小标题：在 R 中组合两个 csv 文件时输出 0 x 0
A tibble: 0 x 0 output while combining two csv files in R
R Studio 4.0.2
套餐：
ggplot2 3.3.2 , purrr 0.3.4
tibble 3.0.4 dplyr 1.0.2
tidyr 1.1.2 stringr 1.4.0
阅读器 1.4.0 forcats 0.5.0
我正在尝试合并两个 CSV 文件并获得 A tibble 0 x 0 输出。其中一个文件有 2070 行和 21 列，另一个文件有 2014 行和 33 列。当我使用下面的代码时，无论功能如何，我都会得到这个输出：A tibble: 0 x 0 output
Schools_safety1517 应该是两个 CSV 文件（ss1516 和 ss1517）的组合。这些数据包含有关纽约市 public 学校发生的事件的犯罪数据维护信息。 ss1516 和 ss1617 在系统中有学校地址、学校名称和学校 ID 等信息。我正在尝试结合这两个 CSV 数据并使用下面的代码创建新的 CSV 数据。作为预期的输出，我期待一个新的 CSV 文件在这两个 CSV 文件中具有值（ss1516 CSV 文件中有 43.491 值，ss1617 CSV 文件中有 66.462 值。但是当我实现此代码时，我有此输出：A小标题：0 x 0 输出和 0 值。
我该如何解决这个问题并合并这两个 CSV 文件？
> school_safety1517 <- list.files(pattern = "ss1_.*csv")
> df_list <- lapply(school_safety1517,read_csv)
> df <- bind_rows(df_list)
> head(df)
# A tibble: 0 x 0
> df <- bind_cols(df_list)
> df
# A tibble: 0 x 0
> ss_1516 <- ss1516
> ss_1617 <- ss1617
> files <- list.files(pattern = "file_.csv")
> files <- list.files(pattern = "ss_1.*csv")
> df_list <- lapply(files,read_csv)
> df <- bind_rows(df_list)
> head(df)
# A tibble: 0 x 0
> df
# A tibble: 0 x 0
编辑：
以下是有关我正在处理的数据的摘要信息：
ss1516 的前 6 行：
# A tibble: 6 x 24
ID `Building Code` DBN `Location Name` `Location Code` Address Borough
<dbl> <chr> <chr> <chr> <chr> <chr> <chr>
1 1 K001 15K0~ P.S. 001 The B~ K001 309 47~ K
2 2 K002 17K0~ Parkside Prepa~ K002 655 PA~ K
3 3 K002 84K7~ EXPLORE CHARTE~ K704 655 PA~ K
4 4 K002 75K1~ P.S. K141 K141 655 PA~ K
5 5 K002 NA 655 PARKSIDE A~ NA 655 PA~ K
6 6 K003 13K0~ P.S. 003 The B~ K003 50 JEF~ K
# ... with 17 more variables: `Geographical District Code` <dbl>,
# Register <chr>, `Building Name` <chr>, `# Schools` <dbl>, `Schools in
# Building` <chr>, `Major N` <chr>, `Oth N` <chr>, `NoCrim N` <chr>, `Prop
# N` <chr>, `Vio N` <chr>, ENGroupA <chr>, RangeA <chr>, `AvgOfMajor
# N` <chr>, `AvgOfOth N` <chr>, `AvgOfNoCrim N` <chr>, `AvgOfProp N` <chr>,
# `AvgOfVio N` <chr>
ss1617 的前 6 行：
> head(ss1617)
School.Year Location.Name Location.Code Borough
1 2016 - 17 PASSAGES ACADEMY AT BELMONT(BN) X695 K
2 2016 - 17 P.S. Q086 Q086 Q
3 2016 - 17 P.S. 001 The Bergen K001 K
4 2016 - 17 P.S. 001 Alfred E. Smith M001 M
5 2016 - 17 P.S. 035 M035 M
6 2016 - 17 The Urban Assembly School for Collaborative Health K764 K
Geographical.District.Code Register Building.Name X..Schools
1 7 618 1
2 28 646 1
3 15 1334 1
4 2 533 1
5 2 833 1
6 19 215 999 JAMAICA AVENUE CONSOLIDATED LOCATION 5
NYPD.Site.Code NYPD.Site.Name
1 211 PS 077K
2 746 MS 074Q
3 198 PS 001K
4 1398 Sunset Park HS
5 663 JHS 056M
6 315 SAMUEL J. TILDEN HS
Schools.in.Building
1 Brooklyn College Academy
2 P.S. 082 Hammond
3 P.S. 001 The Bergen
4 P.S. Q256
5 James Weldon Johnson
6 Multicultural High School |Academy of Innovative Technology |Brooklyn Lab School |Cypress Hills Collegiate Preparatory School |The Urban Assembly School for Collaborative Health |999 JAMAICA AVENUE CONSOLIDATED LOCATION
Major.N Oth.N NoCrim.N Prop.N Vio.N ENGroupA RangeA AvgOfMajor.N AvgOfOth.N AvgOfNoCrim.N
1 0 0 1 0 0 4C 501-750 0.28 1.11 1.74
