data/ex

5 years ago · 6bc3443f95
5 changed files with 249 additions and 1 deletions
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+The MIT License (MIT)
+
+Copyright (c) 2019 Bob Rudis <bob@rud.is>
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
--- a/README.Rmd
+++ b/README.Rmd
@ -1,7 +1,7 @@
 ---
 output: rmarkdown::github_document
 editor_options: 
-  chunk_output_type: inline
+  chunk_output_type: console
 ---
 ```{r pkg-knitr-opts, include=FALSE}
 knitr::opts_chunk$set(
@ -12,3 +12,91 @@ options(width=120)

 # loweslocations

+This past week [Lowe's told their assemblers they were all out of a job](https://www.wsj.com/articles/lowes-lays-off-thousands-of-store-workers-11564680676). This decision impacts ~1-3 (sometimes more depending on the store) workers per [Lowe's store](https://www.lowes.com/Lowes-Stores) and Lowe's assemblers used to make between ~\$13.00 & \$18.00 USD/hour.
+
+The `data` directory contains [`lowes-stores-geo.csv.gz`](data/lowes-stores-geo.csv.gz) which is lovingly hand-crafted transcription of all the locations listed at <https://www.lowes.com/Lowes-Stores>. The addresses have been geolocated (using [{rgeocodio}](https://git.rud.is/hrbrmstr/rgeocodio)) and contain:
+
+- store name
+- store published address
+- store geocoded legit address
+- store phone #
+- county
+- city
+- state
+- longitude
+- latitude
+
+which should be sufficient to enable data journalists to cross reference with census/economic data to facilitate potential regional impact reporting.
+
+## Some Summary Info
+
+```{r libs}
+library(sf)
+library(albersusa)
+library(hrbrthemes)
+library(tidyverse)
+```
+
+```{r data}
+cols(
+  o_addr = col_character(),
+  fmt_addr = col_character(),
+  phone = col_character(),
+  city = col_character(),
+  county = col_character(),
+  state = col_character(),
+  lat = col_double(),
+  lng = col_double()
+) -> lowes_cols
+
+lowes <- read_csv(here::here("data/lowes-stores-geo.csv.gz"), col_types = lowes_cols)
+```
+
+```{r show-data}
+head(lowes) %>% 
+  knitr::kable("markdown")
+```
+
+```{r move-points}
+filter(lowes, !(state %in% c("HI", "AK"))) %>% 
+  select(lon=lng, lat) %>% 
+  bind_rows(
+    filter(lowes, (state %in% c("HI", "AK"))) %>% 
+      select(lng, lat) %>% 
+      points_elided(.) %>% 
+      select(lon=1, lat=2)
+  ) %>% 
+  st_as_sf(
+    coords = c("lon", "lat"),
+    crs = us_longlat_proj, 
+    agr = "constant"
+  ) -> pts
+```
+
+```{r points-map, fig.width=1000/72, fig.height=500/72}
+ggplot() +
+  geom_sf(data = usa_sf("longlat"), fill = ft_cols$gray) +
+  geom_sf(data = pts, size = 0.5, alpha = 1/2, color = ft_cols$yellow) +
+  coord_sf(crs = us_laea_proj, datum = NA) + 
+  labs(
+    x = NULL, y = NULL,
+    title = "Lowe's Locations"
+  ) +
+  theme_ft_rc(grid="") +
+  theme(axis.text = element_blank())
+```
+
+```{r city-sum}
+count(lowes, state, sort=TRUE) %>% 
+  top_n(10) %>% 
+    knitr::kable()
+```
+
+```{r county-sum}
+count(lowes, county, state, sort=TRUE) %>% 
+  top_n(10) %>% 
+  knitr::kable()
+```
+
+
+
--- a/README.md
+++ b/README.md
@ -0,0 +1,139 @@
+
+# loweslocations
+
+This past week [Lowe’s told their assemblers they were all out of a
+job](https://www.wsj.com/articles/lowes-lays-off-thousands-of-store-workers-11564680676).
+This decision impacts \~1-3 (sometimes more depending on the store)
+workers per [Lowe’s store](https://www.lowes.com/Lowes-Stores) and
+Lowe’s assemblers used to make between \~$13.00 & $18.00 USD/hour.
+
+The `data` directory contains
+[`lowes-stores-geo.csv.gz`](data/lowes-stores-geo.csv.gz) which is
+lovingly hand-crafted transcription of all the locations listed at
+<https://www.lowes.com/Lowes-Stores>. The addresses have been geolocated
+(using [{rgeocodio}](https://git.rud.is/hrbrmstr/rgeocodio)) and
+contain:
+
+  - store name
+  - store published address
+  - store geocoded legit address
+  - store phone \#
+  - county
+  - city
+  - state
+  - longitude
+  - latitude
+
+which should be sufficient to enable data journalists to cross reference
+with census/economic data to facilitate potential regional impact
+reporting.
