~hrbrmstr/epidata

47b2d52f37909c0b01ad02edd12decb043a1dfb6 — hrbrmstr 2 years ago e12c13d 
readme
patch browse 
3 files changed, 64 insertions(+), 72 deletions(-)

M README.Rmd
M README.md
A man/figures/README-unnamed-chunk-4-1.png

M README.Rmd => README.Rmd +8 -0
@@ 3,6 3,14 @@ output: rmarkdown::github_document
---

```{r message=FALSE, warning=FALSE, error=FALSE, include=FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "##",
  fig.path = "man/figures/README-",
  out.width = "100%",
  message = FALSE,
  warning = FALSE
)
options(width=120)
```



M README.md => README.md +56 -72
@@ 80,70 80,60 @@ library(epidata)

# current verison
packageVersion("epidata")
```

    ## [1] '0.3.0'
## [1] '0.3.0'

``` r
get_black_white_wage_gap()
```
## # A tibble: 46 x 8
##     date white_median white_average black_median black_average gap_median gap_average gap_regression_based
##    <dbl>        <dbl>         <dbl>        <dbl>         <dbl>      <dbl>       <dbl>                <dbl>
##  1  1973         17.6          20.4         13.7          16.0      0.223       0.215              NA     
##  2  1974         17.2          19.9         13.8          15.8      0.198       0.209              NA     
##  3  1975         17.1          20           13.9          15.8      0.191       0.208              NA     
##  4  1976         17.2          20.1         14.0          16.5      0.19        0.182              NA     
##  5  1977         17.2          20.1         13.9          16.2      0.188       0.19               NA     
##  6  1978         17.4          20.1         13.9          16.4      0.201       0.186              NA     
##  7  1979         17.1          20.3         14.3          16.8      0.164       0.173               0.086 
##  8  1980         17.1          19.9         14.1          16.4      0.173       0.174               0.086 
##  9  1981         16.7          19.8         13.8          16.4      0.175       0.174               0.0820
## 10  1982         16.9          20.0         13.7          16.2      0.194       0.191               0.099 
## # … with 36 more rows

    ## # A tibble: 46 x 8
    ##     date white_median white_average black_median black_average gap_median gap_average gap_regression_based
    ##    <dbl>        <dbl>         <dbl>        <dbl>         <dbl>      <dbl>       <dbl>                <dbl>
    ##  1  1973         17.6          20.4         13.7          16.0      0.223       0.215              NA     
    ##  2  1974         17.2          19.9         13.8          15.8      0.198       0.209              NA     
    ##  3  1975         17.1          20           13.9          15.8      0.191       0.208              NA     
    ##  4  1976         17.2          20.1         14.0          16.5      0.19        0.182              NA     
    ##  5  1977         17.2          20.1         13.9          16.2      0.188       0.19               NA     
    ##  6  1978         17.4          20.1         13.9          16.4      0.201       0.186              NA     
    ##  7  1979         17.1          20.3         14.3          16.8      0.164       0.173               0.086 
    ##  8  1980         17.1          19.9         14.1          16.4      0.173       0.174               0.086 
    ##  9  1981         16.7          19.8         13.8          16.4      0.175       0.174               0.0820
    ## 10  1982         16.9          20.0         13.7          16.2      0.194       0.191               0.099 
    ## # … with 36 more rows

``` r
get_underemployment()
```

    ## # A tibble: 325 x 2
    ##    date         all
    ##    <date>     <dbl>
    ##  1 1989-12-01 0.093
    ##  2 1990-01-01 0.093
    ##  3 1990-02-01 0.093
    ##  4 1990-03-01 0.094
    ##  5 1990-04-01 0.094
    ##  6 1990-05-01 0.094
    ##  7 1990-06-01 0.094
    ##  8 1990-07-01 0.094
    ##  9 1990-08-01 0.095
    ## 10 1990-09-01 0.095
    ## # … with 315 more rows
## # A tibble: 325 x 2
##    date         all
##    <date>     <dbl>
##  1 1989-12-01 0.093
##  2 1990-01-01 0.093
##  3 1990-02-01 0.093
##  4 1990-03-01 0.094
##  5 1990-04-01 0.094
##  6 1990-05-01 0.094
##  7 1990-06-01 0.094
##  8 1990-07-01 0.094
##  9 1990-08-01 0.095
## 10 1990-09-01 0.095
## # … with 315 more rows

