I use this code
library(foreign)
rt<- read.dbf("rt001.dbf")
It creats more variable like ’ changed to: ‘X.’
Field name: ‘’ changed to: ‘X’
Field name: ‘’ changed to: ‘X.1’
Field name: ‘’ changed to: ‘X.2’
Field name: ‘’ changed to: ‘X.3’
Field name: ‘’ changed to: ‘X.4’
Field name: ‘’ changed to: ‘X.5’
Field name: ‘’ changed to: ‘X.6’
Also, it reduces observations such as if I have 120487 observation, I will give me just 12048.
How to solve this?
Hi, and welcome!
Normally, a reproducible example, called a reprex would be helpful, and it's always a good idea to include one, if possible. However, it's not always possible to run one, so I have to cut-and-paste.
Here's how it should work
>
> library(foreign)
> # from example
> x <- read.dbf(system.file("files/sids.dbf", package="foreign")[1])
> str(x)
'data.frame': 100 obs. of 14 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_ : int 1825 1827 1828 1831 1832 1833 1834 1835 1836 1837 ...
$ CNTY_ID : int 1825 1827 1828 1831 1832 1833 1834 1835 1836 1837 ...
$ NAME : Factor w/ 100 levels "Alamance","Alexander",..: 5 3 86 27 66 46 15 37 93 85 ...
$ FIPS : Factor w/ 100 levels "37001","37003",..: 5 3 86 27 66 46 15 37 93 85 ...
$ FIPSNO : int 37009 37005 37171 37053 37131 37091 37029 37073 37185 37169 ...
$ 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 ...
- attr(*, "data_types")= chr "N" "N" "N" "N" ...
> summary(x)
AREA PERIMETER CNTY_ CNTY_ID NAME FIPS FIPSNO CRESS_ID
Min. :0.042 Min. :0.999 Min. :1825 Min. :1825 Alamance : 1 37001 : 1 Min. :37001 Min. : 1.0
1st Qu.:0.091 1st Qu.:1.324 1st Qu.:1902 1st Qu.:1902 Alexander: 1 37003 : 1 1st Qu.:37050 1st Qu.: 25.8
Median :0.120 Median :1.608 Median :1982 Median :1982 Alleghany: 1 37005 : 1 Median :37100 Median : 50.5
Mean :0.126 Mean :1.673 Mean :1986 Mean :1986 Anson : 1 37007 : 1 Mean :37100 Mean : 50.5
3rd Qu.:0.154 3rd Qu.:1.859 3rd Qu.:2067 3rd Qu.:2067 Ashe : 1 37009 : 1 3rd Qu.:37150 3rd Qu.: 75.2
Max. :0.241 Max. :3.640 Max. :2241 Max. :2241 Avery : 1 37011 : 1 Max. :37199 Max. :100.0
(Other) :94 (Other):94
BIR74 SID74 NWBIR74 BIR79 SID79 NWBIR79
Min. : 248 Min. : 0.00 Min. : 1 Min. : 319 Min. : 0.00 Min. : 3
1st Qu.: 1077 1st Qu.: 2.00 1st Qu.: 190 1st Qu.: 1336 1st Qu.: 2.00 1st Qu.: 250
Median : 2180 Median : 4.00 Median : 698 Median : 2636 Median : 5.00 Median : 874
Mean : 3300 Mean : 6.67 Mean :1051 Mean : 4224 Mean : 8.36 Mean : 1353
3rd Qu.: 3936 3rd Qu.: 8.25 3rd Qu.:1168 3rd Qu.: 4889 3rd Qu.:10.25 3rd Qu.: 1407
Max. :21588 Max. :44.00 Max. :8027 Max. :30757 Max. :57.00 Max. :11631
However,
The DBF format is documented but not much adhered to. There is is no guarantee this will read all DBF files.
You might have better luck with the RODBC package
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