rowsums错误：＆＃x27; x＆＃x27;当列的列是数字时，必须是数字

发布于 2025-02-06 09:25:59 字数 1130 浏览 2 评论 0原文

我正在尝试计算数据框中四列的行总和。数据框是从ESRI ArcGIS服务器导入的，当我查看要总结的列的结构时，它们都定义为数字，但我仍然会收到错误'x'必须是数字。

library(sf)
library(dplyr)

STTH <- st_read("https://services.arcgis.com/xxxx/ArcGIS/rest/services/service_xxxx/FeatureServer/")
STTH$projectsum <- rowSums(STTH [,19:22], na.rm = TRUE)

我的数据帧看起来像这样的列19:22

base_st_funding	base_stlandowner_funding	base__section6	base_partners
1200	NA	2100	800
1200	200	3200	NA
1200 NA 1200	NA	NA	210
1200	350	NA NA NA NA	NA NA

，当我致电STR（Stth）时，我可以为列19:22

$ base_st_st_funding： int 2950 NA NA NA 4905 NA 100 NA NA NA ...

$ base_stlandowner_funding : int 3300 NA NA NA 20981 NA NA NA NA NA ...

$ base_section6 : int NA NA NA NA 40364 NA NA NA NA NA ...

$ base_partners ：int na na na na 25000 na na na na na ...

原文

I'm trying to calculate the row sum for four columns in a dataframe. The dataframe was imported from an ESRI ArcGIS server and when I look at the structure of the columns I want to sum they all are defined as numeric but I still get the error 'x' must be numeric.

library(sf)
library(dplyr)

STTH <- st_read("https://services.arcgis.com/xxxx/ArcGIS/rest/services/service_xxxx/FeatureServer/")
STTH$projectsum <- rowSums(STTH [,19:22], na.rm = TRUE)

My dataframe looks like this for the columns 19:22

base_ST_funding	base_stlandowner_funding	base__section6	base_partners
1200	NA	2100	800
1200	200	3200	NA
1200	NA	NA	210
1200	350	NA	NA

And when I call str(STTH) I get this for columns 19:22

$ base_ST_funding : int 2950 NA NA NA 4905 NA 100 NA NA NA ...

$ base_stlandowner_funding : int 3300 NA NA NA 20981 NA NA NA NA NA ...

$ base_section6 : int NA NA NA NA 40364 NA NA NA NA NA ...

$ base_partners : int NA NA NA NA 25000 NA NA NA NA NA ...

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擦肩而过的背影 2025-02-13 09:25:59

这是因为对象是sf以及data.frame。当我们选择列时，几何列将自动选择。我们可以转换为data.frame，选择列并获取rowsums

STTH$projectsum <- rowSums(as.data.frame(STTH)[, 19:22], na.rm = TRUE)

- 可复制示例

> library(sf)
> nc <- st_read(system.file("shape/nc.shp", package="sf"))
> str(nc)
Classes ‘sf’ and 'data.frame':  100 obs. of  15 variables:
 $ AREA     : num  0.114 0.061 0.143 0.07 0.153 0.097 0.062 0.091 0.118 0.124 ...
 $ PERIMETER: num  1.44 1.23 1.63 2.97 2.21 ...
 $ CNTY_    : num  1825 1827 1828 1831 1832 ...
 $ CNTY_ID  : num  1825 1827 1828 1831 1832 ...
 $ NAME     : chr  "Ashe" "Alleghany" "Surry" "Currituck" ...
 $ FIPS     : chr  "37009" "37005" "37171" "37053" ...
 $ FIPSNO   : num  37009 37005 37171 37053 37131 ...
 $ CRESS_ID : int  5 3 86 27 66 46 15 37 93 85 ...
 $ BIR74    : num  1091 487 3188 508 1421 ...
 $ SID74    : num  1 0 5 1 9 7 0 0 4 1 ...
 $ NWBIR74  : num  10 10 208 123 1066 ...
 $ BIR79    : num  1364 542 3616 830 1606 ...
 $ SID79    : num  0 3 6 2 3 5 2 2 2 5 ...
 $ NWBIR79  : num  19 12 260 145 1197 ...
 $ geometry :sfc_MULTIPOLYGON of length 100; first list element: List of 1
  ..$ :List of 1
  .. ..$ : num [1:27, 1:2] -81.5 -81.5 -81.6 -81.6 -81.7 ...
  ..- attr(*, "class")= chr [1:3] "XY" "MULTIPOLYGON" "sfg"
 - attr(*, "sf_column")= chr "geometry"
 - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
  ..- attr(*, "names")= chr [1:14] "AREA" "PERIMETER" "CNTY_" "CNTY_ID" ...
> nc[, 1:4]
Simple feature collection with 100 features and 4 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
Geodetic CRS:  NAD27
First 10 features:
    AREA PERIMETER CNTY_ CNTY_ID                       geometry
1  0.114     1.442  1825    1825 MULTIPOLYGON (((-81.47276 3...
2  0.061     1.231  1827    1827 MULTIPOLYGON (((-81.23989 3...
3  0.143     1.630  1828    1828 MULTIPOLYGON (((-80.45634 3...
4  0.070     2.968  1831    1831 MULTIPOLYGON (((-76.00897 3...
5  0.153     2.206  1832    1832 MULTIPOLYGON (((-77.21767 3...
6  0.097     1.670  1833    1833 MULTIPOLYGON (((-76.74506 3...
7  0.062     1.547  1834    1834 MULTIPOLYGON (((-76.00897 3...
8  0.091     1.284  1835    1835 MULTIPOLYGON (((-76.56251 3...
9  0.118     1.421  1836    1836 MULTIPOLYGON (((-78.30876 3...
10 0.124     1.428  1837    1837 MULTIPOLYGON (((-80.02567 3...
> rowSums(nc[, 1:4], na.rm = TRUE)
Error in rowSums(nc[, 1:4], na.rm = TRUE) : 'x' must be numeric

