search

cis-ds / Discussion

Public discussion
10 stars 15 forks source link

04-datapasta #155

Closed bensoltoff closed 3 years ago

bensoltoff commented 3 years ago

Post your reproducible example here

jnseddon commented 3 years ago 

library(tidyverse)

# import data file

urban <- tibble::tribble(
  ~state, ~urbanindex,
  "Alabama",    9.605935,
  "Alaska",    8.735964,
  "American Samoa",    11.08593,
  "Arizona",    11.29971,
  "Arkansas",    9.259444,
  "California",    12.19028,
  "Colorado",    11.15445,
  "Connecticut",    11.40968,
  "Delaware",    11.00999,
  "District of Columbia",    13.44057,
  "Florida",    11.46484,
  "Georgia",    10.55233,
  "Guam",    11.08593,
  "Hawaii",    11.08621,
  "Idaho",    9.593634,
  "Illinois",    11.62372,
  "Indiana",     10.4105,
  "Iowa",    9.593525,
  "Kansas",    10.12044,
  "Kentucky",    9.789536,
  "Louisiana",    10.17518,
  "Maine",    9.037091,
  "Maryland",    11.71105,
  "Massachusetts",    11.83973,
  "Michigan",    10.80559,
  "Minnesota",    10.45684,
  "Mississippi",    8.910859,
  "Missouri",    10.20212,
  "Montana",    8.470226,
  "Nebraska",    10.19912,
  "Nevada",    11.76972,
  "New Hampshire",    9.917139,
  "New Jersey",    12.23565,
  "New Mexico",    9.896993,
  "New York",    12.55857,
  "North Carolina",    10.32481,
  "North Dakota",    9.054678,
  "Northern Marianas",    11.08593,
  "Ohio",    10.87687,
  "Oklahoma",     9.93928,
  "Oregon",    10.71233,
  "Pennsylvania",    11.14623,
  "Puerto Rico",    11.57168,
  "Rhode Island",    11.72124,
  "South Carolina",    10.11142,
  "South Dakota",    8.728642,
  "Tennessee",    10.19729,
  "Texas",    11.17488,
  "Utah",    10.96281,
  "Vermont",    8.843222,
  "Virgin Islands",    11.08593,
  "Virginia",    10.90625,
  "Washington",    11.11933,
  "West Virginia",    9.111112,
  "Wisconsin",    10.19131,
  "Wyoming",    8.256294
)

# how do I reorder the bars from largest to smallest?
ggplot(data = urban, mapping = aes(x = state, y = urbanindex)) +
  geom_col() +
  coord_flip()

Created on 2020-11-05 by the reprex package (v0.3.0)

