Writing large Pandas Dataframes to CSV file in chunks

Question

How do I write out a large data files to a CSV file in chunks?

I have a set of large data files (1M rows x 20 cols). However, only 5 or so columns of the data files are of interest to me.

I want to make things easier by making copies of these files with only the columns of interest so I have smaller files to work with for post-processing. So I plan to read the file into a dataframe, then write to csv file.

I’ve been looking into reading large data files in chunks into a dataframe. However, I haven’t been able to find anything on how to write out the data to a csv file in chunks.

Here is what I’m trying now, but this doesn’t append the csv file:

with open(os.path.join(folder, filename), 'r') as src:
    df = pd.read_csv(src, sep='t',skiprows=(0,1,2),header=(0), chunksize=1000)
    for chunk in df:
        chunk.to_csv(os.path.join(folder, new_folder,
                                  "new_file_" + filename), 
                                  columns = [['TIME','STUFF']])

Asked By: Korean_Of_the_Mountain

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Source

Answer 1

Solution:

header = True
for chunk in chunks:

    chunk.to_csv(os.path.join(folder, new_folder, "new_file_" + filename),
        header=header, cols=[['TIME','STUFF']], mode='a')

    header = False

Notes:

The mode='a' tells pandas to append.
We only write a column header on the first chunk.

Answered By: Scratch'N'Purr

Answer 2

Check out the chunksize argument in the to_csv method. Here are the docs.

Writing to file would look like:

df.to_csv("path/to/save/file.csv", chunksize=1000, cols=['TIME','STUFF'])

Answered By: Alex

Answer 3

Why don’t you only read the columns of interest and then save it?

file_in = os.path.join(folder, filename)
file_out = os.path.join(folder, new_folder, 'new_file' + filename)

df = pd.read_csv(file_in, sep='t', skiprows=(0, 1, 2), header=0, names=['TIME', 'STUFF'])
df.to_csv(file_out)

Answered By: Alexander

Writing large Pandas Dataframes to CSV file in chunks

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