我如何使用R从美国事实发现者下载数据

Question

在与我以前的问题有关的问题中，我想知道如何从美国事实查找器下载数据。根据美国事实发现者的深链接指南，通往链接的HTTP路径非常规律，并且随着时间的流逝仍然保持一致。DeepLink指南介绍了如何到达桌子的示例，即：

展示表B07010 2006-2008美国社区调查 美国阿拉巴马州和阿拉巴马州奥塔加县的3年估算： http://factfinder.census.gov/bkmk/table/1.0/en/acs/08_3YR/B07010/0100000US|0400000US01|05000 00US01001

，但我不确定如何将'视图转换为r。

中的"下载"

我目前的调查基于这些线程：

1. 使用R下载zpipted数据文件，提取和导入数据
2. 使用r下载zipped数据文件，提取和导入csv
3. 从人口普查2010的导出数据
4. 使用R
下载人口普查数据
5. 如何使用人口普查API提取数据

我将在解决方案时更新此帖子。

Answer 1

这是我迄今为止发现的最有效的解决方案：

使用ACS，Tigris和传单包在R中操纵和映射我们的人口普查数据

library(tigris)
library(acs)
library(stringr) #to pad fips codes
library(gdtools)
#grab the spatial data (tigris)
#note that you can use the county names inthe tigris package but not in the acs.fetch function from the ACS pacakge so I'm using FIPS numbers here.
#Grab the spatial data
counties<-c(5,47,61,81,85)
#solve the 'an error occurred in the secure channel support'
#firewall issue? #nope. 
#https://www2.census.gov/geo/tiger/GENZ2015/shp/
#download via chrome works fine.
library(gdtools) #did not fix it. 
#libcurl may fix it
#https://stackoverflow.com/questions/29688026/vb6-winhhtp-error-occurred-in-the-secure-channel-support
library(curl)
tracts<-tracts(state='NY', county = c(5,47,61,81,85), cb=TRUE)
#It does!
##----------------get the tabular data--------------------
#zevross.com/blog
#get the tabular data
#in order to do this, you will need an API key from the US Census. 
#Go to https://api.census.gov/data/key_signup.html
#to request one (takes a minute or two) and then 
#use the api.key.install function in the `acs` package to use the key.
api.key.install(key="GETYOUROWNKEEY")
#make a geographic set to grab tabular data (acs)
geo<-geo.make(state=c("NY"), county = c(5,47,61,81,85), tract = "*")
#package not updated to 2013 data, so 2012 used as terminal year
income<-acs.fetch(endyear=2012, span=5, geography=geo, table.number="B19001", col.names ="pretty")
#pretty gives fully column names, not census abbreviation. 
#B19001_001 and *.017 are total income and income over $200k
#what results is not data, but a list of what is available.
names(attributes(income)) #shows what's available
attr(income, "acs.colnames")
#convert to data frame for merging. 
income_df<-data.frame(paste0(
                            str_pad(income@geography$state,2,"left", pad="0"),
                            str_pad(income@geography$county,3,"left", pad = "0"),
                            str_pad(income@geography$tract,6,"left", pad="0")),
                            income@estimate[,c(
                                    "Household Income: Total:",
                                    "Household Income: $200,000 or more")], 
                                    stringsAsFactors=FALSE)
                                    #that worked, 12/18/2017                                                       
library(dplyr) #required for select
income_df<-select(income_df, 1:3)
rownames(income_df)<-1:nrow(income_df)
names(income_df)<-c("GEOID","total","over_200")
income_df$percent <-100*(income_df$over_200/income_df$total)
#works!