Session info ``` r devtools::session_info() #> - Session info --------------------------------------------------------------- #> setting value #> version R version 4.0.2 (2020-06-22) #> os Windows 10 x64 #> system x86_64, mingw32 #> ui RTerm #> language (EN) #> collate English_United States.1252 #> ctype English_United States.1252 #> tz America/Chicago #> date 2020-11-05 #> #> - Packages ------------------------------------------------------------------- #> package * version date lib source #> assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.2) #> backports 1.1.10 2020-09-15 [1] CRAN (R 4.0.2) #> blob 1.2.1 2020-01-20 [1] CRAN (R 4.0.2) #> broom 0.7.1 2020-10-02 [1] CRAN (R 4.0.2) #> callr 3.4.4 2020-09-07 [1] CRAN (R 4.0.2) #> cellranger 1.1.0 2016-07-27 [1] CRAN (R 4.0.2) #> cli 2.0.2 2020-02-28 [1] CRAN (R 4.0.2) #> colorspace 1.4-1 2019-03-18 [1] CRAN (R 4.0.2) #> crayon 1.3.4 2017-09-16 [1] CRAN (R 4.0.2) #> curl 4.3 2019-12-02 [1] CRAN (R 4.0.2) #> DBI 1.1.0 2019-12-15 [1] CRAN (R 4.0.2) #> dbplyr 1.4.4 2020-05-27 [1] CRAN (R 4.0.2) #> desc 1.2.0 2018-05-01 [1] CRAN (R 4.0.2) #> devtools 2.3.2 2020-09-18 [1] CRAN (R 4.0.2) #> digest 0.6.25 2020-02-23 [1] CRAN (R 4.0.2) #> dplyr * 1.0.2 2020-08-18 [1] CRAN (R 4.0.2) #> ellipsis 0.3.1 2020-05-15 [1] CRAN (R 4.0.2) #> evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.2) #> fansi 0.4.1 2020-01-08 [1] CRAN (R 4.0.2) #> farver 2.0.3 2020-01-16 [1] CRAN (R 4.0.2) #> forcats * 0.5.0 2020-03-01 [1] CRAN (R 4.0.2) #> fs 1.5.0 2020-07-31 [1] CRAN (R 4.0.2) #> generics 0.0.2 2018-11-29 [1] CRAN (R 4.0.2) #> ggplot2 * 3.3.2 2020-06-19 [1] CRAN (R 4.0.2) #> glue 1.4.2 2020-08-27 [1] CRAN (R 4.0.2) #> gtable 0.3.0 2019-03-25 [1] CRAN (R 4.0.2) #> haven 2.3.1 2020-06-01 [1] CRAN (R 4.0.2) #> highr 0.8 2019-03-20 [1] CRAN (R 4.0.2) #> hms 0.5.3 2020-01-08 [1] CRAN (R 4.0.2) #> htmltools 0.5.0 2020-06-16 [1] CRAN (R 4.0.2) #> httr 1.4.2 2020-07-20 [1] CRAN (R 4.0.2) #> jsonlite 1.7.1 2020-09-07 [1] CRAN (R 4.0.2) #> knitr 1.30 2020-09-22 [1] CRAN (R 4.0.2) #> labeling 0.3 2014-08-23 [1] CRAN (R 4.0.0) #> lifecycle 0.2.0 2020-03-06 [1] CRAN (R 4.0.2) #> lubridate 1.7.9 2020-06-08 [1] CRAN (R 4.0.2) #> magrittr 1.5 2014-11-22 [1] CRAN (R 4.0.2) #> memoise 1.1.0 2017-04-21 [1] CRAN (R 4.0.2) #> mime 0.9 2020-02-04 [1] CRAN (R 4.0.0) #> modelr 0.1.8 2020-05-19 [1] CRAN (R 4.0.2) #> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.0.2) #> pillar 1.4.6 2020-07-10 [1] CRAN (R 4.0.2) #> pkgbuild 1.1.0 2020-07-13 [1] CRAN (R 4.0.2) #> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.2) #> pkgload 1.1.0 2020-05-29 [1] CRAN (R 4.0.2) #> prettyunits 1.1.1 2020-01-24 [1] CRAN (R 4.0.2) #> processx 3.4.4 2020-09-03 [1] CRAN (R 4.0.2) #> ps 1.3.4 2020-08-11 [1] CRAN (R 4.0.2) #> purrr * 0.3.4 2020-04-17 [1] CRAN (R 4.0.2) #> R6 2.4.1 2019-11-12 [1] CRAN (R 4.0.2) #> Rcpp 1.0.5 2020-07-06 [1] CRAN (R 4.0.2) #> readr * 1.3.1 2018-12-21 [1] CRAN (R 4.0.2) #> readxl 1.3.1 2019-03-13 [1] CRAN (R 4.0.2) #> remotes 2.2.0 2020-07-21 [1] CRAN (R 4.0.2) #> reprex 0.3.0 2019-05-16 [1] CRAN (R 4.0.3) #> rlang 0.4.7 2020-07-09 [1] CRAN (R 4.0.2) #> rmarkdown 2.4 2020-09-30 [1] CRAN (R 4.0.2) #> rprojroot 1.3-2 2018-01-03 [1] CRAN (R 4.0.2) #> rvest 0.3.6 2020-07-25 [1] CRAN (R 4.0.2) #> scales 1.1.1 2020-05-11 [1] CRAN (R 4.0.2) #> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.2) #> stringi 1.5.3 2020-09-09 [1] CRAN (R 4.0.2) #> stringr * 1.4.0 2019-02-10 [1] CRAN (R 4.0.2) #> testthat 2.3.2 2020-03-02 [1] CRAN (R 4.0.2) #> tibble * 3.0.3 2020-07-10 [1] CRAN (R 4.0.2) #> tidyr * 1.1.2 2020-08-27 [1] CRAN (R 4.0.2) #> tidyselect 1.1.0 2020-05-11 [1] CRAN (R 4.0.2) #> tidyverse * 1.3.0 2019-11-21 [1] CRAN (R 4.0.2) #> usethis 1.6.3 2020-09-17 [1] CRAN (R 4.0.2) #> vctrs 0.3.4 2020-08-29 [1] CRAN (R 4.0.2) #> withr 2.3.0 2020-09-22 [1] CRAN (R 4.0.2) #> xfun 0.18 2020-09-29 [1] CRAN (R 4.0.2) #> xml2 1.3.2 2020-04-23 [1] CRAN (R 4.0.2) #> yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.2) #> #> [1] C:/Users/dfsat/Documents/R/win-library/4.0 #> [2] C:/Program Files/R/R-4.0.2/library ```
elwebster commented 3 years ago 
## Use the script below to generate a reproducible example
## using the reprex package. Use datapasta::dpasta() to create
## `urban` in the script rather than relying on the source
## CSV file. Once you generate it, post it on
## https://github.com/uc-cfss/Discussion/issues/155

