当变量在另一个文件中定义时将固定宽度的文件导入 R
Importing a fixed-width file into R when the variables are defined in another file
我正在尝试将此数据导入 R。
https://www.cdc.gov/healthyyouth/data/yrbs/data.htm
我知道我需要调查包，但这些文件很奇怪。
有人知道该怎么办吗？
虽然我不能完全回答你的问题，但我可以让你开始。您不确定该怎么做的原因是因为数据没有以您习惯的方式格式化。数据采用 ASCII 格式。以下是该网站的内容：
"Note: SAS and SPSS programs need to be used to convert ASCII into SAS and SPSS datasets. How to use the ASCII data varies from one software package to another. Column positions for each variable usually have to be specified. Column positions for each variable can be found in the documentation for each year’s data. Consult your software documentation for more information."
ASCII 只是一种不同的数据存储方式，例如 .csv 或其他格式，但它的可读性不如将所有内容都放在列中。您可以开始搜索如何将 ASCII 数据导入 R 并从那里开始。抱歉，我可以提供更多帮助。
要读取中的数据，您可以使用 read.fwf 基本方法。
如评论中所述，您可以从 SPSS 语法中获取索引：https://www.cdc.gov/healthyyouth/data/yrbs/sadc_2017/2017_sadc_spss_input_program.sps
我使用文本编辑器快速获取列宽：
vec <- c(5, 50, 50, 8, 8, 3, 10, 8, 8, 8, 3, 3, 3, 3, 3, 8, 8, 8, 8,
3, 3, 1, 1, 8, 8, 8, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3)
每个column/variable对应的名字：
names <- c("sitecode", "sitename", "sitetype", "sitetypenum", "year",
"survyear", "weight", "stratum", "PSU", "record", "age", "sex",
"grade", "race4", "race7", "stheight", "stweight", "bmi", "bmipct",
"qnobese", "qnowt", "q67", "q66", "sexid", "sexid2", "sexpart",
"sexpart2", "Q8", "Q9", "Q10", "Q11", "Q12", "Q13", "Q14", "Q15",
"Q16", "Q17", "Q18", "Q19", "Q20", "Q21", "Q22", "Q23", "Q24",
"Q25", "Q26", "Q27", "Q28", "Q29", "Q30", "Q31", "Q32", "Q33",
"Q34", "Q35", "Q36", "Q37", "Q38", "Q39", "Q40", "Q41", "Q42",
"Q43", "Q44", "Q45", "Q46", "Q47", "Q48", "Q49", "Q50", "Q51",
"Q52", "Q53", "Q54", "Q55", "Q56", "Q57", "Q58", "Q59", "Q60",
"Q61", "Q62", "Q63", "Q64", "Q65", "Q68", "Q69", "Q70", "Q71",
"Q72", "Q73", "Q74", "Q75", "Q76", "Q77", "Q78", "Q79", "Q80",
"Q81", "Q82", "Q83", "Q84", "Q85", "Q86", "Q87", "Q88", "Q89",
"QN8", "QN9", "QN10", "QN11", "QN12", "QN13", "QN14", "QN15",
"QN16", "QN17", "QN18", "QN19", "QN20", "QN21", "QN22", "QN23",
"QN24", "QN25", "QN26", "QN27", "QN28", "QN29", "QN30", "QN31",
"QN32", "QN33", "QN34", "QN35", "QN36", "QN37", "QN38", "QN39",
"QN40", "QN41", "QN42", "QN43", "QN44", "QN45", "QN46", "QN47",
"QN48", "QN49", "QN50", "QN51", "QN52", "QN53", "QN54", "QN55",
