pandas_streaming aims at processing big files with pandas, too big to hold in memory, too small to be parallelized with a significant gain. The module replicates a subset of pandas API and implements other functionalities for machine learning.
from pandas_streaming.df import StreamingDataFrame sdf = StreamingDataFrame.read_csv("filename", sep="\t", encoding="utf-8") for df in sdf: # process this chunk of data # df is a dataframe print(df)
The module can also stream an existing dataframe.
import pandas df = pandas.DataFrame([dict(cf=0, cint=0, cstr="0"), dict(cf=1, cint=1, cstr="1"), dict(cf=3, cint=3, cstr="3")]) from pandas_streaming.df import StreamingDataFrame sdf = StreamingDataFrame.read_df(df) for df in sdf: # process this chunk of data # df is a dataframe print(df)
It contains other helpers to split datasets into train and test with some weird constraints.