. local date = "08-10-2020"
. import delimited "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_
> covid_19_daily_reports/`date'.csv", clear
(14 vars, 3,940 obs)
. describe
Contains data
obs: 3,940
vars: 14
-------------------------------------------------------------------------------------------------------------
storage display value
variable name type format label variable label
-------------------------------------------------------------------------------------------------------------
fips long %12.0g FIPS
admin2 str41 %41s Admin2
province_state str40 %40s Province_State
country_region str32 %32s Country_Region
last_update str19 %19s Last_Update
lat float %9.0g Lat
long_ float %9.0g Long_
confirmed long %12.0g Confirmed
deaths long %12.0g Deaths
recovered long %12.0g Recovered
active long %12.0g Active
combined_key str55 %55s Combined_Key
incidence_rate float %9.0g Incidence_Rate
casefatality_~o float %9.0g Case-Fatality_Ratio
-------------------------------------------------------------------------------------------------------------
Sorted by:
Note: Dataset has changed since last saved.
import excel
. import excel "./data/广东数据/广东省新冠肺炎疫情基本情况统计表_1595314944557.xlsx", clear
(8 vars, 27 obs)
. describe
Contains data
obs: 27
vars: 8
-------------------------------------------------------------------------------------------------------------
storage display value
variable name type format label variable label
-------------------------------------------------------------------------------------------------------------
A str78 %78s
B str9 %9s
C str12 %12s
D str12 %12s
E str6 %9s
F str6 %9s
G str12 %12s
H str13 %13s
-------------------------------------------------------------------------------------------------------------
Sorted by:
Note: Dataset has changed since last saved.
import spss
. import spss using "./data/manipulate.sav", clear
(7 vars, 100 obs)
. list in 1/5
+-----------------------------------------------------------------------------------------------------+
| ID Sex FundCode ArrivalDate EmergDate DischargeDate Length~y |
|-----------------------------------------------------------------------------------------------------|
1. | 1 M HOS 10-Mar-2005 03:04:00 10-Mar-2005 05:09:00 16-Mar-2005 13:00:00 6 |
2. | 2 M HOS 27-Aug-2004 12:32:00 27-Aug-2004 13:10:00 27-Aug-2004 14:00:00 0 |
3. | 3 M HOS 19-Feb-2005 19:18:00 20-Feb-2005 03:39:00 25-Feb-2005 01:00:00 5 |
4. | 4 M TAC 24-Sep-2007 09:35:00 24-Sep-2007 11:38:00 24-Sep-2007 17:05:00 0 |
5. | 5 M TAC 19-Jan-2009 08:39:00 19-Jan-2009 22:06:00 29-Jan-2009 13:01:00 10 |
+-----------------------------------------------------------------------------------------------------+
import sas
. import sas using "./data/psam_p30.sas7bdat", clear
(283 vars, 10,113 obs)
. describe
Contains data
obs: 10,113 PSAM_P30
vars: 283
-------------------------------------------------------------------------------------------------------------
storage display value
variable name type format label variable label
-------------------------------------------------------------------------------------------------------------
