How do I read a large csv file with pandas?

Question

I am trying to read a large csv file (aprox. 6 GB) in pandas and i am getting a memory error:

MemoryError                               Traceback (most recen         


        

Answer 1

In addition to the answers above, for those who want to process CSV and then export to csv, parquet or SQL, d6tstack is another good option. You can load multiple files and it deals with data schema changes (added/removed columns). Chunked out of core support is already built in.

def apply(dfg):
    # do stuff
    return dfg

c = d6tstack.combine_csv.CombinerCSV([bigfile.csv], apply_after_read=apply, sep=',', chunksize=1e6)

# or
c = d6tstack.combine_csv.CombinerCSV(glob.glob('*.csv'), apply_after_read=apply, chunksize=1e6)

# output to various formats, automatically chunked to reduce memory consumption
c.to_csv_combine(filename='out.csv')
c.to_parquet_combine(filename='out.pq')
c.to_psql_combine('postgresql+psycopg2://usr:pwd@localhost/db', 'tablename') # fast for postgres
c.to_mysql_combine('mysql+mysqlconnector://usr:pwd@localhost/db', 'tablename') # fast for mysql
c.to_sql_combine('postgresql+psycopg2://usr:pwd@localhost/db', 'tablename') # slow but flexible