gabrielrandi
gabrielrandi

Reputation: 21

Problems with pd.merge

Hope you all are having an excellent week.

So, I was finishing a script that worked really well for an specific use case. The base is as follows:

Funcion cosine_similarity_join:

def cosine_similarity_join(a:pd.DataFrame, b:pd.DataFrame, col_name):

    a_len = len(a[col_name])

    # all of the "documents" in a 1D array
    corpus = np.concatenate([a[col_name].to_numpy(), b[col_name].to_numpy()])
    
    # vectorize the array
    tfidf, vectorizer = fit_vectorizer(corpus, 3)

    # in this matrix each row represents the str in a and the col is the str from b, value is the cosine similarity
    res = cosine_similarity(tfidf[:a_len], tfidf[a_len:])

    res_series = pd.DataFrame(res).stack().rename("score")
    res_series.index.set_names(['a', 'b'], inplace=True)
    
    # join scores to b
    b_scored = pd.merge(left=b, right=res_series, left_index=True, right_on='b').droplevel('b')

    # find the indices on which to match, (highest score in each row)
    best_match = np.argmax(res, axis=1)

    # Join the rest of 
    res = pd.merge(left=a, right=b_scored, left_index=True, right_index=True, suffixes=('', '_Guess'))
    print(res)

    df = res.reset_index()
    df = df.iloc[df.groupby(by="RefCol")["score"].idxmax()].reset_index(drop=True)

    return df

This works like a charm when I do something like:

resulting_df = cosine_similarity_join(df1,df2,'My_col')

But in my case, I need something in the lines of:

big_df = pd.read_csv('some_really_big_df.csv')
some_other_df = pd.read_csv('some_other_small_df.csv')

counter = 0
size = 10000
total_size = len(big_df)

while counter <= total_size:

    small_df = big_df[counter:counter+size]
    resulting_df = cosine_similarity_join(small_df,some_other_df,'My_col')
    counter += size
    

I already mapped the problem until one specific line in the function:

res = pd.merge(left=a, right=b_scored, left_index=True, right_index=True, suffixes=('', '_Guess'))

Basically this res dataframe is coming out empty and I just cannot understand why (since when I replicate the values outside of the loop it works just fine)...

I looked at the problem for hours now and would gladly accept a new light over the question.

Thank you all in advance!

Upvotes: 0

Views: 34

Answers (1)

gabrielrandi
gabrielrandi

Reputation: 21

Found the problem!

I just needed to reset the indexes for the join clause - once I create a new small df from the big df, the indexes remain equal to the slice of the big one, thus generating the problem when joining with another df!

So basically all I needed to do was:

while counter <= total_size:

    small_df = big_df[counter:counter+size]
    small_df = small_df.reset_index()
    resulting_df = cosine_similarity_join(small_df,some_other_df,'My_col')
    counter += size

I'll leave it here in case it helps someone :)

Cheers!

Upvotes: 1

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