RT str1 %1s Record type
SERIALNO str9 %9s Housing unit/GQ person serial number
SPORDER byte %010.2g Person key after swapping
PUMA str5 %5s Puma Code
ST str2 %2s State of current residence
ADJINC str7 %7s Adjustment factor for income and earnings dollar amounts
PWGTP int %010.2g PUMS person weight
AGEP byte %010.2g PUMS Age
CIT str1 %1s Citizenship
CITWP int %010.2g PUMS Year of naturalization write-in
COW str1 %1s Class of worker
DDRS str1 %1s Difficulty dressing
DEAR str1 %1s Hearing difficulty
DEYE str1 %1s Vision difficulty
DOUT str1 %1s Difficulty going out
DPHY str1 %1s Physical difficulty
DRAT str1 %1s Disability rating
DRATX str1 %1s Disability rating checkbox
DREM str1 %1s Difficulty remembering
ENG str1 %1s English ability
FER str1 %1s Fertility
GCL str1 %1s Grandchildren living in house
GCM str1 %1s Months responsible for grandchildren
GCR str1 %1s Responsible for grandchildren
HINS1 str1 %1s Health insurance through employer/union
HINS2 str1 %1s Health insurance purchased directly
HINS3 str1 %1s Health insurance through Medicare
HINS4 str1 %1s Health Insurance through Medicaid/means-tested public coverage
HINS5 str1 %1s Health Insurance through TRICARE/military health coverage
HINS6 str1 %1s Health Insurance through VA Health Care
HINS7 str1 %1s Health insurance through Indian Health Service
INTP long %010.2g PUMS Interest, net rental, etc. income
JWMNP int %010.2g PUMS Minutes to work
JWRIP byte %010.2g PUMS Total riders
JWTR str2 %2s Transportation to work
LANX str1 %1s Speaks another language at home
MAR str1 %1s Marital status
MARHD str1 %1s Divorced in the past 12 months
MARHM str1 %1s Married in the past 12 months
MARHT str1 %1s Times married
MARHW str1 %1s Widowed in the past 12 months
MARHYP int %010.2g PUMS Year last married
MIG str1 %1s Mobility status
MIL str1 %1s Served in Armed Forces
MLPA str1 %1s Active duty -- SEP2001 or later
MLPB str1 %1s Active duty -- AUG1990 to AUG2001
MLPCD str1 %1s Active Duty -- MAY 1975 to JUL 1990
MLPE str1 %1s Active duty -- Vietnam era
MLPFG str1 %1s Active Duty -- FEB 1955 to JUL 1964
MLPH str1 %1s Active duty -- Korean War
MLPI str1 %1s Active duty -- JAN1947 to JUN1950
MLPJ str1 %1s Active duty -- World War II
MLPK str1 %1s Active duty -- NOV1941 or earlier
NWAB str1 %1s Temporarily absent from work
NWAV str1 %1s Available for Work
NWLA str1 %1s On layoff
NWLK str1 %1s Looking for work
NWRE str1 %1s Informed of recall
OIP long %010.2g PUMS Other income amount
PAP int %010.2g PUMS Cash Public Assistance Income
RELP str2 %2s PUMS Relationship to Reference Person
RETP long %010.2g PUMS Retirement income
SCH str1 %1s School enrollment
SCHG str2 %2s Grade level attending
SCHL str2 %2s Educational attainment
SEMP long %010.2g PUMS Self-employment income
SEX str1 %1s Sex
SSIP int %010.2g PUMS Supplemental security income
SSP long %010.2g PUMS Social Security or Railroad Retirement Income
WAGP long %010.2g PUMS Wages/salary income
WKHP byte %010.2g PUMS Hours worked per week
WKL str1 %1s When last worked
