How can I convert pandas object to h2o dataframe safely?
import h2o import pandas as pd df = pd.DataFrame({'col1': [1,1,2], 'col2': ['César Chávez Day', 'César Chávez Day', 'César Chávez Day']}) hf = h2o.H2OFrame(df) #gives error UnicodeEncodeError: 'ascii' codec can't encode character '\xe9' in position 4: ordinal not in range(128)
Environment: Python 3.5, h2o 3.10.4.2
I agree that this is not an H2O-specific issue. This works for me (same H2O and Python version):
import h2o import pandas as pd df = pd.DataFrame({'col1': [1,1,2], 'col2': ['César Chávez Day', 'César Chávez Day', 'César Chávez Day']}) hf = h2o.H2OFrame(df) ## -- End pasted text -- Parse progress: |█████████████████████████████████████████████████████████| 100% In [4]: hf Out[4]: col1 col2 ------ ---------------- 1 César Chávez Day 1 César Chávez Day 2 César Chávez Day [3 rows x 2 columns] In [5]: type('César Chávez Day') Out[5]: str My specs (you may need to change your default encoding):
In [6]: import sys In [7]: sys.getdefaultencoding() Out[7]: 'utf-8' This thread may help: How do I check if a string is unicode or ascii?
type('César Chávez Day') is "str"?df = pd.DataFrame({'col1': [1,1,2], 'col2': [str('César Chávez Day'), str('César Chávez Day'), str('César Chávez Day')]})type('César Chávez Day') = str and your second advice also causes the same unicode erorr