When converting one of the .csv's
to a pd.DataFrame
using the python odo
module I receive a TypeError
TypeError: Cannot cast array from dtype('float64') to dtype('int64')
according to the rule 'safe'
The code that works for other csv's
# csv table file name
csvNm = 'table.csv'
# convert mysql table to csv
odo_csv = odo(tstConn.connect_string + '::' + tbl , csvNm)
# convert csv to pandas
odo_df = odo(odo_csv , pd.DataFrame)
Here is what I tried so far to no avail:
import pandas as pd
from odo import odo, resource, discover, convert
odo_csv=odo(tstConn.connect_string + '::' + tbl , csvNm)
csv=resource(csvNm)
ds=discover(csv)
# Convert csv to pandas
odo_df = odo(odo_csv , pd.DataFrame, dshape=ds)
and this:
odo_df = odo(odo_csv , pd.DataFrame, casting='unsafe')
Update 1 It looks like I neglected the most obvious hint in this error
pandas\parser.pyx in pandas.parser.TextReader._convert_tokens (pandas\parser.c:11816)()
Leading to encoding issues in Windows SO. But neither this:
odo_df = odo(odo_csv , pd.DataFrame, encoding=odo_csv.encoding)
or this work
odo_df = odo(odo_csv , pd.DataFrame, encoding='cp1252')
This inelegant way (for my use-case) taken from pandas-reading-csv-files (same link as above)
# Python3
with open('/tmp/test.csv', 'r', encoding='cp1252') as f:
df = pd.read_csv(f)
print(df)
Not sure what to try next, any help would be appreciated.
The solution that works is:
import pandas as pd
from odo import odo, resource, discover, convert
# convert mysql to csv
odo_csv=odo(raw_dbConn.connect_string + '::' + tblName , csvNm, header=True)
# Get odo resource aka sqlalchemy.Table instance
resc=resource(raw_dbConn.connect_string + '::' + tblName )
# Discover the resc
ds=discover(resc)
# Convert csv to dataframe
odo_df = odo(odo_csv , pd.DataFrame, dshape=ds ,encoding=odo_csv.encoding)