How can I partially read a huge CSV file?

Question

I have a very big csv file so that I can not read them all into the memory. I only want to read and process a few lines in it. So I am seeking a function in Pandas which could handle this task, which the basic python can handle this well:

with open('abc.csv') as f:
    line = f.readline()
    # pass until it reaches a particular line number....

However, if I do this in pandas, I always read the first line:

datainput1 = pd.read_csv('matrix.txt',sep=',', header = None, nrows = 1 )
datainput2 = pd.read_csv('matrix.txt',sep=',', header = None, nrows = 1 )

I am looking for some easier way to handle this task in pandas. For example, if I want to read rows from 1000 to 2000. How can I do this quickly?

I want to use pandas because I want to read data into the dataframe.

Asked By: lserlohn

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Source

Answer 1

Use chunksize:

for df in pd.read_csv('matrix.txt',sep=',', header = None, chunksize=1):
    #do something

To answer your second part do this:

df = pd.read_csv('matrix.txt',sep=',', header = None, skiprows=1000, chunksize=1000)

This will skip the first 1000 rows and then only read the next 1000 rows giving you rows 1000-2000, unclear if you require the end points to be included or not but you can fiddle the numbers to get what you want.

Answered By: EdChum

Answer 2

In addition to EdChums answer I find the nrows argument useful which simply defines the number of rows you want to import with pandas’ read_csv().

Thereby you don’t get an iterator but rather can just import a part of the whole file of size nrows. It works with skiprows too.

df = pd.read_csv('matrix.txt', sep=',', header=None, skiprows=1000, nrows=1000)

Answered By: petezurich

How can I partially read a huge CSV file?

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