``` r
get_median_and_mean_wages("gr")
## # A tibble: 46 x 25
##     date median average men_median men_average women_median women_average white_median white_average black_median
##    <dbl>  <dbl>   <dbl>      <dbl>       <dbl>        <dbl>         <dbl>        <dbl>         <dbl>        <dbl>
##  1  1973   17.0    19.7       20.6        23.1         13.0          14.9         17.6          20.4         13.7
##  2  1974   16.6    19.4       20.3        22.7         12.8          14.6         17.2          19.9         13.8
##  3  1975   16.6    19.4       20.7        22.7         12.9          14.8         17.1          20           13.9
##  4  1976   16.6    19.6       20.3        22.9         13.1          15.1         17.2          20.1         14.0
##  5  1977   16.6    19.5       20.5        22.9         13.0          15.0         17.2          20.1         13.9
##  6  1978   16.8    19.6       20.8        23.0         13.0          15.0         17.4          20.1         13.9
##  7  1979   16.5    19.7       20.7        23.2         13.1          15.2         17.1          20.3         14.3
##  8  1980   16.4    19.4       20.5        22.8         13.1          15.1         17.1          19.9         14.1
##  9  1981   16.2    19.2       20.1        22.6         13.1          15.1         16.7          19.8         13.8
## 10  1982   16.1    19.4       20.1        22.8         13.0          15.3         16.9          20.0         13.7
## # … with 36 more rows, and 15 more variables: black_average <dbl>, hispanic_median <dbl>, hispanic_average <dbl>,
## #   white_men_median <dbl>, white_men_average <dbl>, black_men_median <dbl>, black_men_average <dbl>,
## #   hispanic_men_median <dbl>, hispanic_men_average <dbl>, white_women_median <dbl>, white_women_average <dbl>,
## #   black_women_median <dbl>, black_women_average <dbl>, hispanic_women_median <dbl>, hispanic_women_average <dbl>
```

    ## # A tibble: 46 x 25
    ##     date median average men_median men_average women_median women_average white_median white_average black_median
    ##    <dbl>  <dbl>   <dbl>      <dbl>       <dbl>        <dbl>         <dbl>        <dbl>         <dbl>        <dbl>
    ##  1  1973   17.0    19.7       20.6        23.1         13.0          14.9         17.6          20.4         13.7
    ##  2  1974   16.6    19.4       20.3        22.7         12.8          14.6         17.2          19.9         13.8
    ##  3  1975   16.6    19.4       20.7        22.7         12.9          14.8         17.1          20           13.9
    ##  4  1976   16.6    19.6       20.3        22.9         13.1          15.1         17.2          20.1         14.0
    ##  5  1977   16.6    19.5       20.5        22.9         13.0          15.0         17.2          20.1         13.9
    ##  6  1978   16.8    19.6       20.8        23.0         13.0          15.0         17.4          20.1         13.9
    ##  7  1979   16.5    19.7       20.7        23.2         13.1          15.2         17.1          20.3         14.3
    ##  8  1980   16.4    19.4       20.5        22.8         13.1          15.1         17.1          19.9         14.1
    ##  9  1981   16.2    19.2       20.1        22.6         13.1          15.1         16.7          19.8         13.8
    ## 10  1982   16.1    19.4       20.1        22.8         13.0          15.3         16.9          20.0         13.7
    ## # … with 36 more rows, and 15 more variables: black_average <dbl>, hispanic_median <dbl>, hispanic_average <dbl>,
    ## #   white_men_median <dbl>, white_men_average <dbl>, black_men_median <dbl>, black_men_average <dbl>,
    ## #   hispanic_men_median <dbl>, hispanic_men_average <dbl>, white_women_median <dbl>, white_women_average <dbl>,
    ## #   black_women_median <dbl>, black_women_average <dbl>, hispanic_women_median <dbl>, hispanic_women_average <dbl>

## Extended Example

``` r


@@ 156,24 146,18 @@ unemployment <- get_unemployment()
wages <- get_median_and_mean_wages()

glimpse(wages)
```

    ## Observations: 46
    ## Variables: 3
    ## $ date    <dbl> 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989,…
    ## $ median  <dbl> 16.96, 16.63, 16.64, 16.60, 16.62, 16.77, 16.49, 16.38, 16.21, 16.14, 16.17, 16.26, 16.51, 16.62, 16.…
    ## $ average <dbl> 19.73, 19.37, 19.41, 19.63, 19.53, 19.57, 19.74, 19.35, 19.24, 19.41, 19.45, 19.52, 19.73, 20.20, 20.…
## Observations: 46
## Variables: 3
## $ date    <dbl> 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989,…
## $ median  <dbl> 16.96, 16.63, 16.64, 16.60, 16.62, 16.77, 16.49, 16.38, 16.21, 16.14, 16.17, 16.26, 16.51, 16.62, 16.…
## $ average <dbl> 19.73, 19.37, 19.41, 19.63, 19.53, 19.57, 19.74, 19.35, 19.24, 19.41, 19.45, 19.52, 19.73, 20.20, 20.…

``` r
glimpse(unemployment)
```
## Observations: 457
## Variables: 2
## $ date <date> 1978-12-01, 1979-01-01, 1979-02-01, 1979-03-01, 1979-04-01, 1979-05-01, 1979-06-01, 1979-07-01, 1979-08…
## $ all  <dbl> 0.061, 0.061, 0.060, 0.060, 0.059, 0.059, 0.059, 0.058, 0.058, 0.058, 0.059, 0.059, 0.059, 0.059, 0.059,…

    ## Observations: 457
    ## Variables: 2
    ## $ date <date> 1978-12-01, 1979-01-01, 1979-02-01, 1979-03-01, 1979-04-01, 1979-05-01, 1979-06-01, 1979-07-01, 1979-08…
    ## $ all  <dbl> 0.061, 0.061, 0.060, 0.060, 0.059, 0.059, 0.059, 0.058, 0.058, 0.058, 0.059, 0.059, 0.059, 0.059, 0.059,…

``` r
group_by(unemployment, date=as.integer(lubridate::year(date))) %>%
  summarise(rate=mean(all)) %>%
  left_join(select(wages, date, median), by="date") %>%


@@ 202,4 186,4 @@ ggplot(df, aes(rate, median)) +
  theme_ipsum_rc(grid="XY")
```

<img src="README_files/figure-gfm/unnamed-chunk-4-1.png" width="960" />
<img src="man/figures/README-unnamed-chunk-4-1.png" width="100%" />


A man/figures/README-unnamed-chunk-4-1.png => man/figures/README-unnamed-chunk-4-1.png +0 -0