WKW str1 %1s Weeks worked past 12 months
WRK str1 %1s Worked last week
YOEP int %010.2g PUMS Year of entry
ANC str1 %1s Ancestry categorization
ANC1P str3 %3s First ancestry 5% code
ANC2P str3 %3s Second ancestry 5% code
DECADE str1 %1s Decade of entry
DIS str1 %1s Disability Recode
DRIVESP str1 %1s Number of vehicles calculated from JWRI
ESP str1 %1s Employment status of parents
ESR str1 %1s Employment Status Recode
FOD1P str4 %4s First Field of Degree 5% code
FOD2P str4 %4s Second Field of Degree 5% code
HICOV str1 %1s Any health insurance coverage
HISP str2 %2s Hispanic recode
INDP str4 %4s Industry recode 5%
JWAP str3 %3s Time of arrival at work categorization
JWDP str3 %3s Time of departure for work categorization
LANP str3 %3s Other language recode 5%
MIGPUMA str5 %5s Migration PUMA
MIGSP str3 %3s Migration state/foreign country recode 5%
MSP str1 %1s Married -- spouse present/ spouse absent
NAICSP str8 %8s NAICS industry code 5%
NATIVITY str1 %1s Nativity
NOP str1 %1s Nativity of Parent
OC str1 %1s Own child
OCCP str4 %4s Occupation recode 5%
PAOC str1 %1s Presence and age of own children
PERNP long %010.2g PUMS Persons earnings (signed)
PINCP long %010.2g PUMS Persons income (signed)
POBP str3 %3s Place of birth 5% code
POVPIP int %010.2g PUMS Poverty index
POWPUMA str5 %5s Place of work PUMA
POWSP str3 %3s Place of work state/fgn countyy recode 5%
PRIVCOV str1 %1s Private health insurance
PUBCOV str1 %1s Public Coverage
QTRBIR str1 %1s Quarter of birth
RAC1P str1 %1s Race1 recode
RAC2P str2 %2s Race2 recode
RAC3P str3 %3s Race3 recode
RACAIAN str1 %1s Race includes AIAN
RACASN str1 %1s Race includes Asian
RACBLK str1 %1s Race includes Black
RACNH str1 %1s Race includes NH
RACNUM str1 %1s Number of race groups represented
RACPI str1 %1s Race includes PI
RACSOR str1 %1s Race includes Other race
RACWHT str1 %1s Race includes White
RC str1 %1s Related child
SCIENGP str1 %1s PUMS Field of Degree Science and Engineering Flag
SCIENGRLP str1 %1s PUMS Field of Degree Science and Engineering Related Flag
SFN str1 %1s Subfamily Number
SFR str1 %1s Subfamily Relationship
SOCP str6 %6s SOC occupation code 5%
VPS str2 %2s Veterans period of service
WAOB str1 %1s World area of birth
FAGEP str1 %1s PUMS Age allocation flag
FANCP str1 %1s PUMS Ancestry Code allocation flag
FCITP str1 %1s PUMS Citizenship allocation flag
FCITWP str1 %1s PUMS Year of naturalization write-in allocation flag
FCOWP str1 %1s PUMS Class of Worker allocation flag
FDDRSP str1 %1s PUMS Difficulty dressing allocation flag
FDEARP str1 %1s PUMS Hearing difficulty allocation
FDEYEP str1 %1s PUMS Vision difficulty allocation
FDISP str1 %1s PUMS Disability Recode allocation flag
FDOUTP str1 %1s PUMS Going Out Difficulty allocation flag
FDPHYP str1 %1s PUMS Physical Activity Difficulty allocation
FDRATP str1 %1s PUMS Disability rating allocation flag
FDRATXP str1 %1s PUMS Disability rating checkbox allocat flag
FDREMP str1 %1s PUMS Remembering Difficulty allocation flag
FENGP str1 %1s PUMS English Ability allocation flag
FESRP str1 %1s PUMS Employment Status Recode allocation flag
