pandas (original) (raw)

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Edit: As indicated in #39181 (comment), the source of the performance degradation was trailing nans at the end of the DataFrame after reading - rhshadrach

Code Sample, a copy-pastable example

Your code here

writer = ExcelWriter(# pylint: disable=abstract-class-instantiated path=fileName, engine='xlsxwriter')
workbook = writer.book # pylint: disable=no-member header_format = workbook.add_format({'bold': True, 'align': 'center', 'fg_color': '#80bfff', 'border': 2, 'font_name': 'Times New Roman', 'font_size': 9})

Problem description

the pylint detects that ExcelWriter don't have "book" member, but the code works well just have a very bad execution time in comparison with the 1.1.5 Pandas version

Expected Output

Save DataFrames in the same file but in different sheets. Expected time: 30 sec (pandas==1.1.5) Current time: 90 sec (pandas==1.2.0)

Output of `pd.show_versions()`

INSTALLED VERSIONS

commit : 3e89b4c4b1580aa890023fc550774e63d499da25 python : 3.8.6.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19041 machine : AMD64 processor : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : Spanish_Mexico.1252

pandas : 1.2.0 numpy : 1.19.1 pytz : 2020.1 dateutil : 2.8.1 pip : 20.3.3 setuptools : 49.2.1 Cython : None pytest : None hypothesis : None sphinx : 3.2.1 blosc : None feather : None xlsxwriter : 1.3.7 lxml.etree : 4.6.2 html5lib : 1.1 pymysql : None psycopg2 : None jinja2 : 2.11.2 IPython : 7.18.1 pandas_datareader: None bs4 : 4.9.3 bottleneck : None fsspec : None fastparquet : None gcsfs : None matplotlib : 3.3.1 numexpr : None odfpy : None openpyxl : 3.0.5 pandas_gbq : None pyarrow : 2.0.0 pyxlsb : None s3fs : None scipy : 1.5.4 sqlalchemy : None tables : None tabulate : 0.8.7 xarray : None xlrd : 1.2.0 xlwt : None numba : None