> nc$newCol <- rowSums(as.data.frame(nc)[, 1:4], na.rm = TRUE)
> nc
Simple feature collection with 100 features and 15 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
Geodetic CRS:  NAD27
First 10 features:
    AREA PERIMETER CNTY_ CNTY_ID        NAME  FIPS FIPSNO CRESS_ID BIR74 SID74 NWBIR74 BIR79 SID79 NWBIR79
1  0.114     1.442  1825    1825        Ashe 37009  37009        5  1091     1      10  1364     0      19
2  0.061     1.231  1827    1827   Alleghany 37005  37005        3   487     0      10   542     3      12
3  0.143     1.630  1828    1828       Surry 37171  37171       86  3188     5     208  3616     6     260
4  0.070     2.968  1831    1831   Currituck 37053  37053       27   508     1     123   830     2     145
5  0.153     2.206  1832    1832 Northampton 37131  37131       66  1421     9    1066  1606     3    1197
6  0.097     1.670  1833    1833    Hertford 37091  37091       46  1452     7     954  1838     5    1237
7  0.062     1.547  1834    1834      Camden 37029  37029       15   286     0     115   350     2     139
8  0.091     1.284  1835    1835       Gates 37073  37073       37   420     0     254   594     2     371
9  0.118     1.421  1836    1836      Warren 37185  37185       93   968     4     748  1190     2     844
10 0.124     1.428  1837    1837      Stokes 37169  37169       85  1612     1     160  2038     5     176
                         geometry   newCol
1  MULTIPOLYGON (((-81.47276 3... 3651.556
2  MULTIPOLYGON (((-81.23989 3... 3655.292
3  MULTIPOLYGON (((-80.45634 3... 3657.773
4  MULTIPOLYGON (((-76.00897 3... 3665.038
5  MULTIPOLYGON (((-77.21767 3... 3666.359
6  MULTIPOLYGON (((-76.74506 3... 3667.767
7  MULTIPOLYGON (((-76.00897 3... 3669.609
8  MULTIPOLYGON (((-76.56251 3... 3671.375
9  MULTIPOLYGON (((-78.30876 3... 3673.539
10 MULTIPOLYGON (((-80.02567 3... 3675.552

It is because the object is a sf as well as data.frame. When we select the columns, the geometry columns are automatically selected. We could convert to data.frame, select the columns and get the rowSums

STTH$projectsum <- rowSums(as.data.frame(STTH)[, 19:22], na.rm = TRUE)