FFERP str1 %1s PUMS Fertility allocation flag
FFODP str1 %1s PUMS Field of degree allocation flag
FGCLP str1 %1s PUMS Grandchildren Living at House allocation flag
FGCMP str1 %1s PUMS Months Responsible for Grandchildren allocation flag
FGCRP str1 %1s PUMS Responsibility for Grandchildren allocation flag
FHINS1P str1 %1s PUMS Health insurance allocation flag #1
FHINS2P str1 %1s PUMS Health insurance allocation flag #2
FHINS3C str1 %1s Medicare coverage given through the eligibility coverage edit
FHINS3P str1 %1s PUMS Health insurance allocation flag #3
FHINS4C str1 %1s Medicaid coverage given through the eligibility coverage edit
FHINS4P str1 %1s PUMS Health insurance allocation flag #4
FHINS5C str1 %1s TRICARE coverage given through the eligibility coverage edit
FHINS5P str1 %1s PUMS Health insurance allocation flag #5
FHINS6P str1 %1s PUMS Health insurance allocation flag #6
FHINS7P str1 %1s PUMS Health insurance allocation flag #7
FHISP str1 %1s PUMS Hispanic Origin allocation flag
FINDP str1 %1s PUMS Industry allocation flag
FINTP str1 %1s PUMS Interest allocation flag
FJWDP str1 %1s PUMS Time of Departure for Work allocation flag
FJWMNP str1 %1s PUMS Travel Time to Work allocation flag
FJWRIP str1 %1s PUMS Vehicle Occupancy allocation flag
FJWTRP str1 %1s PUMS Means of Transportation to Work allocation flag
FLANP str1 %1s PUMS Language Spoken allocation flag
FLANXP str1 %1s PUMS Non-English Language allocation flag
FMARHDP str1 %1s PUMS Divorced in past 12 months allocation flag
FMARHMP str1 %1s PUMS Married in past 12 months allocation flag
FMARHTP str1 %1s PUMS Times married allocation flag
FMARHWP str1 %1s PUMS Widowed in past 12 months allocation flag
FMARHYP str1 %1s PUMS Year last married allocation flag
FMARP str1 %1s PUMS Marital Status allocation flag
FMIGP str1 %1s PUMS Mobility Status allocation flag
FMIGSP str1 %1s PUMS Migration State allocation flag
FMILPP str1 %1s PUMS Period of Service allocation flag
FMILSP str1 %1s PUMS Veteran Status allocation flag
FOCCP str1 %1s PUMS Occupation allocation flag
FOIP str1 %1s PUMS Other Income allocation flag
FPAP str1 %1s PUMS Public Assistance Income allocation flag
FPERNP str1 %1s PUMS Total Persons Earnings allocation flag
FPINCP str1 %1s PUMS Total Persons Income allocation flag
FPOBP str1 %1s PUMS Place of Birth allocation flag
FPOWSP str1 %1s PUMS Place of Work State allocation flag
FPRIVCOVP str1 %1s PUMS Private Health Insurance Coverage allocation flag
FPUBCOVP str1 %1s PUMS Public Health Insurance Coverage allocation flag
FRACP str1 %1s PUMS Race allocation flag
FRELP str1 %1s PUMS Relationship allocation flag
FRETP str1 %1s PUMS Retirement Income allocation flag
FSCHGP str1 %1s PUMS Grade Attending allocation flag
FSCHLP str1 %1s PUMS Educational Attainment allocation flag
FSCHP str1 %1s PUMS School Enrollment allocation flag
FSEMP str1 %1s PUMS Self-employment Income allocation flag
FSEXP str1 %1s PUMS Sex allocation flag
FSSIP str1 %1s PUMS Suplemental Security Income allocation flag
FSSP str1 %1s PUMS Social Security Income allocation flag
