create a sublist from a dataframe-CodePudding

I have this dataframe of 11527 rows in csv format constitued of a list of marks and models of boats

Ultramar Ultra 570 Open
Ultramar Ultra 600
Ultramar Ultra 660 Open
Ultramar Ultramar 440 Open
Ultramar Week End 550
Ultramar Week End 600
Ultramar Week End 650
Ultramar Week End 700
Ultramar Winner 650
Ultramar Winner 800
Ultramar Orque 70
Gobbi Atlantis 47
Gobbi Atlantis 55
Gobbi Gobbi 19
Gobbi Gobbi 21 Sport
Gobbi Gobbi 225 Cabin
Gobbi Gobbi 225 Sport
Gobbi Gobbi 23 Cabin
Gobbi Gobbi 23 Offshore
Gobbi Gobbi 23 Sport
Gobbi Gobbi 245 Cabin

I want to obtain a sublist from this dataframe when i call a particular mark, it returns all the models for this mark

i basically get the start :

import pandas as pd
pd.read_csv("marque_modele_ref.csv", sep=";")

but i don't know how to create separate lists from the mark and models and make some loop to call every models by distincts marks, a bit like a group by in SQL

Any idea ?

Regards,

CodePudding user response：

Having the following DataFrame

>>> df
    make    model1 model2    model3
0   Ultramar     Ultra    600      None
1   Ultramar     Ultra    660      Open
2   Ultramar  Ultramar    440      Open
3   Ultramar      Week    End       550
4   Ultramar      Week    End       600
5   Ultramar      Week    End       650
6   Ultramar      Week    End       700
7   Ultramar    Winner    650      None
8   Ultramar    Winner    800      None
9   Ultramar     Orque     70      None
10     Gobbi  Atlantis     47      None
11     Gobbi  Atlantis     55      None
12     Gobbi     Gobbi     19      None
13     Gobbi     Gobbi     21     Sport
14     Gobbi     Gobbi    225     Cabin
15     Gobbi     Gobbi    225     Sport
16     Gobbi     Gobbi     23     Cabin
17     Gobbi     Gobbi     23  Offshore
18     Gobbi     Gobbi     23     Sport
19     Gobbi     Gobbi    245     Cabin

We can select a specific 'make' and then collect the corresponding models into a list by using .loc and tolist()

df.loc[df['make'] == 'Ultramar','model1'].tolist()

gives us

['Ultra', 'Ultra', 'Ultramar', 'Week', 'Week', 'Week', 'Week', 'Winner', 'Winner', 'Orque']

You probably needs the other three columns too, in which case you can do

df.model3 = df.model3.fillna('')
model = df.model1   ' '   df.model2   ' '  df.model3 # concat the values with a space
df.model = model # assign to the original DataFrame
df.loc[df['make'] == 'Ultramar','model'].tolist()

that gives

['Ultra 600 ', 'Ultra 660 Open', 'Ultramar 440 Open', 'Week End 550', 'Week End 600', 'Week End 650', 'Week End 700', 'Winner 650 ', 'Winner 800 ', 'Orque 70 ']