2 0 1 0 1 0 4C 501-750 0.28 1.11 1.74
3 0 0 1 0 0 7C 1251-1500 0.64 3.02 5.77
4 0 1 0 0 1 4C 501-750 0.28 1.11 1.74
5 0 1 3 0 1 5C 751-1000 0.38 1.71 2.38
6 N/A N/A N/A N/A N/A 2C 1-250 N/A N/A N/A
AvgOfProp.N AvgOfVio.N Geocode Postcode Latitude
1 0.75 0.53 560 BROOK AVENUE\n(40.815701, -73.914526) NA NA
2 0.75 0.53 87 41 PARSONS BOULEVARD\n(41.12133, -72.339742) 11432 40.70890
3 1.72 1.54 309 47 STREET\n(41.574857, -93.767342) NA NA
4 0.75 0.53 8 HENRY STREET\n(41.398617, -73.465855) NA NA
5 0.98 0.82 317 WEST 52ND STREET\n(41.799996, -87.633867) 10019 40.76387
6 N/A N/A 999 JAMAICA AVENUE\n(27.783609, -80.501816) 11208 40.69115
Longitude Community.Board Council.District Census.Tract BIN BBL
1 NA NA NA NA NA NA
2 -73.80394 8 24 448 4438678 4097740001
3 NA NA NA NA NA NA
4 NA NA NA NA NA NA
5 -73.98594 4 3 133 1025241 1010430022
6 -73.86833 5 37 1180 3090738 3040940001
NTA
1
2 Briarwood-Jamaica Hills
3
4
5 Clinton
6 park-cemetery-etc-Brooklyn
ss1516 总结：
> summary(ss1516)
ID Building Code DBN Location Name
Min. : 1 Length:2070 Length:2070 Length:2070
1st Qu.: 518 Class :character Class :character Class :character
Median :1035 Mode :character Mode :character Mode :character
Mean :1035
3rd Qu.:1552
Max. :2069
NA's :1
Location Code Address Borough
Length:2070 Length:2070 Length:2070
Class :character Class :character Class :character
Mode :character Mode :character Mode :character
Geographical District Code Register Building Name
Min. : 0.00 Length:2070 Length:2070
1st Qu.: 8.00 Class :character Class :character
Median :14.00 Mode :character Mode :character
Mean :15.37
3rd Qu.:23.00
Max. :32.00
NA's :4
# Schools Schools in Building Major N Oth N
Min. :1.000 Length:2070 Length:2070 Length:2070
1st Qu.:1.000 Class :character Class :character Class :character
Median :2.000 Mode :character Mode :character Mode :character
Mean :2.211
3rd Qu.:3.000
Max. :8.000
NA's :1
NoCrim N Prop N Vio N ENGroupA
Length:2070 Length:2070 Length:2070 Length:2070
Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character
RangeA AvgOfMajor N AvgOfOth N AvgOfNoCrim N
Length:2070 Length:2070 Length:2070 Length:2070
Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character
AvgOfProp N AvgOfVio N
Length:2070 Length:2070
Class :character Class :character
Mode :character Mode :character
ss1617 总结：
> summary(ss1617)
School.Year Location.Name Location.Code Borough
Length:2046 Length:2046 Length:2046 Length:2046
Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character
Geographical.District.Code Register Building.Name X..Schools NYPD.Site.Code
Min. : 0.00 Length:2046 Length:2046 Min. :1.00 Length:2046
1st Qu.: 8.00 Class :character Class :character 1st Qu.:1.00 Class :character
Median :14.00 Mode :character Mode :character Median :2.00 Mode :character
Mean :15.46 Mean :2.13
3rd Qu.:24.00 3rd Qu.:3.00
Max. :32.00 Max. :8.00
NYPD.Site.Name Schools.in.Building Major.N Oth.N NoCrim.N
Length:2046 Length:2046 Length:2046 Length:2046 Length:2046
Class :character Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character Mode :character
