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Use pandas. read_csv() to read a specific column from a CSV file. To read a CSV file, call pd. read_csv(file_name, usecols=cols_list) with file_name as the name of the CSV file, delimiter as the delimiter, and cols_list as the list of specific columns to read from the CSV file.
This can be done with the help of the pandas. read_csv() method. We will pass the first parameter as the CSV file and the second parameter the list of specific columns in the keyword usecols. It will return the data of the CSV file of specific columns.
To select an entire column, click the column letter or press Ctrl+spacebar.
You could use awk for this. Change '$2' to the nth column you want.
awk -F "\"*,\"*" '{print $2}' textfile.csv
yes. cat mycsv.csv | cut -d ',' -f3 will print 3rd column.
The simplest way I was able to get this done was to just use csvtool. I had other use cases as well to use csvtool and it can handle the quotes or delimiters appropriately if they appear within the column data itself.
csvtool format '%(2)\n' input.csv
Replacing 2 with the column number will effectively extract the column data you are looking for.
Landed here looking to extract from a tab separated file. Thought I would add.
cat textfile.tsv | cut -f2 -s
Where -f2 extracts the 2, non-zero indexed column, or the second column.
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