New submission from Dragoljub <dragol...@gmail.com>:
xref: https://github.com/pandas-dev/pandas/issues/23516 Example: import io import pandas as pd import numpy as np df = pd.DataFrame(np.random.randn(1000000, 10), columns=('COL{}'.format(i) for i in range(10))) csv = io.StringIO(df.to_csv(index=False)) df2 = pd.read_csv(csv) #3.5X slower on Python 3.7.1 pd.read_csv() reads data at 30MB/sec on Python 3.7.1 while at 100MB/sec on Python 3.6.7. This issue seems to be only present on Windows 10 Builds both x86 & x64. Possibly some IO changes in Python 3.7 could have contributed to this slowdown on Windows but not on Linux? ---------- components: IO messages: 329490 nosy: Dragoljub priority: normal severity: normal status: open title: Pandas read_csv() is 3.5X Slower on Python 3.7.1 vs Python 3.6.7 & 3.5.2 On Windows 10 type: performance versions: Python 3.7 _______________________________________ Python tracker <rep...@bugs.python.org> <https://bugs.python.org/issue35195> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
