Assign redudancy in pandas dataframe

Question

[flogin]

Hy guys, I have a dataframe like this:

                                                          Host Redundant
Cluster                                                                  
>Cluster 0                                   Diabrotica_barberi       NaN
>Cluster 1                                   Diabrotica_barberi       NaN
>Cluster 2                              Trichogramma_dendrolimi       NaN
>Cluster 3                                      Formica_exsecta       NaN
>Cluster 4                                      Formica_exsecta       NaN
>Cluster 5                                     Nephila_plumipes       NaN
>Cluster 6                             Ceutorhynchus_obstrictus       NaN
>Cluster 7                                   Spalangia_cameroni       NaN
>Cluster 8                                     Diaphorina_citri       NaN
>Cluster 9                                Aleurodicus_dispersus       NaN
>Cluster 10                               Aleurodicus_dispersus       NaN
>Cluster 11                                               Culex       NaN
>Cluster 12                            Chaetophiloscia_elongata       NaN
>Cluster 13                                      Bemisia_tabaci       NaN
>Cluster 14                                 Sogatella_furcifera       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                                 Sogatella_furcifera       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                              Laodelphax_striatellus       NaN
>Cluster 14                                 Sogatella_furcifera       NaN
>Cluster 14                                 Sogatella_furcifera       NaN
>Cluster 15                              Laodelphax_striatellus       NaN
>Cluster 16                                  Chilo_suppressalis       NaN
>Cluster 17                                  Metaphycus_ericeri       NaN
>Cluster 18                                   Cotesia_glomerata       NaN
>Cluster 18                                            Vespidae       NaN
>Cluster 18                                            Vespidae       NaN
>Cluster 19                               Neoceratitis_asiatica       NaN
>Cluster 19                               Neoceratitis_asiatica       NaN
>Cluster 19                               Neoceratitis_asiatica       NaN
>Cluster 20                                Brontispa_longissima       NaN

Where I have an Index "Cluster" and 2 columns (Host) and (Redundant).

I want to identify Index that has All hosts redundant, like Cluster 19 (considering that have several clusters with some redundant hosts like clusters 14 and 18, but I want assign as Redundant = True only clusters with all hosts equal.)

I know that df.drop_duplicates can remove redundant rows, but I want only to assign as True the "Redundant" column.

Can anyone explain to me how I can do this?

Thanks,

Answer 1

[Jianyu]

Do you mean you want to assign True to all clusters with the same hosts? Try this (Remember to store the dataframe first):

def allSame(mylist):
    return mylist == mylist[::-1]
for i in df.index.unique():
    df.loc[i, 'Redundant'] = allSame(list(df.loc[i,'Host']))

[flogin]

Exactly ! thanks !!!