Pandas dataframe to GDB

edited September 2019 in GX Developer
I have a Pandas dataframe that I want to convert to a GDB. I am using a dataframe because I have text and numeric data fields.

if df is my dataframe, df.dtype returns:
SurveyName object (this is how Pandas reports my string fields)
Job int64
Record int64
Date int64
dtype: object

When I try to write the line gdb.write_line('L0', df, df.columns) I get the errors:
File "...\geosoft\gxpy\", line 2146, in write_line
self.write_channel(line, cs, data[:, np_index: np_index + w], fid=fid)

File "...\geosoft\gxpy\", line 2027, in write_channel
cs = self.new_channel(channel, data.dtype, array=_va_width(data))

File "...\geosoft\gxpy\", line 1189, in new_channel

File "...\geosoft\gxpy\", line 566, in gx_dtype
return _np2gx_type[str(dtype)]

KeyError: 'object'

I also tried explicitly converting each text dataframe column to strings, but it doesn't help:
for column in df.select_dtypes(include=['object']):
    df[column] = df[column].astype('|S')
Is it possible to go directly from a Pandas dataframe to a GDB? Or do I need to use low level functions to write each channel and manually specify the type?



  • NickWilliams
    edited September 2019
    It looks like a small change to the function gx_dtype in the gxpy code avoids the error. Adding the np.object_ check as below:
        if dtype.type is np.str_:
            # x4 to allow for full UTF-8 characters
            return -int(dtype.str[2:])*4
        elif dtype.type is np.object_:
            # My edit, assign length 80 to all strings
            return -int(80)
    I assume this is not a complete solution. Any ideas how to do this properly?
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