+
+## Some Summary Info
+
+``` r
+library(sf)
+library(albersusa)
+library(hrbrthemes)
+library(tidyverse)
+```
+
+``` r
+cols(
+  o_addr = col_character(),
+  fmt_addr = col_character(),
+  phone = col_character(),
+  city = col_character(),
+  county = col_character(),
+  state = col_character(),
+  lat = col_double(),
+  lng = col_double()
+) -> lowes_cols
+
+lowes <- read_csv(here::here("data/lowes-stores-geo.csv.gz"), col_types = lowes_cols)
+```
+
+``` r
+head(lowes) %>% 
+  knitr::kable("markdown")
+```
+
+| o\_addr                                | fmt\_addr                                        | phone          | city      | county                       | state |      lat |         lng |
+| :------------------------------------- | :----------------------------------------------- | :------------- | :-------- | :--------------------------- | :---- | -------: | ----------: |
+| 333 East Tudor Rd , AK 99503           | 333 E Tudor Rd, Anchorage, AK 99503              | (907) 563-0391 | Anchorage | Anchorage Municipality       | AK    | 61.18100 | \-149.87856 |
+| 1200 North Muldoon , AK 99504          | 1200 N Muldoon Rd, Anchorage, AK 99504           | (907) 269-2400 | Anchorage | Anchorage Municipality       | AK    | 61.22563 | \-149.74607 |
+| 10900 Old Seward Highway , AK 99515    | 10900 Old Seward Hwy, Anchorage, AK 99515        | (907) 349-8889 | Anchorage | Anchorage Municipality       | AK    | 61.12179 | \-149.86645 |
+| 425 Merhar Ave , AK 99701              | 425 Merhar Ave, Fairbanks, AK 99701              | (907) 451-4700 | Fairbanks | Fairbanks North Star Borough | AK    | 64.85682 | \-147.69653 |
+| 2561 East Sun Mountain Ave , AK 99654  | 2561 E Sun Mountain Ave, Wasilla, AK 99654       | (907) 352-3100 | Wasilla   | Matanuska-Susitna Borough    | AK    | 61.57333 | \-149.38457 |
+| 235 Colonial Promenade Pkwy , AL 35007 | 235 Colonial Promenade Pkwy, Alabaster, AL 35007 | (205) 685-4060 | Alabaster | Shelby County                | AL    | 33.23110 |  \-86.80503 |
+
+``` r
+filter(lowes, !(state %in% c("HI", "AK"))) %>% 
+  select(lon=lng, lat) %>% 
+  bind_rows(
+    filter(lowes, (state %in% c("HI", "AK"))) %>% 
+      select(lng, lat) %>% 
+      points_elided(.) %>% 
+      select(lon=1, lat=2)
+  ) %>% 
+  st_as_sf(
+    coords = c("lon", "lat"),
+    crs = us_longlat_proj, 
+    agr = "constant"
+  ) -> pts
+```
+
+``` r
+ggplot() +
+  geom_sf(data = usa_sf("longlat"), fill = ft_cols$gray) +
+  geom_sf(data = pts, size = 0.5, alpha = 1/2, color = ft_cols$yellow) +
+  coord_sf(crs = us_laea_proj, datum = NA) + 
+  labs(
+    x = NULL, y = NULL,
+    title = "Lowe's Locations"
+  ) +
+  theme_ft_rc(grid="") +
+  theme(axis.text = element_blank())
+```
+
+<img src="README_files/figure-gfm/points-map-1.png" width="1333.33333333333" />
+
+``` r
+count(lowes, state, sort=TRUE) %>% 
+  top_n(10) %>% 
+    knitr::kable()
+```
+
+| state |   n |
+| :---- | --: |
+| TX    | 142 |
+| FL    | 126 |
+| NC    | 114 |
+| CA    | 110 |
+| OH    |  83 |
+| PA    |  83 |
+| NY    |  70 |
+| VA    |  69 |
+| GA    |  63 |
+| TN    |  60 |
+
+``` r
+count(lowes, county, state, sort=TRUE) %>% 
+  top_n(10) %>% 
+  knitr::kable()
+```
+
+| county                | state |  n |
+| :-------------------- | :---- | -: |
+| Maricopa County       | AZ    | 21 |
+| Los Angeles County    | CA    | 20 |
+| Harris County         | TX    | 18 |
+| Clark County          | NV    | 13 |
+| Riverside County      | CA    | 12 |
+| Tarrant County        | TX    | 11 |
+| Bexar County          | TX    | 10 |
+| San Bernardino County | CA    | 10 |
+| Allegheny County      | PA    |  9 |
+| Dallas County         | TX    |  9 |
+| Franklin County       | OH    |  9 |
+| Hillsborough County   | FL    |  9 |
+| Mecklenburg County    | NC    |  9 |
--- a/README_files/figure-gfm/points-map-1.png
+++ b/README_files/figure-gfm/points-map-1.png
--- a/data/lowes-stores-geo.csv.gz
+++ b/data/lowes-stores-geo.csv.gz