"QN56", "QN57", "QN58", "QN59", "QN60", "QN61", "QN62", "QN63",
"QN64", "QN65", "QN68", "QN69", "QN70", "QN71", "QN72", "QN73",
"QN74", "QN75", "QN76", "QN77", "QN78", "QN79", "QN80", "QN81",
"QN82", "QN83", "QN84", "QN85", "QN86", "QN87", "QN88", "QN89",
"qnfrcig", "qndaycig", "qnfrevp", "qndayevp", "qnfrskl", "qndayskl",
"qnfrcgr", "qndaycgr", "qntb2", "qntb3", "qntb4", "qniudimp",
"qnshparg", "qnothhpl", "qndualbc", "qnbcnone", "qnfr0", "qnfr1",
"qnfr2", "qnfr3", "qnveg0", "qnveg1", "qnveg2", "qnveg3", "qnsoda1",
"qnsoda2", "qnsoda3", "qnmilk1", "qnmilk2", "qnmilk3", "qnbk7day",
"qnpa0day", "qnpa7day", "qndlype", "qnnodnt", "qbikehelmet",
"qdrivemarijuana", "qcelldriving", "qpropertydamage", "qbullyweight",
"qbullygender", "qbullygay", "qchokeself", "qcigschool", "qchewtobschool",
"qalcoholschool", "qtypealcohol", "qhowmarijuana", "qmarijuanaschool",
"qcurrentcocaine", "qcurrentheroin", "qcurrentmeth", "qhallucdrug",
"qprescription30d", "qgenderexp", "qtaughtHIV", "qtaughtsexed",
"qtaughtstd", "qtaughtcondom", "qtaughtbc", "qdietpop", "qcoffeetea",
"qsportsdrink", "qenergydrink", "qsugardrink", "qwater", "qfastfood",
"qfoodallergy", "qwenthungry", "qmusclestrength", "qsunscreenuse",
"qindoortanning", "qsunburn", "qconcentrating", "qcurrentasthma",
"qwheresleep", "qspeakenglish", "qtransgender", "qnbikehelmet",
"qndrivemarijuana", "qncelldriving", "qnpropertydamage", "qnbullyweight",
"qnbullygender", "qnbullygay", "qnchokeself", "qncigschool",
"qnchewtobschool", "qnalcoholschool", "qntypealcohol", "qnhowmarijuana",
"qnmarijuanaschool", "qncurrentcocaine", "qncurrentheroin", "qncurrentmeth",
"qnhallucdrug", "qnprescription30d", "qngenderexp", "qntaughtHIV",
"qntaughtsexed", "qntaughtstd", "qntaughtcondom", "qntaughtbc",
"qndietpop", "qncoffeetea", "qnsportsdrink", "qnspdrk1", "qnspdrk2",
"qnspdrk3", "qnenergydrink", "qnsugardrink", "qnwater", "qnwater1",
"qnwater2", "qnwater3", "qnfastfood", "qnfoodallergy", "qnwenthungry",
"qnmusclestrength", "qnsunscreenuse", "qnindoortanning", "qnsunburn",
"qnconcentrating", "qncurrentasthma", "qnwheresleep", "qnspeakenglish",
"qntransgender")
正如之前的评论中提到的，我们可以使用 read.fwf 方法读取带有 *.dat 文件的固定文件（我只保存了一个子集......我预计这需要一段时间才能完成读取整个文件):
df <- read.fwf(file = "c:/temp/file", widths = vec)
# Rename columns
names(df) <- names
# Inspect the head.
head(df, n=2)