library(tidyverse)
library(here)
#> here() starts at C:/Users/elweb/Desktop/reproducible-examples-and-git-master

# import data file
urban <- read_csv(here("data", "urbanization-state.csv"))
#> Parsed with column specification:
#> cols(
#>   state = col_character(),
#>   urbanindex = col_double()
#> )

# how do I reorder the bars from largest to smallest?
ggplot(data = urban, mapping = aes(x = state, y = urbanindex)) +
  geom_col() +
  coord_flip()

Created on 2020-11-05 by the reprex package (v0.3.0)

ssmarkow commented 3 years ago 
urban_small <- tibble::tribble(
            ~state, ~urbanindex,
         "Alabama",    9.605935,
          "Alaska",    8.735964,
  "American Samoa",    11.08593,
         "Arizona",    11.29971,
        "Arkansas",    9.259444,
      "California",    12.19028
  )

ggplot(data = urban_small, mapping = aes(x = state, y = urbanindex)) +
  geom_col() +
  coord_flip()
#> Error in ggplot(data = urban_small, mapping = aes(x = state, y = urbanindex)): could not find function "ggplot"
nbrown20 commented 3 years ago 

library(tidyverse)
library(here)
#> here() starts at /tmp/RtmpXFpYcO/reprexf598d13863f8e

urban2 <- tibble::tribble(
            ~state, ~urbanindex,
         "Alabama",    9.605935,
          "Alaska",    8.735964,
  "American Samoa",    11.08593,
         "Arizona",    11.29971,
        "Arkansas",    9.259444,
      "California",    12.19028
  )

# how do I reorder the bars from largest to smallest?
ggplot(data = urban2, mapping = aes(x = state, y = urbanindex)) +
  geom_col() +
  coord_flip()

Created on 2020-11-05 by the reprex package (v0.3.0)

