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tidying code blocks

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Jeremy Kidwell 2019-01-27 07:30:19 +00:00
parent 366f482bf5
commit 550121458e
1 changed files with 4 additions and 1 deletions
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mapping_draft.Rmd
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@ -197,7 +197,9 @@ proj4string(dtas) <- proj4string(admin_lev1)
permaculture <- read.csv("data/permaculture_scot-0.8.csv") permaculture <- read.csv("data/permaculture_scot-0.8.csv")
coordinates(permaculture) <- c("X", "Y") coordinates(permaculture) <- c("X", "Y")
proj4string(permaculture) <- proj4string(admin_lev1) proj4string(permaculture) <- proj4string(admin_lev1)
```
```{r process_admin_data}
# TODO: Code below augments existing dataframes to run calculations and add columns with point counts per polygon, # TODO: Code below augments existing dataframes to run calculations and add columns with point counts per polygon,
# percentages, and normalising data. I'm pretty sure this can all be done inline under create_admin_ecs_choropleth # percentages, and normalising data. I'm pretty sure this can all be done inline under create_admin_ecs_choropleth
# code chunk without adding new columns to dataframes here, but how?! # code chunk without adding new columns to dataframes here, but how?!
@ -352,7 +354,8 @@ We can compare the representation in these various regions against our compariso
[Figure 4, normalised by PointX data; also including agricultural parishes etc. as above] [Figure 4, normalised by PointX data; also including agricultural parishes etc. as above]
# plot as chlorogram: https://www.r-graph-gallery.com/331-basic-cartogram/ todo: plot as chlorogram: https://www.r-graph-gallery.com/331-basic-cartogram/
# Appendix A # Appendix A
```{r pander_admin_table} ```{r pander_admin_table}