Himalayas

[nicolasfoss]

Thank you for your submission! Please leave this text as-is when you submit, and then check the checklist.

Usability:

• This dataset has not already been used in TidyTuesday.
• The dataset is less than 20MB when saved as a tidy CSV.
• I can imagine at least one data visualization related to this dataset.

Preparation:

• cleaning.R has code to download and clean the dataset, resulting in descriptively-named data.frames.
• I ran saving.R to create csvs and md data dictionaries for each of my data.frames.
• I filled in descriptions for each variable in each of the {dataset}.md files.
• I edited the intro.md file to introduce my dataset.
• I included at least one image for my dataset as a png file.
• I completed the information in meta.yaml, including descriptive alt text for each image.
• I provided information in meta.yaml about how to credit me, and deleted any parts of that block that I do not want you to use.

[nicolasfoss]

I was thinking maybe the analysis would be more interesting if I provide the dataset that has all the climber information as well?

[jonthegeek]

Just a couple tweaks. I'll apply them then make sure everything merges cleanly. Thanks!

[jonthegeek]

Note to self: make sure credit still shows up properly after this is assigned:

Thank you to [Nicolas Foss](www.linkedin.com/in/nicolas-foss) for curating this week's dataset.

[jonthegeek]

Looks great! Now I just need to assign it to a week and see if that reveals any issues.

[jonthegeek]

/assign positconf 2025-01-21

[jonthegeek]

/assign himalayas 2025-01-21

[jonthegeek]

Update credit link

[jonthegeek]

Thanks again!