-reproducible example

> library(sf)
> nc <- st_read(system.file("shape/nc.shp", package="sf"))
> str(nc)
Classes ‘sf’ and 'data.frame':  100 obs. of  15 variables:
 $ AREA     : num  0.114 0.061 0.143 0.07 0.153 0.097 0.062 0.091 0.118 0.124 ...
 $ PERIMETER: num  1.44 1.23 1.63 2.97 2.21 ...
 $ CNTY_    : num  1825 1827 1828 1831 1832 ...
 $ CNTY_ID  : num  1825 1827 1828 1831 1832 ...
 $ NAME     : chr  "Ashe" "Alleghany" "Surry" "Currituck" ...
 $ FIPS     : chr  "37009" "37005" "37171" "37053" ...
 $ FIPSNO   : num  37009 37005 37171 37053 37131 ...
 $ CRESS_ID : int  5 3 86 27 66 46 15 37 93 85 ...
 $ BIR74    : num  1091 487 3188 508 1421 ...
 $ SID74    : num  1 0 5 1 9 7 0 0 4 1 ...
 $ NWBIR74  : num  10 10 208 123 1066 ...
 $ BIR79    : num  1364 542 3616 830 1606 ...
 $ SID79    : num  0 3 6 2 3 5 2 2 2 5 ...
 $ NWBIR79  : num  19 12 260 145 1197 ...
 $ geometry :sfc_MULTIPOLYGON of length 100; first list element: List of 1
  ..$ :List of 1
  .. ..$ : num [1:27, 1:2] -81.5 -81.5 -81.6 -81.6 -81.7 ...
  ..- attr(*, "class")= chr [1:3] "XY" "MULTIPOLYGON" "sfg"
 - attr(*, "sf_column")= chr "geometry"
 - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
  ..- attr(*, "names")= chr [1:14] "AREA" "PERIMETER" "CNTY_" "CNTY_ID" ...
> nc[, 1:4]
Simple feature collection with 100 features and 4 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
Geodetic CRS:  NAD27
First 10 features:
    AREA PERIMETER CNTY_ CNTY_ID                       geometry
1  0.114     1.442  1825    1825 MULTIPOLYGON (((-81.47276 3...
2  0.061     1.231  1827    1827 MULTIPOLYGON (((-81.23989 3...
3  0.143     1.630  1828    1828 MULTIPOLYGON (((-80.45634 3...
4  0.070     2.968  1831    1831 MULTIPOLYGON (((-76.00897 3...
5  0.153     2.206  1832    1832 MULTIPOLYGON (((-77.21767 3...
6  0.097     1.670  1833    1833 MULTIPOLYGON (((-76.74506 3...
7  0.062     1.547  1834    1834 MULTIPOLYGON (((-76.00897 3...
8  0.091     1.284  1835    1835 MULTIPOLYGON (((-76.56251 3...
9  0.118     1.421  1836    1836 MULTIPOLYGON (((-78.30876 3...
10 0.124     1.428  1837    1837 MULTIPOLYGON (((-80.02567 3...
> rowSums(nc[, 1:4], na.rm = TRUE)
Error in rowSums(nc[, 1:4], na.rm = TRUE) : 'x' must be numeric

> nc$newCol <- rowSums(as.data.frame(nc)[, 1:4], na.rm = TRUE)
> nc
Simple feature collection with 100 features and 15 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
Geodetic CRS:  NAD27
First 10 features:
    AREA PERIMETER CNTY_ CNTY_ID        NAME  FIPS FIPSNO CRESS_ID BIR74 SID74 NWBIR74 BIR79 SID79 NWBIR79
1  0.114     1.442  1825    1825        Ashe 37009  37009        5  1091     1      10  1364     0      19
2  0.061     1.231  1827    1827   Alleghany 37005  37005        3   487     0      10   542     3      12
3  0.143     1.630  1828    1828       Surry 37171  37171       86  3188     5     208  3616     6     260
4  0.070     2.968  1831    1831   Currituck 37053  37053       27   508     1     123   830     2     145
5  0.153     2.206  1832    1832 Northampton 37131  37131       66  1421     9    1066  1606     3    1197
6  0.097     1.670  1833    1833    Hertford 37091  37091       46  1452     7     954  1838     5    1237
7  0.062     1.547  1834    1834      Camden 37029  37029       15   286     0     115   350     2     139
8  0.091     1.284  1835    1835       Gates 37073  37073       37   420     0     254   594     2     371
9  0.118     1.421  1836    1836      Warren 37185  37185       93   968     4     748  1190     2     844
10 0.124     1.428  1837    1837      Stokes 37169  37169       85  1612     1     160  2038     5     176
                         geometry   newCol
1  MULTIPOLYGON (((-81.47276 3... 3651.556
2  MULTIPOLYGON (((-81.23989 3... 3655.292
3  MULTIPOLYGON (((-80.45634 3... 3657.773
4  MULTIPOLYGON (((-76.00897 3... 3665.038
5  MULTIPOLYGON (((-77.21767 3... 3666.359
6  MULTIPOLYGON (((-76.74506 3... 3667.767
7  MULTIPOLYGON (((-76.00897 3... 3669.609
8  MULTIPOLYGON (((-76.56251 3... 3671.375
9  MULTIPOLYGON (((-78.30876 3... 3673.539
10 MULTIPOLYGON (((-80.02567 3... 3675.552

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