Prop.N Vio.N ENGroupA RangeA AvgOfMajor.N
Length:2046 Length:2046 Length:2046 Length:2046 Length:2046
Class :character Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character Mode :character
AvgOfOth.N AvgOfNoCrim.N AvgOfProp.N AvgOfVio.N Geocode
Length:2046 Length:2046 Length:2046 Length:2046 Length:2046
Class :character Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character Mode :character
Postcode Latitude Longitude Community.Board Council.District
Min. :10001 Min. :40.51 Min. :-74.24 Min. : 1.000 Min. : 1.00
1st Qu.:10451 1st Qu.:40.67 1st Qu.:-73.96 1st Qu.: 3.000 1st Qu.:12.00
Median :11102 Median :40.73 Median :-73.92 Median : 7.000 Median :23.00
Mean :10788 Mean :40.74 Mean :-73.92 Mean : 7.306 Mean :24.31
3rd Qu.:11226 3rd Qu.:40.82 3rd Qu.:-73.88 3rd Qu.:11.000 3rd Qu.:37.00
Max. :11694 Max. :40.90 Max. :-73.71 Max. :18.000 Max. :51.00
NA's :26 NA's :26 NA's :26 NA's :26 NA's :26
Census.Tract BIN BBL NTA
Min. : 1.0 Min. :1000003 Min. :1.000e+09 Length:2046
1st Qu.: 155.0 1st Qu.:2005348 1st Qu.:2.027e+09 Class :character
Median : 312.5 Median :3042210 Median :3.014e+09 Mode :character
Mean : 7065.4 Mean :2743071 Mean :2.674e+09
3rd Qu.: 896.0 3rd Qu.:3394175 3rd Qu.:3.082e+09
Max. :157903.0 Max. :5158758 Max. :5.079e+09
NA's :26 NA's :30 NA's :30
导入数据集的链接：
ss1516：https://data.cityofnewyork.us/api/views/44t3-dj6x/rows.csv?accessType=DOWNLOAD
ss1617: https://data.cityofnewyork.us/api/views/rear-wh5i/rows.csv?accessType=DOWNLOAD
我的数据框的最后一个版本是 df ，而不是 school_safety1517 这就是为什么试图找到 schoolsafety1517 的输出是没有意义的。
R Studio 4.0.2
套餐：
ggplot2 3.3.2 , purrr 0.3.4
tibble 3.0.4 dplyr 1.0.2
tidyr 1.1.2 stringr 1.4.0
阅读器 1.4.0 forcats 0.5.0
我正在尝试合并两个 CSV 文件并获得 A tibble 0 x 0 输出。其中一个文件有 2070 行和 21 列，另一个文件有 2014 行和 33 列。当我使用下面的代码时，无论功能如何，我都会得到这个输出：A tibble: 0 x 0 output
Schools_safety1517 应该是两个 CSV 文件（ss1516 和 ss1517）的组合。这些数据包含有关纽约市 public 学校发生的事件的犯罪数据维护信息。 ss1516 和 ss1617 在系统中有学校地址、学校名称和学校 ID 等信息。我正在尝试结合这两个 CSV 数据并使用下面的代码创建新的 CSV 数据。作为预期的输出，我期待一个新的 CSV 文件在这两个 CSV 文件中具有值（ss1516 CSV 文件中有 43.491 值，ss1617 CSV 文件中有 66.462 值。但是当我实现此代码时，我有此输出：A小标题：0 x 0 输出和 0 值。
我该如何解决这个问题并合并这两个 CSV 文件？
> school_safety1517 <- list.files(pattern = "ss1_.*csv")
> df_list <- lapply(school_safety1517,read_csv)
> df <- bind_rows(df_list)
> head(df)
# A tibble: 0 x 0
> df <- bind_cols(df_list)
> df
# A tibble: 0 x 0
> ss_1516 <- ss1516
> ss_1617 <- ss1617
> files <- list.files(pattern = "file_.csv")
> files <- list.files(pattern = "ss_1.*csv")
> df_list <- lapply(files,read_csv)
> df <- bind_rows(df_list)
> head(df)
# A tibble: 0 x 0
> df
# A tibble: 0 x 0
编辑： 以下是有关我正在处理的数据的摘要信息： ss1516 的前 6 行：
# A tibble: 6 x 24
ID `Building Code` DBN `Location Name` `Location Code` Address Borough
<dbl> <chr> <chr> <chr> <chr> <chr> <chr>
1 1 K001 15K0~ P.S. 001 The B~ K001 309 47~ K
2 2 K002 17K0~ Parkside Prepa~ K002 655 PA~ K
3 3 K002 84K7~ EXPLORE CHARTE~ K704 655 PA~ K
4 4 K002 75K1~ P.S. K141 K141 655 PA~ K
5 5 K002 NA 655 PARKSIDE A~ NA 655 PA~ K
6 6 K003 13K0~ P.S. 003 The B~ K003 50 JEF~ K
