2017-03-04 49 views
0

以下工作:爲什麼我無法使用R package acs從SF1獲得國家和ZCTA級別的估計?

acs::acs.fetch(dataset = "acs", 
       endyear = 2015, 
       span = 5, 
       geography = acs::geo.make(zip = "*"), 
       variable = "B01001_001") 

那麼,這是否:

acs::acs.fetch(dataset = "sf1", 
       endyear = 2010, 
       span = 0, 
       geography = acs::geo.make(state = "*"), 
       variable = "PCT0120001") 

,因爲沒有提供郵政編碼水平測算請向我解釋爲什麼後續不工作,因爲它不是人口普查API。我是否需要以不同的方式指定地理位置,才能從sf1獲取國家和ZCTA級別的估算值,而不是從人口普查API中的acs5中獲取?

acs::acs.fetch(dataset = "sf1", 
       endyear = 2010, 
       span = 0, 
       geography = acs::geo.make(zip = "*"), 
       variable = "PCT0120001") 
# Error in file(file, "rt") : cannot open the connection 
# In addition: Warning message: 
# No data found at: 
# http://api.census.gov/data/2010/sf1?key=2dd03c4048ca2edb8463d8c0bbdc09c5eb3b4013&get=PCT0120001,NAME&for=zip+code+tabulation+area:* 

acs::acs.fetch(dataset = "sf1", 
       endyear = 2010, 
       span = 0, 
       geography = acs::geo.make(us = "*"), 
       variable = "PCT0120001") 
# Error in file(file, "rt") : cannot open the connection 
# In addition: Warning message: 
# No data found at: 
# http://api.census.gov/data/2010/sf1?key=2dd03c4048ca2edb8463d8c0bbdc09c5eb3b4013&get=PCT0120001,NAME&for=us:* 

回答

0

您可以使用totalcensus package下載摘要文件並提取每個郵政編碼中的數據。數據被下載到您自己的計算機中,因此訪問數據不受人口普查API的限制。

library(totalcensus) 
aaa <- read_decennial(
    year = 2010, 
    states = "US", 
    table_contents = "PCT0120001", 
    geo_headers = "ZCTA5", 
    summary_level = "860" 
) 


print(aaa) 

#    lon  lat ZCTA5 state population PCT0120001 GEOCOMP SUMLEV 
#  1: -66.74996 18.18056 00601 NA  18570  18570  all 860 
#  2: -67.17613 18.36227 00602 NA  41520  41520  all 860 
#  3: -67.11989 18.45518 00603 NA  54689  54689  all 860 
#  4: -66.93291 18.15835 00606 NA  6615  6615  all 860 
#  5: -67.12587 18.29096 00610 NA  29016  29016  all 860 
# ---                  
# 33116: -130.04103 56.00232 99923 NA   87   87  all 860 
# 33117: -132.94593 55.55020 99925 NA  819  819  all 860 
# 33118: -131.47074 55.13807 99926 NA  1460  1460  all 860 
# 33119: -133.45792 56.23906 99927 NA   94   94  all 860 
# 33120: -131.60683 56.41383 99929 NA  2338  2338  all 860 
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