pandas python - how to convert array (different length with data frame) to data frame and keep the row and column name?

Question

first of all, I have calculated the cosine similarities using the data frame and the result is returned array object.

assumed that, this is my data frame

   A B C D E
X1 0 0 1 0 1
X2 0 1 2 3 1
X3 0 1 1 0 1

here is the way I have calculated the df

df = df.drop(['colX'], axis=1)
cos_sim = cosine_similarity(df_new_jac)

and it returns like this

array([[0.,   0., 1.],
       [0.,  1., 2.],
       [0.,  1., 1.]

however, i hope to see the result like this

   X1 X2 X3 
X1 0  0  1 
X2 0  1  2 
X3 0  1  1 

but, according to the shape of 'df' and 'cos_sim' are having the different shape, I can't use this code

df = df.set_index('colX')
v = cosine_similarity(df.values)

df[:] = v
df.reset_index()

the error shows, the len must be equivalent. is any suggestion to fix this issue?

Answer 1

not exactly sure what you're trying to achieve here, but here is my best guess:

import pandas as pd
# the original df
df1 = pd.DataFrame({'index': ['X1','X2','X3'], 'A':[0,0,0], 'B':[0,1,1], 'C': [1,2,1], 'D': [0,3,0], 'E':[1,1,1]})
# the cosine_similarity df
df2 = pd.DataFrame({'index': ['X1','X2','X3'], 'X1':[0,0,0], 'X2':[0, 1,1], 'X3':[1,2,1]})
# note the 'index' column is a column, not the index.

# merge the 2, by default on the common column (i.e. the 'index' column)
df = df1.merge(df2)
df.set_index('index', inplace=True)
>   A   B   C   D   E   X1  X2  X3
index                               
X1  0   0   1   0   1   0   0   1
X2  0   1   2   3   1   0   1   2
X3  0   1   1   0   1   0   1   1