library(readr)(Language): (Method Name)
Introduction
This first section should provide a brief background on the methodology with links to associated journal articles, or relevant sources. This should give the reader a high level overview of the method and its implementation. This will be helpful in setting the stage for the examples and discussion that follow.
Libraries or Extensions Needed
This section should describe what libraries, packages, or additional materials needed for the analysis described.
Data Sources for the Analysis
For real data, please provide a means of accessing these data and describe the data source used in the example, especially if it is a new dataset not already in the CAMIS/data/ folder.
For simulated/dummy datasets, please provide reproducible code to generate these data. This includes setting a random seed for reproducible random number generation.
exData <- tibble::tribble(
~Var1, ~Var2,
"val1", 1,
"val2", 2)data ExData;
input Var1 $ Var2 ...;
datalines;
[Data Lines];
run; import pandas as pd
data = {"score": [40, 47, 52, 26, 19, 25], "count": [2, 2, 2, 1, 2, 2]}
df = pd.DataFrame(data)Again, it is important to give credit to the original source of the data used in your example.
Statistical Method
Example Code using < package name >
Now you can start adding specific examples of how to use these packages or methods to conduct the analysis. It is helpful to include some notes and comments throughout.
For R packages, it is helpful to prepend package names to functions so new readers can understand where specific functions originate, especially with new packages.
# For R packages
lme4::lmer()
survival::Surv()Comparison of Packages
If you are comparing more than one package of a single language, consider adding in a table to illustrate some of the differences/similarities between the packages/methods.
Conclusion
Finally, add a conclusion section to the page. This may take on different forms but should broadly summarize the findings in the comparison of languages, packages, or approaches. In summarizing, be sure to include the advantages/limitations of the packages and approaches so the reader can understand the capabilities of the approaches to the statstical methodology.
There may be instances where you recommend specific languages, packages, or functions. Be sure to provide your rationale for these recommendations.
References
Be sure to include any references or sources used for the analysis here. These could be external links to pages or in-text citations. This will all help the reader find material needed for further evaluation.
Also, include this Session Info section. Manually add the packages used in your analysis in a vector, like shown below. This captures the environment used, which is important for reproducibility.
NoteSession Info
─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 4.4.2 (2024-10-31)
os Ubuntu 24.04.3 LTS
system x86_64, linux-gnu
ui X11
language (EN)
collate C.UTF-8
ctype C.UTF-8
tz UTC
date 2025-09-17
pandoc 3.6.3 @ /opt/quarto/bin/tools/ (via rmarkdown)
─ Packages ───────────────────────────────────────────────────────────────────
! package * version date (UTC) lib source
bit 4.5.0 2024-09-20 [1] RSPM (R 4.4.0)
bit64 4.5.2 2024-09-22 [1] RSPM (R 4.4.0)
P cli 3.6.3 2024-06-21 [?] RSPM (R 4.4.0)
clipr 0.8.0 2022-02-22 [1] RSPM (R 4.4.0)
cpp11 0.5.0 2024-08-27 [1] RSPM (R 4.4.0)
crayon 1.5.3 2024-06-20 [1] RSPM (R 4.4.0)
dplyr 1.1.4 2023-11-17 [1] RSPM (R 4.4.0)
P fansi 1.0.6 2023-12-08 [?] RSPM (R 4.4.0)
generics 0.1.3 2022-07-05 [1] RSPM (R 4.4.0)
P glue 1.8.0 2024-09-30 [?] RSPM (R 4.4.0)
hms 1.1.3 2023-03-21 [1] RSPM (R 4.4.0)
janitor 2.2.0 2023-02-02 [1] RSPM (R 4.4.0)
lattice 0.22-6 2024-03-20 [2] CRAN (R 4.4.2)
P lifecycle 1.0.4 2023-11-07 [?] RSPM (R 4.4.0)
lubridate 1.9.3 2023-09-27 [1] RSPM (R 4.4.0)
P magrittr 2.0.3 2022-03-30 [?] RSPM (R 4.4.0)
Matrix 1.7-1 2024-10-18 [2] CRAN (R 4.4.2)
P pillar 1.9.0 2023-03-22 [?] RSPM (R 4.4.0)
P pkgconfig 2.0.3 2019-09-22 [?] RSPM (R 4.4.0)
prettyunits 1.2.0 2023-09-24 [1] RSPM (R 4.4.0)
progress 1.2.3 2023-12-06 [1] RSPM (R 4.4.0)
purrr 1.0.2 2023-08-10 [1] RSPM (R 4.4.0)
R6 2.5.1 2021-08-19 [1] RSPM (R 4.4.0)
readr 2.1.5 2024-01-10 [1] RSPM (R 4.4.0)
P rlang 1.1.6 2025-04-11 [?] RSPM (R 4.4.0)
snakecase 0.11.1 2023-08-27 [1] RSPM (R 4.4.0)
stringi 1.8.4 2024-05-06 [1] RSPM (R 4.4.0)
stringr 1.5.1 2023-11-14 [1] RSPM (R 4.4.0)
survival 3.7-0 2024-06-05 [2] CRAN (R 4.4.2)
P tibble 3.2.1 2023-03-20 [?] RSPM (R 4.4.0)
tidyr 1.3.1 2024-01-24 [1] RSPM (R 4.4.0)
tidyselect 1.2.1 2024-03-11 [1] RSPM (R 4.4.0)
timechange 0.3.0 2024-01-18 [1] RSPM (R 4.4.0)
tzdb 0.4.0 2023-05-12 [1] RSPM (R 4.4.0)
P utf8 1.2.4 2023-10-22 [?] RSPM (R 4.4.0)
P vctrs 0.6.5 2023-12-01 [?] RSPM (R 4.4.0)
vroom 1.6.5 2023-12-05 [1] RSPM (R 4.4.0)
withr 3.0.1 2024-07-31 [1] RSPM (R 4.4.0)
[1] /home/runner/work/CAMIS/CAMIS/renv/library/linux-ubuntu-noble/R-4.4/x86_64-pc-linux-gnu
[2] /opt/R/4.4.2/lib/R/library
P ── Loaded and on-disk path mismatch.
─ Python configuration ───────────────────────────────────────────────────────
python: /home/runner/work/CAMIS/CAMIS/renv/python/virtualenvs/renv-python-3.12/bin/python
libpython: /usr/lib/python3.12/config-3.12-x86_64-linux-gnu/libpython3.12.so
pythonhome: /home/runner/work/CAMIS/CAMIS/renv/python/virtualenvs/renv-python-3.12:/home/runner/work/CAMIS/CAMIS/renv/python/virtualenvs/renv-python-3.12
version: 3.12.3 (main, Aug 14 2025, 17:47:21) [GCC 13.3.0]
numpy: /home/runner/work/CAMIS/CAMIS/renv/python/virtualenvs/renv-python-3.12/lib/python3.12/site-packages/numpy
numpy_version: 2.0.1
NOTE: Python version was forced by RETICULATE_PYTHON
──────────────────────────────────────────────────────────────────────────────