Database Reference
In-Depth Information
| 4.6 | 3.1 | 1.5 | 0.2 |
|---------------+-------------+--------------+--------------|
Here, the included columns are kept in the same order. Instead of the column names,
you can also specify the indices of the columns, which start at 1. This allows you to,
for example, select only the odd columns (should you ever need it!):
$
echo
'a,b,c,d,e,f,g,h,i\n1,2,3,4,5,6,7,8,9'
|
>
csvcut -c
$(
seq 1 2 9 | paste -sd,
)
a,c,e,g,i
1,3,5,7,9
If you're certain that there are no commas in any of the values, then you can also use
cut
to extract columns. Be aware that
cut
does not reorder columns, as is demon‐
strated with the following command:
$
echo
'a,b,c,d,e,f,g,h,i\n1,2,3,4,5,6,7,8,9'
| cut -d, -f 5,1,3
a,c,e
1,3,5
As you can see, it doesn't matter in which order we specify the columns; with
cut
they will always appear in the original order. For completeness, let's also take a look at
the SQL approach for extracting and reordering the numerical columns of the Iris
data set:
$
< iris.csv csvsql --query
"SELECT sepal_length, petal_length, "
\
>
"sepal_width, petal_width FROM stdin"
| head -n 5 | csvlook
|---------------+--------------+-------------+--------------|
| sepal_length | petal_length | sepal_width | petal_width |
|---------------+--------------+-------------+--------------|
| 5.1 | 1.4 | 3.5 | 0.2 |
| 4.9 | 1.4 | 3.0 | 0.2 |
| 4.7 | 1.3 | 3.2 | 0.2 |
| 4.6 | 1.5 | 3.1 | 0.2 |
|---------------+--------------+-------------+--------------|
Filtering Lines
The difference between filtering lines in a CSV file as opposed to a plain-text file is
that you may want to base this filtering on values in a certain column only. Filtering
on location is essentially the same, but you have to take into account that the first line
of a CSV file is usually the header. Remember that you can always use the
body
command-line tool if you want to keep the header:
$
seq 5 | sed -n
'3,5p'
3
4
5
$
seq 5 | header -a count | body sed -n
'3,5p'
count
3