Session info ``` r devtools::session_info() #> ─ Session info ─────────────────────────────────────────────────────────────── #> setting value #> version R version 4.0.1 (2020-06-06) #> os Red Hat Enterprise Linux 8.2 (Ootpa) #> system x86_64, linux-gnu #> ui X11 #> language (EN) #> collate en_US.UTF-8 #> ctype en_US.UTF-8 #> tz America/Chicago #> date 2020-11-05 #> #> ─ Packages ─────────────────────────────────────────────────────────────────── #> package * version date lib source #> assertthat 0.2.1 2019-03-21 [2] CRAN (R 4.0.1) #> backports 1.1.9 2020-08-24 [2] CRAN (R 4.0.1) #> blob 1.2.1 2020-01-20 [2] CRAN (R 4.0.1) #> broom 0.7.0 2020-07-09 [2] CRAN (R 4.0.1) #> callr 3.4.3 2020-03-28 [2] CRAN (R 4.0.1) #> cellranger 1.1.0 2016-07-27 [2] CRAN (R 4.0.1) #> cli 2.0.2 2020-02-28 [2] CRAN (R 4.0.1) #> colorspace 1.4-1 2019-03-18 [2] CRAN (R 4.0.1) #> crayon 1.3.4 2017-09-16 [2] CRAN (R 4.0.1) #> curl 4.3 2019-12-02 [2] CRAN (R 4.0.1) #> DBI 1.1.0 2019-12-15 [2] CRAN (R 4.0.1) #> dbplyr 1.4.4 2020-05-27 [2] CRAN (R 4.0.1) #> desc 1.2.0 2018-05-01 [2] CRAN (R 4.0.1) #> devtools 2.3.1 2020-07-21 [2] CRAN (R 4.0.1) #> digest 0.6.27 2020-10-24 [1] CRAN (R 4.0.1) #> dplyr * 1.0.2 2020-08-18 [1] CRAN (R 4.0.1) #> ellipsis 0.3.1 2020-05-15 [2] CRAN (R 4.0.1) #> evaluate 0.14 2019-05-28 [2] CRAN (R 4.0.1) #> fansi 0.4.1 2020-01-08 [2] CRAN (R 4.0.1) #> farver 2.0.3 2020-01-16 [2] CRAN (R 4.0.1) #> forcats * 0.5.0 2020-03-01 [2] CRAN (R 4.0.1) #> fs 1.5.0 2020-07-31 [2] CRAN (R 4.0.1) #> generics 0.0.2 2018-11-29 [2] CRAN (R 4.0.1) #> ggplot2 * 3.3.2 2020-06-19 [2] CRAN (R 4.0.1) #> glue 1.4.2 2020-08-27 [1] CRAN (R 4.0.1) #> gtable 0.3.0 2019-03-25 [2] CRAN (R 4.0.1) #> haven 2.3.1 2020-06-01 [2] CRAN (R 4.0.1) #> here * 0.1 2017-05-28 [2] CRAN (R 4.0.1) #> highr 0.8 2019-03-20 [2] CRAN (R 4.0.1) #> hms 0.5.3 2020-01-08 [2] CRAN (R 4.0.1) #> htmltools 0.5.0 2020-06-16 [1] CRAN (R 4.0.1) #> httr 1.4.2 2020-07-20 [2] CRAN (R 4.0.1) #> jsonlite 1.7.1 2020-09-07 [1] CRAN (R 4.0.1) #> knitr 1.30 2020-09-22 [1] CRAN (R 4.0.1) #> labeling 0.3 2014-08-23 [2] CRAN (R 4.0.1) #> lifecycle 0.2.0 2020-03-06 [2] CRAN (R 4.0.1) #> lubridate 1.7.9 2020-06-08 [1] CRAN (R 4.0.1) #> magrittr 1.5 2014-11-22 [2] CRAN (R 4.0.1) #> memoise 1.1.0 2017-04-21 [2] CRAN (R 4.0.1) #> mime 0.9 2020-02-04 [2] CRAN (R 4.0.1) #> modelr 0.1.8 2020-05-19 [2] CRAN (R 4.0.1) #> munsell 0.5.0 2018-06-12 [2] CRAN (R 4.0.1) #> pillar 1.4.6 2020-07-10 [2] CRAN (R 4.0.1) #> pkgbuild 1.1.0 2020-07-13 [2] CRAN (R 4.0.1) #> pkgconfig 2.0.3 2019-09-22 [2] CRAN (R 4.0.1) #> pkgload 1.1.0 2020-05-29 [2] CRAN (R 4.0.1) #> prettyunits 1.1.1 2020-01-24 [2] CRAN (R 4.0.1) #> processx 3.4.3 2020-07-05 [2] CRAN (R 4.0.1) #> ps 1.3.4 2020-08-11 [2] CRAN (R 4.0.1) #> purrr * 0.3.4 2020-04-17 [2] CRAN (R 4.0.1) #> R6 2.4.1 2019-11-12 [2] CRAN (R 4.0.1) #> Rcpp 1.0.5 2020-07-06 [2] CRAN (R 4.0.1) #> readr * 1.3.1 2018-12-21 [2] CRAN (R 4.0.1) #> readxl 1.3.1 2019-03-13 [2] CRAN (R 4.0.1) #> remotes 2.2.0 2020-07-21 [2] CRAN (R 4.0.1) #> reprex 0.3.0 2019-05-16 [2] CRAN (R 4.0.1) #> rlang 0.4.8 2020-10-08 [1] CRAN (R 4.0.1) #> rmarkdown 2.5.3 2020-10-31 [1] Github (rstudio/rmarkdown@62d9b6b) #> rprojroot 1.3-2 2018-01-03 [2] CRAN (R 4.0.1) #> rvest 0.3.6 2020-07-25 [2] CRAN (R 4.0.1) #> scales 1.1.1 2020-05-11 [1] CRAN (R 4.0.1) #> sessioninfo 1.1.1 2018-11-05 [2] CRAN (R 4.0.1) #> stringi 1.5.3 2020-09-09 [1] CRAN (R 4.0.1) #> stringr * 1.4.0 2019-02-10 [2] CRAN (R 4.0.1) #> testthat 2.3.2 2020-03-02 [2] CRAN (R 4.0.1) #> tibble * 3.0.3 2020-07-10 [2] CRAN (R 4.0.1) #> tidyr * 1.1.1 2020-07-31 [2] CRAN (R 4.0.1) #> tidyselect 1.1.0 2020-05-11 [2] CRAN (R 4.0.1) #> tidyverse * 1.3.0 2019-11-21 [2] CRAN (R 4.0.1) #> usethis 1.6.1 2020-04-29 [2] CRAN (R 4.0.1) #> vctrs 0.3.2 2020-07-15 [2] CRAN (R 4.0.1) #> withr 2.2.0 2020-04-20 [2] CRAN (R 4.0.1) #> xfun 0.19 2020-10-30 [1] CRAN (R 4.0.1) #> xml2 1.3.2 2020-04-23 [2] CRAN (R 4.0.1) #> yaml 2.2.1 2020-02-01 [2] CRAN (R 4.0.1) #> #> [1] /home/nbrown20/R/x86_64-pc-linux-gnu-library/4.0 #> [2] /opt/R/4.0.1/lib/R/library ```
sharanyabashyam commented 3 years ago

