ArrowInvalid: ("Could not convert dtype('int64') with type numpy.dtype[int64]: did not recognize Python value type when inferring an Arrow data type", 'Conversion failed for column dtype with type object')

Using Streamlit
1

When updated to streamlit 0.86.0

passing few dataframes causing pyarrow error

Traceback:
File "c:\users\krishna\anaconda3\lib\site-packages\streamlit\script_runner.py", line 350, in _run_script
    exec(code, module.__dict__)
File "C:\Users\krishna\Documents\Streamlit\*****\app.py", line 234, in <module>
    st.dataframe(num_stat)
File "c:\users\krishna\anaconda3\lib\site-packages\streamlit\elements\dataframe_selector.py", line 85, in dataframe
    return self.dg._arrow_dataframe(data, width, height)
File "c:\users\krishna\anaconda3\lib\site-packages\streamlit\elements\arrow.py", line 82, in _arrow_dataframe
    marshall(proto, data, default_uuid)
File "c:\users\krishna\anaconda3\lib\site-packages\streamlit\elements\arrow.py", line 160, in marshall
    proto.data = type_util.data_frame_to_bytes(df)
File "c:\users\krishna\anaconda3\lib\site-packages\streamlit\type_util.py", line 371, in data_frame_to_bytes
    table = pa.Table.from_pandas(df)
File "pyarrow\table.pxi", line 1561, in pyarrow.lib.Table.from_pandas
File "c:\users\krishna\anaconda3\lib\site-packages\pyarrow\pandas_compat.py", line 595, in dataframe_to_arrays
    for c, f in zip(columns_to_convert, convert_fields)]
File "c:\users\krishna\anaconda3\lib\site-packages\pyarrow\pandas_compat.py", line 595, in <listcomp>
    for c, f in zip(columns_to_convert, convert_fields)]
File "c:\users\krishna\anaconda3\lib\site-packages\pyarrow\pandas_compat.py", line 581, in convert_column
    raise e
File "c:\users\krishna\anaconda3\lib\site-packages\pyarrow\pandas_compat.py", line 575, in convert_column
    result = pa.array(col, type=type_, from_pandas=True, safe=safe)
File "pyarrow\array.pxi", line 302, in pyarrow.lib.array
File "pyarrow\array.pxi", line 83, in pyarrow.lib._ndarray_to_array
File "pyarrow\error.pxi", line 99, in pyarrow.lib.check_status
1 Like
2

What is the code? What does the df look like?

1 Like
3
4

Do this as a final step

df = df.astype(str)

I found it in other questions of this type and it worked for me

1 Like
5

Thank you, it works.!