FWAGP str1 %1s PUMS Wages/Salary Income allocation flag
FWKHP str1 %1s PUMS Hours Worked Per Week allocation flag
FWKLP str1 %1s PUMS When Last Worked allocation flag
FWKWP str1 %1s PUMS Weeks Worked Past 12 Months allocation flag
FWRKP str1 %1s PUMS Worked last week flag
FYOEP str1 %1s PUMS Year of Entry allocation flag
pwgtp1 int %010.2g
pwgtp2 int %010.2g
pwgtp3 int %010.2g
pwgtp4 int %010.2g
pwgtp5 int %010.2g
pwgtp6 int %010.2g
pwgtp7 int %010.2g
pwgtp8 int %010.2g
pwgtp9 int %010.2g
pwgtp10 int %010.2g
pwgtp11 int %010.2g
pwgtp12 int %010.2g
pwgtp13 int %010.2g
pwgtp14 int %010.2g
pwgtp15 int %010.2g
pwgtp16 int %010.2g
pwgtp17 int %010.2g
pwgtp18 int %010.2g
pwgtp19 int %010.2g
pwgtp20 int %010.2g
pwgtp21 int %010.2g
pwgtp22 int %010.2g
pwgtp23 int %010.2g
pwgtp24 int %010.2g
pwgtp25 int %010.2g
pwgtp26 int %010.2g
pwgtp27 int %010.2g
pwgtp28 int %010.2g
pwgtp29 int %010.2g
pwgtp30 int %010.2g
pwgtp31 int %010.2g
pwgtp32 int %010.2g
pwgtp33 int %010.2g
pwgtp34 int %010.2g
pwgtp35 int %010.2g
pwgtp36 int %010.2g
pwgtp37 int %010.2g
pwgtp38 int %010.2g
pwgtp39 int %010.2g
pwgtp40 int %010.2g
pwgtp41 int %010.2g
pwgtp42 int %010.2g
pwgtp43 int %010.2g
pwgtp44 int %010.2g
pwgtp45 int %010.2g
pwgtp46 int %010.2g
pwgtp47 int %010.2g
pwgtp48 int %010.2g
pwgtp49 int %010.2g
pwgtp50 int %010.2g
pwgtp51 int %010.2g
pwgtp52 int %010.2g
pwgtp53 int %010.2g
pwgtp54 int %010.2g
pwgtp55 int %010.2g
pwgtp56 int %010.2g
pwgtp57 int %010.2g
pwgtp58 int %010.2g
pwgtp59 int %010.2g
pwgtp60 int %010.2g
pwgtp61 int %010.2g
pwgtp62 int %010.2g
pwgtp63 int %010.2g
pwgtp64 int %010.2g
pwgtp65 int %010.2g
pwgtp66 int %010.2g
pwgtp67 int %010.2g
pwgtp68 int %010.2g
pwgtp69 int %010.2g
pwgtp70 int %010.2g
pwgtp71 int %010.2g
pwgtp72 int %010.2g
pwgtp73 int %010.2g
pwgtp74 int %010.2g
pwgtp75 int %010.2g
pwgtp76 int %010.2g
pwgtp77 int %010.2g
pwgtp78 int %010.2g
pwgtp79 int %010.2g
pwgtp80 int %010.2g
-------------------------------------------------------------------------------------------------------------
Sorted by:
Note: Dataset has changed since last saved.
get data from pandas using sfi
. python:
----------------------------------------------- python (type end to exit) -----------------------------------
>>> import pandas as pd
>>> data = pd.read_html("https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html")
>>> df = data[4]
>>> df.head()
Unnamed: 0 ... Non-Hispanic White
0 Proportion of hospitalized COVID-NET cases1 ... 31.4%
1 Proportion of population in COVID-NET catchment ... 58.5%
2 Prevalence ratios2 ... 0.5
[3 rows x 6 columns]
>>> t = df.values.tolist()
>>> end
-------------------------------------------------------------------------------------------------------------
生成Stata dataset
clear
quietly python:
from sfi import Data
Data.addObs(len(t))
stata: gen desc = ""
stata: gen indian = ""
stata: gen balck = ""
stata: gen hisp = ""
stata: gen asian = ""
stata: gen white = ""
Data.store(None, range(len(t)), t)
end
. list, clean string(22)
desc indian balck hisp asian white
