Python Pandas: How to read only first n rows of CSV files in?

Question

I have a very large data set and I can't afford to read the entire data set in. So, I'm thinking of reading only one chunk of it to train but I have no idea how to do it. Any thought will be appreciated.

Solution

If you only want to read the first 999,999 (non-header) rows:

read_csv(..., nrows=999999)

If you only want to read rows 1,000,000 ... 1,999,999

read_csv(..., skiprows=1000000, nrows=999999)

nrows : int, default None Number of rows of file to read. Useful for reading pieces of large files*

skiprows : list-like or integer Row numbers to skip (0-indexed) or number of rows to skip (int) at the start of the file

and for large files, you'll probably also want to use chunksize:

chunksize : int, default None Return TextFileReader object for iteration

pandas.io.parsers.read_csv documentation

Comments

[smci]

That's ok, they're slightly hidden. The doc could do with these examples. chunksize is a bit of a pain, you have to deal with unevenly-sized chunks. Also preallocate your arrays/dataframes with the fixed size you know you'll need, don't dynamically do concat/append whenever you can avoid it.

[smci]

...and also, it's not like the interface is nstart=,nend=.... You have to do the arithmetic on skiprows = nend - nrows

[FooBar]

I guess that's just taken over from SQL: LIMIT nstart, skiprows :/

[smci]

...and don't forget off-by-n errors if you also use header=n/list