比较两个 pandas 数据框的差异 [英] Comparing two pandas dataframes for differences

问题描述

我有一个脚本可以更新5到10列的数据，但有时起始csv与结束csv相同，因此我不想写相同的csvfile，而是希望它不执行任何操作...

I've got a script updating 5-10 columns worth of data , but sometimes the start csv will be identical to the end csv so instead of writing an identical csvfile I want it to do nothing...

如何比较两个数据框以检查它们是否相同?

How can I compare two dataframes to check if they're the same or not?

csvdata = pandas.read_csv('csvfile.csv')
csvdata_old = csvdata

# ... do stuff with csvdata dataframe

if csvdata_old != csvdata:
    csvdata.to_csv('csvfile.csv', index=False)

有什么想法吗?

推荐答案

您还需要注意创建DataFrame的副本，否则csvdata_old将使用csvdata更新(因为它指向同一个对象):

You also need to be careful to create a copy of the DataFrame, otherwise the csvdata_old will be updated with csvdata (since it points to the same object):

csvdata_old = csvdata.copy()

要检查它们是否相等，您可以使用assert_frame_equal，如该答案所示:

To check whether they are equal, you can use assert_frame_equal as in this answer:

from pandas.util.testing import assert_frame_equal
assert_frame_equal(csvdata, csvdata_old)

您可以将其包装在函数中，例如:

You can wrap this in a function with something like:

try:
    assert_frame_equal(csvdata, csvdata_old)
    return True
except:  # appeantly AssertionError doesn't catch all
    return False

有人在讨论更好的方法...

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