CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
x89
x89

Reputation: 3460

pass multiple rows into a function

I have a function

def get_similar_row(rows, target):
    """Return the index of the most similar row"""
    return np.argmax(cosine_similarity(rows, [target]))


get_similar_row([[1191, 3, 0, 1, 1], 
                 [3251, 2, 1, 0, 0], 
                 [1641, 1, 1, 1, 0]], [2133, 3, 0, 0, 1])

Instead of manually inputting numbers while calling the function, I want to pass all rows of my data frame df such that I skip the id and pass in all other variables for all rows. This is for the rows parameter of the function.

id  size    numberOfPlants  balcony   available  publicTransport    
0   1191    3               0         1           1
1   3251    2               1         0           0
2   1641    1               1         1           0
3   2133    3               0         0           1

Upvotes: 2

Views: 453

Answers (1)

jezrael
jezrael

Reputation: 862501

Use DataFrame.drop for remove id column, convert to numpy array and pass to function:

#target id
id1 = 3

#convert id to index if necessary
df1 = df.set_index('id')

#selected row by id
target = df1.loc[id1]

#removed target row from original data
get_similar_row(df1.drop(id1).to_numpy(), target.to_numpy())

Upvotes: 2

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