CODEWITHSUNDEEP
pythonpandasdataframedata-structures
Andrew Tulip
Andrew Tulip

Reputation: 161

How to hash the strings of a dataframe in Python?

I need to somehow hash the strings of the dataframe's fields.

I have this df:

cars =            ['Tesla', 'Renault', 'Tesla', 'Fiat', 'Audi', 'Tesla', 'Mercedes', 'Mercedes']
included_colors = ['red', 'green', np.nan, np.nan, 'yellow', 'black', np.nan, 'orange']
data = {'Cars': cars, 'Included Colors': included_colors}
df = pd.DataFrame (data, columns = ['Cars', 'Included Colors'])

And it looks like this:

       Cars Included Colors
0     Tesla             red
1   Renault           green
2     Tesla             NaN
3      Fiat             NaN
4      Audi          yellow
5     Tesla           black
6  Mercedes             NaN
7  Mercedes          orange

I am trying to create a dictionary or another form of data structure that would be useful in this case, in this way:

so that I would finally have the cars and all the associated colors matched, like in this example:

Tesla - red, black
Renault - green
Fiat - np.nan
Audi - yellow
Mercedes - orange

I tried this code but I don't know how to continue...:

all_cars = df['Cars'].tolist() # extract all the cars from the df in a list
all_cars = list(dict.fromkeys(all_cars)) # make them unique

dis = {}
for car in all_cars:
    mask = (df['Cars'] == car)
    dis[df.loc[mask, 'Cars']] = df.loc[mask, 'Included Colors']

It does not have to be a dictionary, it could be anything, just to have all these key -values matched. I just thought that this data structure would fit.

How to make this work? Thanks a lot!!!!

Upvotes: 2

Views: 140

Answers (1)

Andrej Kesely
Andrej Kesely

Reputation: 195438

You can use groupby() and aggregate to list. Then create output dictionary:

x = df.groupby("Cars", as_index=False).agg(list)
out = dict(zip(x.Cars, x["Included Colors"]))
print(out)

Prints:

{'Audi': ['yellow'], 'Fiat': [nan], 'Mercedes': [nan, 'orange'], 'Renault': ['green'], 'Tesla': ['red', nan, 'black']}

Thanks to @QuangHoang a shorter answer:

print(df.groupby("Cars")['Included Colors'].agg(list).to_dict())

Upvotes: 2

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