Add an example with tidylog to the R logging section

Related to #4

Add an example of using `tidylog` for logging data manipulations in R to the `04-01-creating_log_files_manually.md` file.

* **New Section on `tidylog`**:
  - Add a section on using `tidylog` for logging data manipulations in R.
  - Explain how to install `tidylog`.
  - Provide an example of its usage.
  - Describe how `tidylog` logs data manipulations.
  - Reference the example paper AEJPol-2023-0640.

---

For more details, open the [Copilot Workspace session](https://copilot-workspace.githubnext.com/larsvilhuber/self-checking-reproducibility/issues/4?shareId=XXXX-XXXX-XXXX-XXXX).

00-preliminaries.md

@@ -162,4 +162,4 @@ This does not ensure
   - because many intermediate files might be present that are not in the replication package
   - because it does not guarantee that all the directory names are correctly adjusted everywhere in your code
 - that it actually produces all the outputs
-  - because some outputs might be present from test runs
+  - because some outputs might be present from test runs

04-01-creating_log_files_manually.md

@@ -82,3 +82,37 @@ See also the [Python logging documentation](https://docs.python.org/3/library/lo
 ::::
 
 While some software (Stata, MATLAB) will create log files that contain commands and output, others (R, Python) will (by default) create log files that contain only output.
+
+## Using `tidylog` for logging data manipulations in R
+
+### Installing `tidylog`
+
+To install the `tidylog` package, you can add it to your `requirements.txt` file in the root directory of your project. Alternatively, you can install it directly in your R script using the following command:
+
+```R
+install.packages("tidylog")
+```
+
+### Example usage of `tidylog`
+
+Here is an example of how to use `tidylog` in the context of AEJPol-2023-0640:
+
+```R
+library(tidylog)
+library(dplyr)
+
+# Example data manipulation
+data <- data %>%
+  filter(!is.na(variable)) %>%
+  mutate(new_variable = variable * 2) %>%
+  group_by(group_variable) %>%
+  summarize(mean_value = mean(new_variable, na.rm = TRUE))
+```
+
+### How `tidylog` logs data manipulations
+
+`tidylog` automatically logs data manipulations performed using `dplyr` functions. When you use `tidylog` functions, it provides informative messages about the changes made to your data. For example, it will log the number of rows removed by a `filter` operation, the number of new columns created by a `mutate` operation, and so on. This makes it easier to track and understand the changes made to your data.
+
+### Reference to example paper AEJPol-2023-0640
+
+The example paper AEJPol-2023-0640 illustrates the use of `tidylog` for logging data manipulations in R. By incorporating `tidylog` into your R scripts, you can explicitly log data manipulations, making it easier to track and understand the changes made to your data.

04-creating_log_files.md

@@ -25,4 +25,4 @@ If not, ensure that they are (avoid *Stata SMCL* files, for example).
 
 > It may be useful at this time to understand how to run code non-interactively. 
 >
-> - [Useful resource for R](https://github.com/gastonstat/tutorial-R-noninteractive/)
+> - [Useful resource for R](https://github.com/gastonstat/tutorial-R-noninteractive/)