row number in the returned matrix
corresponds to the row number in the Excel file. This is helpful if we want to
warn the user about possible problems, such as the non-numeric value in row 
1004:

```{r}
# Store the text matrix in sheet
sheet <- sheets$sheet_01

# Get the number of the row containing a non-numeric value in column 2 
invalid_row <- max(which(is.na(as.numeric(sheet[, 2]))))

# Give a message to the user
cat("Dear user, please have a look at row", invalid_row, "of the sheet")
```
