Greg Freedman Ellis gergness

## covdata_excess.md

      
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                gergness
                / covdata_excess.md
            
            
              Created
              September 23, 2020 01:43
            
          
    suppressPackageStartupMessages({
    library(covdata)
    library(dplyr)
    library(ggplot2)
    library(geofacet)
    library(glue)
})
pop_state <- uspop %>%
    filter(sex_id == "totsex" & hisp_id == "tothisp") %>%

  
## answerbase2623637_1.Rmd
This is I think closest to what was described, however it holds all of the data in memory still...

``` r
library(ipumsr)
ddi <- read_ipums_ddi(ipums_example("cps_00006.xml"))

# (These are just the names for an extract included with ipumsr - they stand in for
# REPWT1-REPWT40, REPWT41-REPWT80, etc.)
var_groups <- list(
  HH_RE1 = tidyselect::vars_select(ddi$var_info$var_name, YEAR:SERIAL),

## nhgis_cartogram.R
library(purrr)
library(ipumsr) # requires development version: devtools::install_github("mnpopcenter/ipumsr")
library(rmapshaper)
library(ggplot2)
library(gganimate) # devtools::install_github("thomasp85/gganimate")
library(stringr)
library(dplyr)
library(tidyr)
library(cartogram)
library(sf)

## ipumsr-bigdata.html
<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8">


<meta name="generator" content="pandoc">

<meta name="viewport" content="width=device-width, initial-scale=1">

<meta name="author" content="Minnesota Population Center">

## ipumsr-bigdata.html
<!DOCTYPE html>

<html xmlns="http://www.w3.org/1999/xhtml">

<head>

<meta charset="utf-8" />
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="generator" content="pandoc" />

## transformr.Rmd
Hitting an error with transformr, not sure if I'm specifying it wrong though...

``` r
library(tidycensus)
library(rmapshaper)
library(cartogram)
library(sf)
#> Linking to GEOS 3.6.1, GDAL 2.2.3, proj.4 4.9.3
library(transformr)
library(ggplot2)

## gist.html
<!DOCTYPE html>

<html xmlns="http://www.w3.org/1999/xhtml">

<head>

<meta charset="utf-8" />
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="generator" content="pandoc" />

## survey_arrange.Rmd
``` r
suppressPackageStartupMessages({
  library(survey)
  library(srvyr)
  library(dplyr)
})
# stratified sample from examples
data(api)
dstrata <- apistrat %>%
  as_survey(strata = stype, weights = pw)
	This is I think closest to what was described, however it holds all of the data in memory still...

	``` r
	library(ipumsr)
	ddi <- read_ipums_ddi(ipums_example("cps_00006.xml"))

	# (These are just the names for an extract included with ipumsr - they stand in for
	# REPWT1-REPWT40, REPWT41-REPWT80, etc.)
	var_groups <- list(
	HH_RE1 = tidyselect::vars_select(ddi$var_info$var_name, YEAR:SERIAL),
	library(purrr)
	library(ipumsr) # requires development version: devtools::install_github("mnpopcenter/ipumsr")
	library(rmapshaper)
	library(ggplot2)
	library(gganimate) # devtools::install_github("thomasp85/gganimate")
	library(stringr)
	library(dplyr)
	library(tidyr)
	library(cartogram)
	library(sf)
	<!DOCTYPE html>
	<html xmlns="http://www.w3.org/1999/xhtml"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8">



	<meta name="generator" content="pandoc">

	<meta name="viewport" content="width=device-width, initial-scale=1">

	<meta name="author" content="Minnesota Population Center">
	<!DOCTYPE html>

	<html xmlns="http://www.w3.org/1999/xhtml">

	<head>

	<meta charset="utf-8" />
	<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
	<meta name="generator" content="pandoc" />
	Hitting an error with transformr, not sure if I'm specifying it wrong though...

	``` r
	library(tidycensus)
	library(rmapshaper)
	library(cartogram)
	library(sf)
	#> Linking to GEOS 3.6.1, GDAL 2.2.3, proj.4 4.9.3
	library(transformr)
	library(ggplot2)
	``` r
	suppressPackageStartupMessages({
	library(survey)
	library(srvyr)
	library(dplyr)
	})
	# stratified sample from examples
	data(api)
	dstrata <- apistrat %>%
	as_survey(strata = stype, weights = pw)