markdown R Census API数据

Posted 2021-05-05

---
title: "Census"
author: "Tim Kluis"
date: "4/11/2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## Census 

This is an overview of how to utilize TidyCensus for data analysis that requires demographic information. The censusapi tutorial can be found at https://cran.r-project.org/web/packages/censusapi/vignettes/getting-started.html. Additional online documentation can be found at https://www.census.gov/data/developers/data-sets.html.

## Load Required Libraries

```{r libraries}
install.packages("censusapi")
library(tidyverse) 		# General package for standardize R programming
library(censusapi)		# Simplified Census API package
library(sqldf) 			  # Package that allows SQL programming
library(RPostgreSQL) 	# Package that controls PostgreSQL Database
```

## Identify Census API Key

You need to apply with the Census to obtain an API key to access their online database

```{r apikey, echo=FALSE}
# Add key to .Renviron
Sys.setenv(CENSUS_KEY="e230244144eac2f1fd00198c98b15ecd1afcf6ad")

# Check to see that the expected key is output in your R console
Sys.getenv("CENSUS_KEY")
```

## Gather APIs available from Census

In order to know the APIs that are available to utilize you need to leverage the listCensusApisfunction.

```{r apis}
apis <- listCensusApis()
View(apis)
```


## Gather Varlists from Census

In order to know the variables that are available to utilize you need to leverage the listCensusMetadata function. You need to location the name from the apis dataframe to place in the function to determine the type = variables.

```{r varlists}
sahie_vars <- listCensusMetadata(name = "timeseries/healthins/sahie", 
    type = "variables")
head(sahie_vars)
```

## Gather Geographies to leveage from Census

In order to know the geography levels that are available to utilize you need to leverage the listCensusMetadata function. You need to locate the geography from the apis dataframe to place in the function to determine the type = geography.

```{r geography}
sahie_geos <- listCensusMetadata(name = "timeseries/healthins/sahie", 
    type = "geography")
head(sahie_geos)
```

## Gather Data from Census

In order to gather the data from the census you need to leverage the getCensus function. Key variables in the function are name, vars, region, time)

```{r gatherdata}
sahie_states <- getCensus(name = "timeseries/healthins/sahie",
    vars = c("NAME", "IPRCAT", "IPR_DESC", "PCTUI_PT"), 
    region = "state:*", 
    time = 2016)
head(sahie_states)
```


```{r gatherdata2}
sahie_counties <- getCensus(name = "timeseries/healthins/sahie",
    vars = c("NAME", "IPRCAT", "IPR_DESC", "PCTUI_PT"), 
    region = "county:*", 
    regionin = "state:01,02", 
    time = 2017)
head(sahie_counties, n=12L)
```

```{r gatherdata3}
sahie_years <- getCensus(name = "timeseries/healthins/sahie",
    vars = c("NAME", "PCTUI_PT"), 
    region = "state:01", 
    time = "from 2006 to 2017")
head(sahie_years)
```