# ... with 17 more variables: `Geographical District Code` <dbl>,
# Register <chr>, `Building Name` <chr>, `# Schools` <dbl>, `Schools in
# Building` <chr>, `Major N` <chr>, `Oth N` <chr>, `NoCrim N` <chr>, `Prop
# N` <chr>, `Vio N` <chr>, ENGroupA <chr>, RangeA <chr>, `AvgOfMajor
# N` <chr>, `AvgOfOth N` <chr>, `AvgOfNoCrim N` <chr>, `AvgOfProp N` <chr>,
# `AvgOfVio N` <chr>
ss1617 的前 6 行：
> head(ss1617)
School.Year Location.Name Location.Code Borough
1 2016 - 17 PASSAGES ACADEMY AT BELMONT(BN) X695 K
2 2016 - 17 P.S. Q086 Q086 Q
3 2016 - 17 P.S. 001 The Bergen K001 K
4 2016 - 17 P.S. 001 Alfred E. Smith M001 M
5 2016 - 17 P.S. 035 M035 M
6 2016 - 17 The Urban Assembly School for Collaborative Health K764 K
Geographical.District.Code Register Building.Name X..Schools
1 7 618 1
2 28 646 1
3 15 1334 1
4 2 533 1
5 2 833 1
6 19 215 999 JAMAICA AVENUE CONSOLIDATED LOCATION 5
NYPD.Site.Code NYPD.Site.Name
1 211 PS 077K
2 746 MS 074Q
3 198 PS 001K
4 1398 Sunset Park HS
5 663 JHS 056M
6 315 SAMUEL J. TILDEN HS
Schools.in.Building
1 Brooklyn College Academy
2 P.S. 082 Hammond
3 P.S. 001 The Bergen
4 P.S. Q256
5 James Weldon Johnson
6 Multicultural High School |Academy of Innovative Technology |Brooklyn Lab School |Cypress Hills Collegiate Preparatory School |The Urban Assembly School for Collaborative Health |999 JAMAICA AVENUE CONSOLIDATED LOCATION
Major.N Oth.N NoCrim.N Prop.N Vio.N ENGroupA RangeA AvgOfMajor.N AvgOfOth.N AvgOfNoCrim.N
1 0 0 1 0 0 4C 501-750 0.28 1.11 1.74
2 0 1 0 1 0 4C 501-750 0.28 1.11 1.74
3 0 0 1 0 0 7C 1251-1500 0.64 3.02 5.77
4 0 1 0 0 1 4C 501-750 0.28 1.11 1.74
5 0 1 3 0 1 5C 751-1000 0.38 1.71 2.38
6 N/A N/A N/A N/A N/A 2C 1-250 N/A N/A N/A
AvgOfProp.N AvgOfVio.N Geocode Postcode Latitude
1 0.75 0.53 560 BROOK AVENUE\n(40.815701, -73.914526) NA NA
2 0.75 0.53 87 41 PARSONS BOULEVARD\n(41.12133, -72.339742) 11432 40.70890
3 1.72 1.54 309 47 STREET\n(41.574857, -93.767342) NA NA
4 0.75 0.53 8 HENRY STREET\n(41.398617, -73.465855) NA NA
5 0.98 0.82 317 WEST 52ND STREET\n(41.799996, -87.633867) 10019 40.76387
6 N/A N/A 999 JAMAICA AVENUE\n(27.783609, -80.501816) 11208 40.69115
Longitude Community.Board Council.District Census.Tract BIN BBL
1 NA NA NA NA NA NA
2 -73.80394 8 24 448 4438678 4097740001
3 NA NA NA NA NA NA
4 NA NA NA NA NA NA
5 -73.98594 4 3 133 1025241 1010430022
6 -73.86833 5 37 1180 3090738 3040940001
NTA
1
2 Briarwood-Jamaica Hills
3
4
5 Clinton
6 park-cemetery-etc-Brooklyn
ss1516 总结：
> summary(ss1516)
ID Building Code DBN Location Name
Min. : 1 Length:2070 Length:2070 Length:2070
1st Qu.: 518 Class :character Class :character Class :character
Median :1035 Mode :character Mode :character Mode :character
Mean :1035
3rd Qu.:1552
Max. :2069
NA's :1
Location Code Address Borough
Length:2070 Length:2070 Length:2070
Class :character Class :character Class :character
Mode :character Mode :character Mode :character
Geographical District Code Register Building Name
Min. : 0.00 Length:2070 Length:2070
1st Qu.: 8.00 Class :character Class :character
Median :14.00 Mode :character Mode :character
Mean :15.37
3rd Qu.:23.00
Max. :32.00
NA's :4