1. Proportion of hospital.. 1.3% 33.0% 23.1% 5.0% 31.4%
2. Proportion of populati.. 0.7% 17.9% 14.1% 8.9% 58.5%
3. Prevalence ratios2 1.9 1.8 1.6 0.6 0.5
Covid-19数据的获取与显示
Covid-19数据
. local date = "07-30-2020"
. import delimited "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_
> covid_19_daily_reports/`date'.csv", clear
(14 vars, 3,935 obs)
. save ./data/covid_`date'.dta, replace
file ./data/covid_07-30-2020.dta saved
. desc
Contains data from ./data/covid_07-30-2020.dta
obs: 3,935
vars: 14 22 Aug 2020 08:49
-------------------------------------------------------------------------------------------------------------
storage display value
variable name type format label variable label
-------------------------------------------------------------------------------------------------------------
fips long %12.0g FIPS
admin2 str41 %41s Admin2
province_state str40 %40s Province_State
country_region str32 %32s Country_Region
last_update str19 %19s Last_Update
lat float %9.0g Lat
long_ float %9.0g Long_
confirmed long %12.0g Confirmed
deaths long %12.0g Deaths
recovered long %12.0g Recovered
active long %12.0g Active
combined_key str55 %55s Combined_Key
incidence_rate float %9.0g Incidence_Rate
casefatality_~o float %9.0g Case-Fatality_Ratio
-------------------------------------------------------------------------------------------------------------
Sorted by:
获得与生成US county shape data
cd data
copy https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_county_500k.zip ///
cb_2018_us_county_500k.zip
unzipfile cb_2018_us_county_500k.zip
spshape2dta ./cb_2018_us_county_500k/cb_2018_us_county_500k.shp, ///
saving(usacounties) replace
use usacounties.dta, clear
generate fips = real(GEOID)
save usacounties.dta, replace
cd ..
. import delimited https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/counties/totals/co-est2
> 019-alldata.csv, clear
(164 vars, 3,193 obs)
.
. generate fips = state*1000 + county
. desc
Contains data
obs: 3,193
vars: 165
-------------------------------------------------------------------------------------------------------------
storage display value
variable name type format label variable label
-------------------------------------------------------------------------------------------------------------
sumlev byte %8.0g SUMLEV
region byte %8.0g REGION
division byte %8.0g DIVISION
state byte %8.0g STATE
county int %8.0g COUNTY
stname str20 %20s STNAME
ctyname str33 %33s CTYNAME
census2010pop long %12.0g CENSUS2010POP
estimatesb~2010 long %12.0g ESTIMATESBASE2010
popestimate2010 long %12.0g POPESTIMATE2010
popestimate2011 long %12.0g POPESTIMATE2011
popestimate2012 long %12.0g POPESTIMATE2012
popestimate2013 long %12.0g POPESTIMATE2013
popestimate2014 long %12.0g POPESTIMATE2014
popestimate2015 long %12.0g POPESTIMATE2015
popestimate2016 long %12.0g POPESTIMATE2016
popestimate2017 long %12.0g POPESTIMATE2017
popestimate2018 long %12.0g POPESTIMATE2018
popestimate2019 long %12.0g POPESTIMATE2019
npopchg_2010 long %12.0g NPOPCHG_2010
npopchg_2011 long %12.0g NPOPCHG_2011
npopchg_2012 long %12.0g NPOPCHG_2012