# sitecode sitename sitetype sitetypenum year survyear weight stratum PSU record age sex grade race4 race7
# 1 XX United States (XX) National 3 1991 1 0.2645 12210 5 29890 . . 1 3 4
# 2 XX United States (XX) National 3 1991 1 0.5060 12310 29 29891 . . . . .
# stheight stweight bmi bmipct qnobese qnowt q67 q66 sexid sexid2 sexpart sexpart2 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22 Q23 Q24 Q25 Q26 Q27 Q28 Q29 Q30 Q31 Q32 Q33
# 1 . . . . . . NA NA . . . . 2 4 NA NA 4 NA NA NA NA 3 NA NA NA NA NA NA NA NA 2 2 1 1 1 NA 2 4
# 2 . . . . . . NA NA . . . . NA NA NA NA NA NA NA NA NA 1 NA NA NA NA NA NA NA NA 1 1 1 1 1 NA 1 1
# Q34 Q35 Q36 Q37 Q38 Q39 Q40 Q41 Q42 Q43 Q44 Q45 Q46 Q47 Q48 Q49 Q50 Q51 Q52 Q53 Q54 Q55 Q56 Q57 Q58 Q59 Q60 Q61 Q62 Q63 Q64 Q65 Q68 Q69 Q70 Q71 Q72 Q73 Q74 Q75 Q76 Q77 Q78 Q79 Q80 Q81 Q82 Q83 Q84
# 1 NA NA NA NA NA NA 4 4 3 NA NA NA 5 5 5 1 NA NA NA NA NA 1 NA NA 1 1 5 4 4 3 3 8 1 NA NA NA NA NA NA NA NA NA NA NA NA NA 6 NA NA
# 2 NA NA NA NA NA NA 6 2 2 NA NA NA 1 1 1 1 NA NA NA NA NA 1 NA NA 1 1 2 2 2 3 3 2 3 NA NA NA NA NA NA NA NA NA NA NA NA NA 6 NA NA
# Q85 Q86 Q87 Q88 Q89 QN8 QN9 QN10 QN11 QN12 QN13 QN14 QN15 QN16 QN17 QN18 QN19 QN20 QN21 QN22 QN23 QN24 QN25 QN26 QN27 QN28 QN29 QN30 QN31 QN32 QN33 QN34 QN35 QN36 QN37 QN38 QN39 QN40 QN41 QN42
# 1 NA NA NA NA NA 1 1 . . 1 . . . . 1 . . . . . . . . 2 2 2 2 1 . 1 2 . . . . . . 1 1 1
# 2 NA NA NA NA NA . . . . . . . . . 2 . . . . . . . . 1 1 2 2 1 . 2 . . . . . . . 1 1 1
# QN43 QN44 QN45 QN46 QN47 QN48 QN49 QN50 QN51 QN52 QN53 QN54 QN55 QN56 QN57 QN58 QN59 QN60 QN61 QN62 QN63 QN64 QN65 QN68 QN69 QN70 QN71 QN72 QN73 QN74 QN75 QN76 QN77 QN78 QN79 QN80 QN81 QN82 QN83
# 1 . . . 1 2 1 2 . . . . . 2 . . 1 1 2 2 1 2 2 2 2 . . . . . . . . . . . . . 1 .
# 2 . . . 2 2 2 2 . . . . . 2 . . 1 1 1 2 2 . . . 2 . . . . . . . . . . . . . 1 .
# QN84 QN85 QN86 QN87 QN88 QN89 qnfrcig qndaycig qnfrevp qndayevp qnfrskl qndayskl qnfrcgr qndaycgr qntb2 qntb3 qntb4 qniudimp qnshparg qnothhpl qndualbc qnbcnone qnfr0 qnfr1 qnfr2 qnfr3 qnveg0
# 1 . . . . . . 2 2 . . . . . . . . . . . . . 2 . . . . .
# 2 . . . . . . 2 2 . . . . . . . . . . . . . . . . . . .
# qnveg1 qnveg2 qnveg3 qnsoda1 qnsoda2 qnsoda3 qnmilk1 qnmilk2 qnmilk3 qnbk7day qnpa0day qnpa7day qndlype qnnodnt qbikehelmet qdrivemarijuana qcelldriving qpropertydamage qbullyweight qbullygender
# 1 . . . . . . . . . . . . 1 . 2 NA NA NA NA NA
# 2 . . . . . . . . . . . . 1 . NA NA NA NA NA NA
# qbullygay qchokeself qcigschool qchewtobschool qalcoholschool qtypealcohol qhowmarijuana qmarijuanaschool qcurrentcocaine qcurrentheroin qcurrentmeth qhallucdrug qprescription30d qgenderexp
# 1 NA NA NA NA NA NA NA NA 1 NA NA NA NA NA
# 2 NA NA NA NA NA NA NA NA 1 NA NA NA NA NA
# qtaughtHIV qtaughtsexed qtaughtstd qtaughtcondom qtaughtbc qdietpop qcoffeetea qsportsdrink qenergydrink qsugardrink qwater qfastfood qfoodallergy qwenthungry qmusclestrength qsunscreenuse
# 1 2 NA NA NA NA NA NA NA NA NA NA NA NA NA 1 NA
# 2 1 NA NA NA NA NA NA NA NA NA NA NA NA NA 2 NA
# qindoortanning qsunburn qconcentrating qcurrentasthma qwheresleep qspeakenglish qtransgender qnbikehelmet qndrivemarijuana qncelldriving qnpropertydamage qnbullyweight qnbullygender qnbullygay
