I have a .csv data set which is separated by "," and has about 5,000 rows and "5" columns.
However, for some columns, the content contains also ",", for example:
2660,11-01-2016,70.75,05-06-2013,I,,,
4080,26-02-2016,59.36,,D
Thus, when I tried to read it with read_delim()
, it will throw me warnings
, but the result shall be fine, for example:
Warning: 7 parsing failures.
row # A tibble: 5 x 5 col row col expected actual file expected actual 1 309 5 columns 8 columns 'data/my_data.csv' file 2 523 5 columns 7 columns 'data/my_data.csv' row 3 588 5 columns 8 columns 'data/my_data.csv' col 4 1661 5 columns 9 columns 'data/my_data.csv' expected 5 1877 5 columns 7 columns 'data/my_data.csv'
Is there any way for me to tackle this problem?
I guess I could use read_Lines()
and process it one by one and then turn them into a data frame.
Do you have any other ways to deal with such a situation?
1) read.table with fill=TRUE Using fill=TRUE
with read.table
results in no warnings:
Lines <- "2660,11-01-2016,70.75,05-06-2013,I,,,
4080,26-02-2016,59.36,,D"
# replace text = Lines with your filename
read.table(text = Lines, sep = ",", fill = TRUE)
giving:
V1 V2 V3 V4 V5 V6 V7 V8
1 2660 11-01-2016 70.75 05-06-2013 I NA NA NA
2 4080 26-02-2016 59.36 D NA NA NA
2) replace 1st 4 commas with semicolon Another approach would be:
# replace textConnection(Lines) with your filename
L <- readLines(textConnection(Lines))
for(i in 1:4) L <- sub(",", ";", L)
read.table(text = L, sep = ";")
giving:
V1 V2 V3 V4 V5
1 2660 11-01-2016 70.75 05-06-2013 I,,,
2 4080 26-02-2016 59.36 D
3) remove commas at end of lines Another possibility is to remove commas at the end of lines. (If you are on Windows then sed is in the Rtools distribution.)
read.table(pipe("sed -e s/,*$// readtest.csv"), sep = ",")
giving:
V1 V2 V3 V4 V5
1 2660 11-01-2016 70.75 05-06-2013 I
2 4080 26-02-2016 59.36 D
3a) similar to (3) but without sed
# replace textConnection(Lines) with your filename
L <- readLines(textConnection(Lines))
read.table(text = sub(",*$", "", L), sep = ",")