pandas check if all rows of a dataframe are equal or same

awhan — Wed, 29 Aug 2018 00:16:13 +0000

I could not easily find solutions for this problem hence this post.

Here are two ways of checking that
df.apply(pd.Series.nunique, axis=0).unique().tolist() == [1]
and
df.groupby(df.columns.tolist()).ngroups == 1

the groupby method was *slightly* faster in my timing tests using the following code
import pandas as pd import timeit


data = [

    dict(zip(list('abc'), range(1, 4))),

    dict(zip(list('abc'), range(1, 4))),

]
df = pd.DataFrame(data)
print(df.apply(pd.Series.nunique, axis=0).unique().tolist() == [1])
print(df.groupby(df.columns.tolist()).ngroups == 1)
print(timeit.timeit('df.apply(pd.Series.nunique, axis=0).unique().tolist() == [1]',

                    number=1000, globals=globals()))

print(timeit.timeit('df.groupby(df.columns.tolist()).ngroups == 1', number=1000, globals=globals()))

python – Awhan Patnaik

pandas check if all rows of a dataframe are equal or same