# 1 NA NA NA NA NA NA NA 1 . . . . . .
# 2 NA NA NA NA NA NA NA . . . . . . .
# qnchokeself qncigschool qnchewtobschool qnalcoholschool qntypealcohol qnhowmarijuana qnmarijuanaschool qncurrentcocaine qncurrentheroin qncurrentmeth qnhallucdrug qnprescription30d qngenderexp
# 1 . . . . . . . 2 . . . . .
# 2 . . . . . . . 2 . . . . .
# qntaughtHIV qntaughtsexed qntaughtstd qntaughtcondom qntaughtbc qndietpop qncoffeetea qnsportsdrink qnspdrk1 qnspdrk2 qnspdrk3 qnenergydrink qnsugardrink qnwater qnwater1 qnwater2 qnwater3
# 1 2 . . . . . . . . . . . . . . . .
# 2 1 . . . . . . . . . . . . . . . .
# qnfastfood qnfoodallergy qnwenthungry qnmusclestrength qnsunscreenuse qnindoortanning qnsunburn qnconcentrating qncurrentasthma qnwheresleep qnspeakenglish qntransgender
# 1 . . . 2 . . . . . . . .
# 2 . . . 2 . . . . . . . .
请注意，可能需要修剪任何字符列。缺少的也是“。”所以你可能也想删除它们。
我正在尝试将此数据导入 R。
https://www.cdc.gov/healthyyouth/data/yrbs/data.htm
我知道我需要调查包，但这些文件很奇怪。
有人知道该怎么办吗？
虽然我不能完全回答你的问题，但我可以让你开始。您不确定该怎么做的原因是因为数据没有以您习惯的方式格式化。数据采用 ASCII 格式。以下是该网站的内容：
"Note: SAS and SPSS programs need to be used to convert ASCII into SAS and SPSS datasets. How to use the ASCII data varies from one software package to another. Column positions for each variable usually have to be specified. Column positions for each variable can be found in the documentation for each year’s data. Consult your software documentation for more information."
ASCII 只是一种不同的数据存储方式，例如 .csv 或其他格式，但它的可读性不如将所有内容都放在列中。您可以开始搜索如何将 ASCII 数据导入 R 并从那里开始。抱歉，我可以提供更多帮助。
要读取中的数据，您可以使用 read.fwf 基本方法。
如评论中所述，您可以从 SPSS 语法中获取索引：https://www.cdc.gov/healthyyouth/data/yrbs/sadc_2017/2017_sadc_spss_input_program.sps
我使用文本编辑器快速获取列宽：
vec <- c(5, 50, 50, 8, 8, 3, 10, 8, 8, 8, 3, 3, 3, 3, 3, 8, 8, 8, 8,
3, 3, 1, 1, 8, 8, 8, 8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3)
每个column/variable对应的名字：
names <- c("sitecode", "sitename", "sitetype", "sitetypenum", "year",
"survyear", "weight", "stratum", "PSU", "record", "age", "sex",
"grade", "race4", "race7", "stheight", "stweight", "bmi", "bmipct",
"qnobese", "qnowt", "q67", "q66", "sexid", "sexid2", "sexpart",
"sexpart2", "Q8", "Q9", "Q10", "Q11", "Q12", "Q13", "Q14", "Q15",
"Q16", "Q17", "Q18", "Q19", "Q20", "Q21", "Q22", "Q23", "Q24",
"Q25", "Q26", "Q27", "Q28", "Q29", "Q30", "Q31", "Q32", "Q33",
"Q34", "Q35", "Q36", "Q37", "Q38", "Q39", "Q40", "Q41", "Q42",
"Q43", "Q44", "Q45", "Q46", "Q47", "Q48", "Q49", "Q50", "Q51",
"Q52", "Q53", "Q54", "Q55", "Q56", "Q57", "Q58", "Q59", "Q60",
"Q61", "Q62", "Q63", "Q64", "Q65", "Q68", "Q69", "Q70", "Q71",
"Q72", "Q73", "Q74", "Q75", "Q76", "Q77", "Q78", "Q79", "Q80",
"Q81", "Q82", "Q83", "Q84", "Q85", "Q86", "Q87", "Q88", "Q89",
