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pandas column type detection is not precise. for some columns the type in not the actual data type when reading xml files with read_xml.
Describe the solution you'd like
the solution is to add dtype option in the read_xml utility that will provide pandas with the wanted column types, this feature exists already with read_json, read_csv and many other utilities.
API breaking implications
this will make the read_xml utility detect the right type for each column. to keep the data in the correct format.
Describe alternatives you've considered
creating a script that will use the default pandas.DataFrame(......) constructor that contains dtype option to parse the xml file.
the loaded result from the read_xml is not the same as the xml file. the highlighted column is a string but pandas read it as an integer and with this the data is corrupted.
The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem?
pandas column type detection is not precise. for some columns the type in not the actual data type when reading xml files with read_xml.
Describe the solution you'd like
the solution is to add dtype option in the read_xml utility that will provide pandas with the wanted column types, this feature exists already with read_json, read_csv and many other utilities.
API breaking implications
this will make the read_xml utility detect the right type for each column. to keep the data in the correct format.
Describe alternatives you've considered
creating a script that will use the default pandas.DataFrame(......) constructor that contains dtype option to parse the xml file.


the loaded result from the read_xml is not the same as the xml file. the highlighted column is a string but pandas read it as an integer and with this the data is corrupted.
The text was updated successfully, but these errors were encountered: