I know the code chunks is helpful (to me at least), but in a report, I would hidden them. Any reader interested in the code should read them in your Rmd file. Only highlight code chunk that is meaningful to the audience.

siting of cooling centers

Add a note below the able for what each column is.

This is the case, but I want you to make it explicit why it is important to link heat wave/dome and health/heat vulnerability - why the cejst is the base data source for this.

Spell out "Land Surface Temperature (F)"

This is very helpful, but readers of the map may not pay attention to the code comments - as a matter of fact you may want to hide the code snippet when presentation your product to non-technical audience. Consider rename your column to something expressive but concise.

The tooltip for this layer currently shows the FID column, which is not very meaningful/useful. Consider modify it to show CEJST column(s) you want to highlight.

more likely to be in poor condition

I thought we excluded unincorporated #11 (80%), but it seems it still show ing up. Since it is so much higher and you're using a continuous color gradient, this makes the map less readable.

As I now look at it, the GRANT PARK in the bottom right is likely a neighborhood outside Portland and with duplicated name. We should exclude it.

Since this information is the same for all maps. I will put it somewhere less prominent. Maybe below the map?

Since you'll be using this exact string in your map and charts, I'd go with "Non-Profit", "For Profit", "Public Entity".

snippets like this are usually not very helpful in a report - OK for a technical memo though.

note which data file is this. If server as a report to non-technical audience/client (e.g. Dr. Bates), it is better to summarize the extend of missing values on critical variables or non-matches.

I would name each of the sub-tabs, Statistics by property, Statistics by Owner, Statistics by management co

Very nice!

Also include number of evicted?

similar to the figure above, rename scale::percent(...) % Evicted and remove pct_evicted. Keep either owner_type or factor(owner_type).

I would create a new column for as.Date(...) and name it Month, similarly for as.factor(...). You want your dashboards to be approachable for non-technical audience.

Legend should also indicate size of circle proportional to number of evictions

It'd be helpful to visualize where the fatal crashes happen, with maps.

Need more support for this claim. Or simply, we based our analysis on this score.

-> "Zooming in"

by road functional class

cite source. Good job adding the dashed line representing it in the figure.

same comments for this table. I'd consider collapsing income categories into a smaller number of groups (~5).

Same comments as the table above: consider using kable, merged these two tables (additional column)

As I commented during your presentation, this trend may be affect the "outlier" neighborhood in the top right corner of the figure.

You can use kabble to make data frame printout better looking. Merge these two tables. Add table title.

delete, since those are total crashes, not only pedestrian/cyclist crashes. only total traffic volume is relevant here.

delete

delete

Provide a title for your figures. I know you already have the section title, but my preference is that each figure/table in your report should be self-contained, ie, your reader don't need to read your report to understand what the figure/table is about.

Very argued section setting the background and motivation of your project

I see that you are doing citation and references manually. This is fine for your class project. I encourage you to look into using bibliography with Rmd, e.g. https://bookdown.org/yihui/rmarkdown-cookbook/bibliography.html