"QN8", "QN9", "QN10", "QN11", "QN12", "QN13", "QN14", "QN15",
"QN16", "QN17", "QN18", "QN19", "QN20", "QN21", "QN22", "QN23",
"QN24", "QN25", "QN26", "QN27", "QN28", "QN29", "QN30", "QN31",
"QN32", "QN33", "QN34", "QN35", "QN36", "QN37", "QN38", "QN39",
"QN40", "QN41", "QN42", "QN43", "QN44", "QN45", "QN46", "QN47",
"QN48", "QN49", "QN50", "QN51", "QN52", "QN53", "QN54", "QN55",
"QN56", "QN57", "QN58", "QN59", "QN60", "QN61", "QN62", "QN63",
"QN64", "QN65", "QN68", "QN69", "QN70", "QN71", "QN72", "QN73",
"QN74", "QN75", "QN76", "QN77", "QN78", "QN79", "QN80", "QN81",
"QN82", "QN83", "QN84", "QN85", "QN86", "QN87", "QN88", "QN89",
"qnfrcig", "qndaycig", "qnfrevp", "qndayevp", "qnfrskl", "qndayskl",
"qnfrcgr", "qndaycgr", "qntb2", "qntb3", "qntb4", "qniudimp",
"qnshparg", "qnothhpl", "qndualbc", "qnbcnone", "qnfr0", "qnfr1",
"qnfr2", "qnfr3", "qnveg0", "qnveg1", "qnveg2", "qnveg3", "qnsoda1",
"qnsoda2", "qnsoda3", "qnmilk1", "qnmilk2", "qnmilk3", "qnbk7day",
"qnpa0day", "qnpa7day", "qndlype", "qnnodnt", "qbikehelmet",
"qdrivemarijuana", "qcelldriving", "qpropertydamage", "qbullyweight",
"qbullygender", "qbullygay", "qchokeself", "qcigschool", "qchewtobschool",
"qalcoholschool", "qtypealcohol", "qhowmarijuana", "qmarijuanaschool",
"qcurrentcocaine", "qcurrentheroin", "qcurrentmeth", "qhallucdrug",
"qprescription30d", "qgenderexp", "qtaughtHIV", "qtaughtsexed",
"qtaughtstd", "qtaughtcondom", "qtaughtbc", "qdietpop", "qcoffeetea",
"qsportsdrink", "qenergydrink", "qsugardrink", "qwater", "qfastfood",
"qfoodallergy", "qwenthungry", "qmusclestrength", "qsunscreenuse",
"qindoortanning", "qsunburn", "qconcentrating", "qcurrentasthma",
"qwheresleep", "qspeakenglish", "qtransgender", "qnbikehelmet",
"qndrivemarijuana", "qncelldriving", "qnpropertydamage", "qnbullyweight",
"qnbullygender", "qnbullygay", "qnchokeself", "qncigschool",
"qnchewtobschool", "qnalcoholschool", "qntypealcohol", "qnhowmarijuana",
"qnmarijuanaschool", "qncurrentcocaine", "qncurrentheroin", "qncurrentmeth",
"qnhallucdrug", "qnprescription30d", "qngenderexp", "qntaughtHIV",
"qntaughtsexed", "qntaughtstd", "qntaughtcondom", "qntaughtbc",
"qndietpop", "qncoffeetea", "qnsportsdrink", "qnspdrk1", "qnspdrk2",
"qnspdrk3", "qnenergydrink", "qnsugardrink", "qnwater", "qnwater1",
"qnwater2", "qnwater3", "qnfastfood", "qnfoodallergy", "qnwenthungry",
"qnmusclestrength", "qnsunscreenuse", "qnindoortanning", "qnsunburn",
"qnconcentrating", "qncurrentasthma", "qnwheresleep", "qnspeakenglish",
"qntransgender")
正如之前的评论中提到的，我们可以使用 read.fwf 方法读取带有 *.dat 文件的固定文件（我只保存了一个子集......我预计这需要一段时间才能完成读取整个文件):
df <- read.fwf(file = "c:/temp/file", widths = vec)