library(tidyverse)

# import data file
urban <- tibble::tribble(
  ~state, ~urbanindex,
  "Alabama",    9.605935,
  "Alaska",    8.735964,
  "American Samoa",    11.08593,
  "Arizona",    11.29971,
  "Arkansas",    9.259444,
  "California",    12.19028
)

# how do I reorder the bars from largest to smallest?
ggplot(data = urban, mapping = aes(x = state, y = urbanindex)) +
  geom_col() +
  coord_flip()
kaitlynvanbaalen commented 3 years ago 
library(tidyverse)
library(here)
#> here() starts at /private/var/folders/hb/llpc00gj2tb6cqsc6wv4k0qw0000gn/T/RtmpXidWiF/reprex6469239ab833

# import data file
urban <- tibble::tribble(
  ~state, ~urbanindex,
  "Alabama", 9.605935,
  "Alaska", 8.735964,
  "American Samoa", 11.08593,
  "Arizona", 11.29971,
  "Arkansas", 9.259444,
)

# how do I reorder the bars from largest to smallest?
ggplot(data = urban, mapping = aes(x = state, y = urbanindex)) +
  geom_col() +
  coord_flip()

Created on 2020-11-05 by the reprex package (v0.3.0)

ktownsend3 commented 3 years ago 
library(tidyverse)
library(here)
#> here() starts at /tmp/RtmpTpGrbr/reprexf613e32ac5cb6

urban <- tibble::tribble(
  ~state, ~urbanindex,
  "Alabama", 9.605935,
  "Alaska", 8.735964,
  "American Samoa", 11.08593,
  "Arizona", 11.29971,
  "Arkansas", 9.259444,
  "California", 12.19028,
  "Colorado", 11.15445,
  "Connecticut", 11.40968
)

# how do I reorder the bars from largest to smallest?
ggplot(data = urban, mapping = aes(x = state, y = urbanindex)) +
  geom_col() +
  coord_flip()

Created on 2020-11-05 by the reprex package (v0.3.0)