[英]Check for differences between the columns of two pandas data frames side by side
I thought this solution would solve my problem but the op here needed to check if the rows of his two data frames contained a difference. 我认为这个解决方案可以解决我的问题,但是这里需要检查他的两个数据帧的行是否包含差异。 I want to do the same but for the columns. 我想对列进行相同的操作。 The solution was ne = (df1 != df2).any(1)
but that does not help with my columns. 解决方案是ne = (df1 != df2).any(1)
但这对我的列没有帮助。 Yes, I just checked and both of my dataframes have exactly the same shape
. 是的,我刚检查过,我的两个数据帧都具有完全相同的shape
。 If I do df1 == df2
it gives me a new data frame full of trues and falses. 如果我做df1 == df2
它会给我一个充满真实和虚假的新数据框。 Looking at the first hundred rows it looks like most of the columns with a few exceptions are equal. 查看前100行,看起来大多数列都有相同的例外情况。 How can you just get one True / False for each column? 你怎么能为每一列得到一个真/假?
Here is a toy example: 这是一个玩具示例:
import numpy as np
import pandas as pd
df1 = pd.DataFrame(np.random.randint(low=0, high=10, size=(5, 5)), columns=['a', 'b', 'c', 'd', 'e'])
df2 = df1.copy()
df2.at[3,'d'] += 10
Desired output: 期望的输出:
A True
B True
C True
D False
E True
Use DataFrame.all
for check if all values per rows are True
s: 使用DataFrame.all
检查每行的所有值是否为True
:
print ((df1 == df2).all())
a True
b True
c True
d False
e True
dtype: bool
Detail: 详情:
print (df1 == df2)
a b c d e
0 True True True True True
1 True True True True True
2 True True True True True
3 True True True False True
4 True True True True True
Solution with any
is possible also, only need invert output by ~
: any
解决方案也是可能的,只需要反转输出~
:
print (~((df1 != df2).any()))
a True
b True
c True
d False
e True
dtype: bool
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