# Rename columns
names(df) <- names
# Inspect the head.
head(df, n=2)
# sitecode sitename sitetype sitetypenum year survyear weight stratum PSU record age sex grade race4 race7
# 1 XX United States (XX) National 3 1991 1 0.2645 12210 5 29890 . . 1 3 4
# 2 XX United States (XX) National 3 1991 1 0.5060 12310 29 29891 . . . . .
# stheight stweight bmi bmipct qnobese qnowt q67 q66 sexid sexid2 sexpart sexpart2 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22 Q23 Q24 Q25 Q26 Q27 Q28 Q29 Q30 Q31 Q32 Q33
# 1 . . . . . . NA NA . . . . 2 4 NA NA 4 NA NA NA NA 3 NA NA NA NA NA NA NA NA 2 2 1 1 1 NA 2 4
# 2 . . . . . . NA NA . . . . NA NA NA NA NA NA NA NA NA 1 NA NA NA NA NA NA NA NA 1 1 1 1 1 NA 1 1
# Q34 Q35 Q36 Q37 Q38 Q39 Q40 Q41 Q42 Q43 Q44 Q45 Q46 Q47 Q48 Q49 Q50 Q51 Q52 Q53 Q54 Q55 Q56 Q57 Q58 Q59 Q60 Q61 Q62 Q63 Q64 Q65 Q68 Q69 Q70 Q71 Q72 Q73 Q74 Q75 Q76 Q77 Q78 Q79 Q80 Q81 Q82 Q83 Q84
# 1 NA NA NA NA NA NA 4 4 3 NA NA NA 5 5 5 1 NA NA NA NA NA 1 NA NA 1 1 5 4 4 3 3 8 1 NA NA NA NA NA NA NA NA NA NA NA NA NA 6 NA NA
# 2 NA NA NA NA NA NA 6 2 2 NA NA NA 1 1 1 1 NA NA NA NA NA 1 NA NA 1 1 2 2 2 3 3 2 3 NA NA NA NA NA NA NA NA NA NA NA NA NA 6 NA NA
# Q85 Q86 Q87 Q88 Q89 QN8 QN9 QN10 QN11 QN12 QN13 QN14 QN15 QN16 QN17 QN18 QN19 QN20 QN21 QN22 QN23 QN24 QN25 QN26 QN27 QN28 QN29 QN30 QN31 QN32 QN33 QN34 QN35 QN36 QN37 QN38 QN39 QN40 QN41 QN42
# 1 NA NA NA NA NA 1 1 . . 1 . . . . 1 . . . . . . . . 2 2 2 2 1 . 1 2 . . . . . . 1 1 1
# 2 NA NA NA NA NA . . . . . . . . . 2 . . . . . . . . 1 1 2 2 1 . 2 . . . . . . . 1 1 1
# QN43 QN44 QN45 QN46 QN47 QN48 QN49 QN50 QN51 QN52 QN53 QN54 QN55 QN56 QN57 QN58 QN59 QN60 QN61 QN62 QN63 QN64 QN65 QN68 QN69 QN70 QN71 QN72 QN73 QN74 QN75 QN76 QN77 QN78 QN79 QN80 QN81 QN82 QN83