npopchg_2013 long %12.0g NPOPCHG_2013
npopchg_2014 long %12.0g NPOPCHG_2014
npopchg_2015 long %12.0g NPOPCHG_2015
npopchg_2016 long %12.0g NPOPCHG_2016
npopchg_2017 long %12.0g NPOPCHG_2017
npopchg_2018 long %12.0g NPOPCHG_2018
npopchg_2019 long %12.0g NPOPCHG_2019
births2010 long %12.0g BIRTHS2010
births2011 long %12.0g BIRTHS2011
births2012 long %12.0g BIRTHS2012
births2013 long %12.0g BIRTHS2013
births2014 long %12.0g BIRTHS2014
births2015 long %12.0g BIRTHS2015
births2016 long %12.0g BIRTHS2016
births2017 long %12.0g BIRTHS2017
births2018 long %12.0g BIRTHS2018
births2019 long %12.0g BIRTHS2019
deaths2010 long %12.0g DEATHS2010
deaths2011 long %12.0g DEATHS2011
deaths2012 long %12.0g DEATHS2012
deaths2013 long %12.0g DEATHS2013
deaths2014 long %12.0g DEATHS2014
deaths2015 long %12.0g DEATHS2015
deaths2016 long %12.0g DEATHS2016
deaths2017 long %12.0g DEATHS2017
deaths2018 long %12.0g DEATHS2018
deaths2019 long %12.0g DEATHS2019
naturalinc2010 long %12.0g NATURALINC2010
naturalinc2011 long %12.0g NATURALINC2011
naturalinc2012 long %12.0g NATURALINC2012
naturalinc2013 long %12.0g NATURALINC2013
naturalinc2014 long %12.0g NATURALINC2014
naturalinc2015 long %12.0g NATURALINC2015
naturalinc2016 long %12.0g NATURALINC2016
naturalinc2017 long %12.0g NATURALINC2017
naturalinc2018 long %12.0g NATURALINC2018
naturalinc2019 long %12.0g NATURALINC2019
internatio~2010 int %8.0g INTERNATIONALMIG2010
internatio~2011 long %12.0g INTERNATIONALMIG2011
internatio~2012 long %12.0g INTERNATIONALMIG2012
internatio~2013 long %12.0g INTERNATIONALMIG2013
internatio~2014 long %12.0g INTERNATIONALMIG2014
internatio~2015 long %12.0g INTERNATIONALMIG2015
internatio~2016 long %12.0g INTERNATIONALMIG2016
internatio~2017 long %12.0g INTERNATIONALMIG2017
internatio~2018 long %12.0g INTERNATIONALMIG2018
internatio~2019 long %12.0g INTERNATIONALMIG2019
domesticmig2010 int %8.0g DOMESTICMIG2010
domesticmig2011 long %12.0g DOMESTICMIG2011
domesticmig2012 long %12.0g DOMESTICMIG2012
domesticmig2013 long %12.0g DOMESTICMIG2013
domesticmig2014 long %12.0g DOMESTICMIG2014
domesticmig2015 long %12.0g DOMESTICMIG2015
domesticmig2016 long %12.0g DOMESTICMIG2016
domesticmig2017 long %12.0g DOMESTICMIG2017
domesticmig2018 long %12.0g DOMESTICMIG2018
domesticmig2019 long %12.0g DOMESTICMIG2019
netmig2010 long %12.0g NETMIG2010
netmig2011 long %12.0g NETMIG2011
netmig2012 long %12.0g NETMIG2012
netmig2013 long %12.0g NETMIG2013
netmig2014 long %12.0g NETMIG2014
netmig2015 long %12.0g NETMIG2015
netmig2016 long %12.0g NETMIG2016
netmig2017 long %12.0g NETMIG2017
netmig2018 long %12.0g NETMIG2018
netmig2019 long %12.0g NETMIG2019
residual2010 int %8.0g RESIDUAL2010
residual2011 int %8.0g RESIDUAL2011
residual2012 int %8.0g RESIDUAL2012
residual2013 int %8.0g RESIDUAL2013
residual2014 int %8.0g RESIDUAL2014
residual2015 int %8.0g RESIDUAL2015
residual2016 int %8.0g RESIDUAL2016
residual2017 int %8.0g RESIDUAL2017
residual2018 int %8.0g RESIDUAL2018
residual2019 int %8.0g RESIDUAL2019
gqestimatesba~0 long %12.0g GQESTIMATESBASE2010
gqestimates2010 long %12.0g GQESTIMATES2010
