PYTHON

python load pandas from pickle

>>> unpickled_df = pd.read_pickle("./dummy.pkl")
>>> unpickled_df
   foo  bar
0    0    5
1    1    6
2    2    7
3    3    8
4    4    9

pandas to pickle

# use pickle format to save columns with complex data (like list) 
# and keep their structure

>>> original_df = pd.DataFrame({"foo": range(5), "bar": range(5, 10)})
>>> original_df
   foo  bar
0    0    5
1    1    6
2    2    7
3    3    8
4    4    9
>>> original_df.to_pickle("./dummy.pkl") # use read_pickle to read the dataframe

python pickle dataframe

# save and load of DataFrames
dateiTraining = "daten/Training.zip"
trainDataFrame.to_pickle( self.dateiTraining )
if ( os.path.exists( dateiTraining ) ):
	testDataFrame = panda.read_pickle( dateiTraining )