vignettes/demo-1night-vroom-etc.md

In laurelboyd/craggy_2019: Housing Data and Eviction Data for King County, Washington, United States

Demo OneNightCount.csv and vroom

John D. Smith 2019-08-24

library(tidyverse)

## ── Attaching packages ────── tidyverse 1.2.1 ──

## ✔ ggplot2 3.2.1     ✔ readr   1.3.1
## ✔ tibble  2.1.3     ✔ purrr   0.3.2
## ✔ tidyr   0.8.3     ✔ stringr 1.4.0
## ✔ ggplot2 3.2.1     ✔ forcats 0.4.0

## ── Conflicts ───────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()

library(vroom)
library(inspectdf)
library(skimr)

## 
## Attaching package: 'skimr'

## The following object is masked from 'package:stats':
## 
##     filter

library(janitor)

## 
## Attaching package: 'janitor'

## The following objects are masked from 'package:stats':
## 
##     chisq.test, fisher.test

library(craggy2019)

Generate a minimally serviceable data frame:

oneNightCount <- vroom(system.file("extdata", "oneNightCount.csv", package = "craggy2019"))

## Observations: 130
## Variables: 14
## chr [ 1]: Location
## dbl [13]: YEAR, SEATTLE, KENT, NORTH END, EAST SIDE, SW KING CO, WHITE CNTR, FEDERAL ...
## 
## Call `spec()` for a copy-pastable column specification
## Specify the column types with `col_types` to quiet this message

oneNightCount <- oneNightCount %>% 
  clean_names %>% 
  select(-total) %>% 
  filter(location != "TOTAL")

Inspect with a few skimr and inspectdf:

skim(oneNightCount)

## Skim summary statistics
##  n obs: 120 
##  n variables: 13 
## 
## ── Variable type:character ────────────────────
##  variable missing complete   n min max empty n_unique
##  location       0      120 120   5  18     0       12
## 
## ── Variable type:numeric ──────────────────────
##         variable missing complete   n    mean     sd   p0  p25    p50
##           auburn      12      108 120    5.88  11.67    0    0    1  
##        east_side       0      120 120   13.48  24.72    0    0    3  
##      federal_way       0      120 120   10.78  25.36    0    0    2  
##             kent       0      120 120    8.63  15.97    0    1    2.5
##  night_owl_buses       0      120 120   11.2   38.42    0    0    0  
##        north_end       0      120 120    5.16  13.54    0    0    1  
##           renton       0      120 120    6.97  12.09    0    0    3  
##          seattle       0      120 120  176.88 193.1     4   26  109  
##       sw_king_co      96       24 120   21.83  38.46    0    0    4  
##    vashon_island      96       24 120    2      6.53    0    0    0  
##       white_cntr      24       96 120    3.84   9.76    0    0    0  
##             year       0      120 120 2011.5    2.88 2007 2009 2011.5
##      p75 p100     hist
##     4      54 ▇▁▁▁▁▁▁▁
##     9     109 ▇▁▁▁▁▁▁▁
##     7     199 ▇▁▁▁▁▁▁▁
##     9     126 ▇▁▁▁▁▁▁▁
##     0     174 ▇▁▁▁▁▁▁▁
##     3      89 ▇▁▁▁▁▁▁▁
##     7      75 ▇▁▁▁▁▁▁▁
##   273.75  914 ▇▃▂▁▁▁▁▁
##    25.25  161 ▇▁▁▁▁▁▁▁
##     0      31 ▇▁▁▁▁▁▁▁
##     2      54 ▇▁▁▁▁▁▁▁
##  2014    2016 ▇▃▃▃▃▃▃▇

inspectdf::inspect_cor(oneNightCount) %>% show_plot()

inspectdf::inspect_num(oneNightCount) %>% show_plot()

inspectdf::inspect_na(oneNightCount) 

## # A tibble: 13 x 3
##    col_name          cnt  pcnt
##    <chr>           <dbl> <dbl>
##  1 sw_king_co         96    80
##  2 vashon_island      96    80
##  3 white_cntr         24    20
##  4 auburn             12    10
##  5 location            0     0
##  6 year                0     0
##  7 seattle             0     0
##  8 kent                0     0
##  9 north_end           0     0
## 10 east_side           0     0
## 11 federal_way         0     0
## 12 renton              0     0
## 13 night_owl_buses     0     0

laurelboyd/craggy_2019 documentation built on Nov. 4, 2019, 4:17 p.m.