gqestimates2011 long %12.0g GQESTIMATES2011
gqestimates2012 long %12.0g GQESTIMATES2012
gqestimates2013 long %12.0g GQESTIMATES2013
gqestimates2014 long %12.0g GQESTIMATES2014
gqestimates2015 long %12.0g GQESTIMATES2015
gqestimates2016 long %12.0g GQESTIMATES2016
gqestimates2017 long %12.0g GQESTIMATES2017
gqestimates2018 long %12.0g GQESTIMATES2018
gqestimates2019 long %12.0g GQESTIMATES2019
rbirth2011 float %9.0g RBIRTH2011
rbirth2012 float %9.0g RBIRTH2012
rbirth2013 float %9.0g RBIRTH2013
rbirth2014 float %9.0g RBIRTH2014
rbirth2015 float %9.0g RBIRTH2015
rbirth2016 float %9.0g RBIRTH2016
rbirth2017 float %9.0g RBIRTH2017
rbirth2018 float %9.0g RBIRTH2018
rbirth2019 float %9.0g RBIRTH2019
rdeath2011 float %9.0g RDEATH2011
rdeath2012 float %9.0g RDEATH2012
rdeath2013 float %9.0g RDEATH2013
rdeath2014 float %9.0g RDEATH2014
rdeath2015 float %9.0g RDEATH2015
rdeath2016 float %9.0g RDEATH2016
rdeath2017 float %9.0g RDEATH2017
rdeath2018 float %9.0g RDEATH2018
rdeath2019 float %9.0g RDEATH2019
rnaturalinc2011 float %9.0g RNATURALINC2011
rnaturalinc2012 float %9.0g RNATURALINC2012
rnaturalinc2013 float %9.0g RNATURALINC2013
rnaturalinc2014 float %9.0g RNATURALINC2014
rnaturalinc2015 float %9.0g RNATURALINC2015
rnaturalinc2016 float %9.0g RNATURALINC2016
rnaturalinc2017 float %9.0g RNATURALINC2017
rnaturalinc2018 float %9.0g RNATURALINC2018
rnaturalinc2019 float %9.0g RNATURALINC2019
rinternati~2011 float %9.0g RINTERNATIONALMIG2011
rinternati~2012 float %9.0g RINTERNATIONALMIG2012
rinternati~2013 float %9.0g RINTERNATIONALMIG2013
rinternati~2014 float %9.0g RINTERNATIONALMIG2014
rinternati~2015 float %9.0g RINTERNATIONALMIG2015
rinternati~2016 float %9.0g RINTERNATIONALMIG2016
rinternati~2017 float %9.0g RINTERNATIONALMIG2017
rinternati~2018 float %9.0g RINTERNATIONALMIG2018
rinternati~2019 float %9.0g RINTERNATIONALMIG2019
rdomesticm~2011 float %9.0g RDOMESTICMIG2011
rdomesticm~2012 float %9.0g RDOMESTICMIG2012
rdomesticm~2013 float %9.0g RDOMESTICMIG2013
rdomesticm~2014 float %9.0g RDOMESTICMIG2014
rdomesticm~2015 float %9.0g RDOMESTICMIG2015
rdomesticm~2016 float %9.0g RDOMESTICMIG2016
rdomesticm~2017 float %9.0g RDOMESTICMIG2017
rdomesticm~2018 float %9.0g RDOMESTICMIG2018
rdomesticm~2019 float %9.0g RDOMESTICMIG2019
rnetmig2011 float %9.0g RNETMIG2011
rnetmig2012 float %9.0g RNETMIG2012
rnetmig2013 float %9.0g RNETMIG2013
rnetmig2014 float %9.0g RNETMIG2014
rnetmig2015 float %9.0g RNETMIG2015
rnetmig2016 float %9.0g RNETMIG2016
rnetmig2017 float %9.0g RNETMIG2017
rnetmig2018 float %9.0g RNETMIG2018
rnetmig2019 float %9.0g RNETMIG2019
fips float %9.0g
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Sorted by:
Note: Dataset has changed since last saved.
. * save ./data/census_popn.dta, replace
merge 数据
use ./data/covid_`date'.dta, clear
drop if fips >= .
merge 1:1 fips using data/usacounties.dta
keep if _merge == 3
drop _merge
merge 1:1 fips using data/census_popn
generate confirmed_adj = 100000*(confirmed/popestimate2019)
label var confirmed_adj "Cases per 100,000"
format %16.0fc confirmed_adj
