In Python, compare row diffs for multiple columns

Question

I want to perform a row by row comparison over multiple columns. I want a single series, indicating if all entries in a row (over several columns) are the same as the previous row.

Lets say I have the following dataframe

import pandas as pd
df = pd.DataFrame({'A' : [1, 1, 1, 2, 2], 
                   'B' : [2, 2, 3, 3, 3], 
                   'C' : [1, 1, 1, 2, 2]})

I can compare all the rows, of all the columns

>>> df.diff().eq(0)
       A      B      C
0  False  False  False
1   True   True   True
2   True  False   True
3  False   True  False
4   True   True   True

This gives a dataframe comparing each series individually. What I want is the comparison of all columns in one series.

I can achieve this by looping

compare_all = df.diff().eq(0)
compare_tot = compare_all[compare_all.columns[0]]
for c in compare_all.columns[1:]:
    compare_tot = compare_tot & compare_all[c]

This gives

>>> compare_tot
0    False
1     True
2    False
3    False
4     True
dtype: bool

as expected.

Is it possible to achieve this in with a one-liner, that is without the loop?

Alexander · Accepted Answer · 2017-08-24 06:45:13Z

2

>>> (df == df.shift()).all(axis=1)
0    False
1     True
2    False
3    False
4     True
dtype: bool

answered Aug 24, 2017 at 6:45

Alexander

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2 Comments

mortysporty Over a year ago

Am I right to assume that the diff()-function only works for numerical data, whilst this works for strings as well?

Alexander Over a year ago

Correct. The diff method would throw an error if the values cannot be differenced such as the case with strings.

Zero · Accepted Answer · 2017-08-24 06:37:52Z

1

You need all

In [1306]: df.diff().eq(0).all(1)
Out[1306]:
0    False
1     True
2    False
3    False
4     True
dtype: bool

answered Aug 24, 2017 at 6:37

Zero

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