# Schools Schools in Building Major N Oth N
Min. :1.000 Length:2070 Length:2070 Length:2070
1st Qu.:1.000 Class :character Class :character Class :character
Median :2.000 Mode :character Mode :character Mode :character
Mean :2.211
3rd Qu.:3.000
Max. :8.000
NA's :1
NoCrim N Prop N Vio N ENGroupA
Length:2070 Length:2070 Length:2070 Length:2070
Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character
RangeA AvgOfMajor N AvgOfOth N AvgOfNoCrim N
Length:2070 Length:2070 Length:2070 Length:2070
Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character
AvgOfProp N AvgOfVio N
Length:2070 Length:2070
Class :character Class :character
Mode :character Mode :character
ss1617 总结：
> summary(ss1617)
School.Year Location.Name Location.Code Borough
Length:2046 Length:2046 Length:2046 Length:2046
Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character
Geographical.District.Code Register Building.Name X..Schools NYPD.Site.Code
Min. : 0.00 Length:2046 Length:2046 Min. :1.00 Length:2046
1st Qu.: 8.00 Class :character Class :character 1st Qu.:1.00 Class :character
Median :14.00 Mode :character Mode :character Median :2.00 Mode :character
Mean :15.46 Mean :2.13
3rd Qu.:24.00 3rd Qu.:3.00
Max. :32.00 Max. :8.00
NYPD.Site.Name Schools.in.Building Major.N Oth.N NoCrim.N
Length:2046 Length:2046 Length:2046 Length:2046 Length:2046
Class :character Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character Mode :character
Prop.N Vio.N ENGroupA RangeA AvgOfMajor.N
Length:2046 Length:2046 Length:2046 Length:2046 Length:2046
Class :character Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character Mode :character
AvgOfOth.N AvgOfNoCrim.N AvgOfProp.N AvgOfVio.N Geocode
Length:2046 Length:2046 Length:2046 Length:2046 Length:2046
Class :character Class :character Class :character Class :character Class :character
Mode :character Mode :character Mode :character Mode :character Mode :character
Postcode Latitude Longitude Community.Board Council.District
Min. :10001 Min. :40.51 Min. :-74.24 Min. : 1.000 Min. : 1.00
1st Qu.:10451 1st Qu.:40.67 1st Qu.:-73.96 1st Qu.: 3.000 1st Qu.:12.00
Median :11102 Median :40.73 Median :-73.92 Median : 7.000 Median :23.00
Mean :10788 Mean :40.74 Mean :-73.92 Mean : 7.306 Mean :24.31
3rd Qu.:11226 3rd Qu.:40.82 3rd Qu.:-73.88 3rd Qu.:11.000 3rd Qu.:37.00
Max. :11694 Max. :40.90 Max. :-73.71 Max. :18.000 Max. :51.00
NA's :26 NA's :26 NA's :26 NA's :26 NA's :26
Census.Tract BIN BBL NTA
Min. : 1.0 Min. :1000003 Min. :1.000e+09 Length:2046
1st Qu.: 155.0 1st Qu.:2005348 1st Qu.:2.027e+09 Class :character
Median : 312.5 Median :3042210 Median :3.014e+09 Mode :character
Mean : 7065.4 Mean :2743071 Mean :2.674e+09
3rd Qu.: 896.0 3rd Qu.:3394175 3rd Qu.:3.082e+09
Max. :157903.0 Max. :5158758 Max. :5.079e+09
NA's :26 NA's :30 NA's :30
导入数据集的链接： ss1516：https://data.cityofnewyork.us/api/views/44t3-dj6x/rows.csv?accessType=DOWNLOAD ss1617: https://data.cityofnewyork.us/api/views/rear-wh5i/rows.csv?accessType=DOWNLOAD
我的数据框的最后一个版本是 df ，而不是 school_safety1517 这就是为什么试图找到 schoolsafety1517 的输出是没有意义的。