Cannot cast array data from dtype('O') to dtype('float64') according to the rule 'safe'

Question

When running my Tukey test, it gives me this error:

Cannot cast array data from dtype('O') to dtype('float64') according to the rule 'safe'

My Dataframe Head Output:

    Group    Score
3   A        1.91
4   B        1.7
5   C        1.69
6   D        1.68
7   E        1.49

My Tukey Test Code:

from statsmodels.stats.multicomp import pairwise_tukeyhsd
from statsmodels.stats.multicomp import MultiComparison

mc = MultiComparison(df['Score'], df['Group'])
result = mc.tukeyhsd()

print(result)
print(mc.groupsunique)


> TypeError Traceback (most recent call
> last) <ipython-input-10-705a07612b72> in <module>()
>       1 mc = MultiComparison(df['Score'], df['Group'])
> ----> 2 result = mc.tukeyhsd()
>       3 
>       4 print(result)
>       5 print(mc.groupsunique)
> 
> /usr/local/lib/python3.6/dist-packages/statsmodels/sandbox/stats/multicomp.py
> in tukeyhsd(self, alpha)
>     964         self.groupstats = GroupsStats(
>     965                             np.column_stack([self.data, self.groupintlab]),
> --> 966                             useranks=False)
>     967 
>     968         gmeans = self.groupstats.groupmean
> 
> /usr/local/lib/python3.6/dist-packages/statsmodels/sandbox/stats/multicomp.py
> in __init__(self, x, useranks, uni, intlab)
>     535 
>     536         #temporary until separated and made all lazy
> --> 537         self.runbasic(useranks=useranks)
>     538 
>     539 
> 
> /usr/local/lib/python3.6/dist-packages/statsmodels/sandbox/stats/multicomp.py
> in runbasic(self, useranks)
>     569         else:
>     570             self.xx = x[:,0]
> --> 571         self.groupsum = groupranksum = np.bincount(self.intlab, weights=self.xx)
>     572         #print('groupranksum', groupranksum, groupranksum.shape, self.groupnobs.shape
>     573         # start at 1 for stats.rankdata :
> 
> TypeError: Cannot cast array data from dtype('O') to dtype('float64')
> according to the rule 'safe'

Does anyone know what this means?

Answer 1

Try replacing the line

mc = MultiComparison(df['Score'], df['Group'])

with

mc = MultiComparison(df['Score'].astype('float'), df['Group'])

If you obtain a failure there, then there is likely a problematic row. You can resolve this by using the following instead:

mc = MultiComparison(pd.to_numeric(df['Score'], errors='coerce'), df['Group'])