pass multiple rows into a function

Question

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

jezrael · Accepted Answer · 2021-03-17 08:51:39Z

2

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())

edited Mar 17, 2021 at 8:51

answered Mar 17, 2021 at 8:18

jezrael

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3 Comments

x89 Over a year ago

For example, if I want to check which row is the most similar to my third row. Here, the third row is target. The id is 2. So in my function, get_similar_row(rows, target) I want to pass the the third row just be specifying the id 2. But I want to ensure that while calculating the similarity within the function, the idfield is not included.

x89 Over a year ago

Then I need to compare my target with all other rows of the dataframe. So I need to pass all other rows in the rows parameter. But I want to exclude the third row since that's the original row that I am using as target. I also want to include the idfield from similarity calculation

jezrael Over a year ago

@x89 - for me mor clear, can you check edit?

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