使用python pandas在数据框中的选定列为数据的每一行创建哈希值 [英] Create hash value for each row of data with selected columns in dataframe in python pandas

问题描述

我问了类似的问题中有关为数据的每一行创建哈希值的信息.我知道我可以使用hashlib.md5(b'Hello World').hexdigest()之类的东西来对字符串进行哈希处理，但是数据框中的行又如何呢?

I have asked similar question in R about creating hash value for each row of data. I know that I can use something like hashlib.md5(b'Hello World').hexdigest() to hash a string, but how about a row in a dataframe?

我起草了如下代码:

for index, row in course_staff_df.iterrows():
        temp_df.loc[index,'hash'] = hashlib.md5(str(row[['cola','colb']].values)).hexdigest()

对我来说似乎不是很pythonic，有什么更好的解决方法吗?

It seems not very pythonic to me, any better solution?

推荐答案

或者简单地:

df.apply(lambda x: hash(tuple(x)), axis = 1)

例如:

import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.rand(3,5))
print df
df.apply(lambda x: hash(tuple(x)), axis = 1)

     0         1         2         3         4
0  0.728046  0.542013  0.672425  0.374253  0.718211
1  0.875581  0.512513  0.826147  0.748880  0.835621
2  0.451142  0.178005  0.002384  0.060760  0.098650

0    5024405147753823273
1    -798936807792898628
2   -8745618293760919309

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