# 1 . . . 1 2 1 2 . . . . . 2 . . 1 1 2 2 1 2 2 2 2 . . . . . . . . . . . . . 1 .
# 2 . . . 2 2 2 2 . . . . . 2 . . 1 1 1 2 2 . . . 2 . . . . . . . . . . . . . 1 .
# QN84 QN85 QN86 QN87 QN88 QN89 qnfrcig qndaycig qnfrevp qndayevp qnfrskl qndayskl qnfrcgr qndaycgr qntb2 qntb3 qntb4 qniudimp qnshparg qnothhpl qndualbc qnbcnone qnfr0 qnfr1 qnfr2 qnfr3 qnveg0
# 1 . . . . . . 2 2 . . . . . . . . . . . . . 2 . . . . .
# 2 . . . . . . 2 2 . . . . . . . . . . . . . . . . . . .
# qnveg1 qnveg2 qnveg3 qnsoda1 qnsoda2 qnsoda3 qnmilk1 qnmilk2 qnmilk3 qnbk7day qnpa0day qnpa7day qndlype qnnodnt qbikehelmet qdrivemarijuana qcelldriving qpropertydamage qbullyweight qbullygender
# 1 . . . . . . . . . . . . 1 . 2 NA NA NA NA NA
# 2 . . . . . . . . . . . . 1 . NA NA NA NA NA NA
# qbullygay qchokeself qcigschool qchewtobschool qalcoholschool qtypealcohol qhowmarijuana qmarijuanaschool qcurrentcocaine qcurrentheroin qcurrentmeth qhallucdrug qprescription30d qgenderexp
# 1 NA NA NA NA NA NA NA NA 1 NA NA NA NA NA
# 2 NA NA NA NA NA NA NA NA 1 NA NA NA NA NA
# qtaughtHIV qtaughtsexed qtaughtstd qtaughtcondom qtaughtbc qdietpop qcoffeetea qsportsdrink qenergydrink qsugardrink qwater qfastfood qfoodallergy qwenthungry qmusclestrength qsunscreenuse
# 1 2 NA NA NA NA NA NA NA NA NA NA NA NA NA 1 NA
# 2 1 NA NA NA NA NA NA NA NA NA NA NA NA NA 2 NA
# qindoortanning qsunburn qconcentrating qcurrentasthma qwheresleep qspeakenglish qtransgender qnbikehelmet qndrivemarijuana qncelldriving qnpropertydamage qnbullyweight qnbullygender qnbullygay
# 1 NA NA NA NA NA NA NA 1 . . . . . .
# 2 NA NA NA NA NA NA NA . . . . . . .
# qnchokeself qncigschool qnchewtobschool qnalcoholschool qntypealcohol qnhowmarijuana qnmarijuanaschool qncurrentcocaine qncurrentheroin qncurrentmeth qnhallucdrug qnprescription30d qngenderexp
# 1 . . . . . . . 2 . . . . .
# 2 . . . . . . . 2 . . . . .
# qntaughtHIV qntaughtsexed qntaughtstd qntaughtcondom qntaughtbc qndietpop qncoffeetea qnsportsdrink qnspdrk1 qnspdrk2 qnspdrk3 qnenergydrink qnsugardrink qnwater qnwater1 qnwater2 qnwater3
# 1 2 . . . . . . . . . . . . . . . .
# 2 1 . . . . . . . . . . . . . . . .
# qnfastfood qnfoodallergy qnwenthungry qnmusclestrength qnsunscreenuse qnindoortanning qnsunburn qnconcentrating qncurrentasthma qnwheresleep qnspeakenglish qntransgender
# 1 . . . 2 . . . . . . . .
# 2 . . . 2 . . . . . . . .
请注意，可能需要修剪任何字符列。缺少的也是“。”所以你可能也想删除它们。