ValueError when inserting data into numpy Array

I am trying to insert data from a dataframe df into a numpy array matrix_of_coupons_and_facevalues. However, I basically need to add the value associated with a row of df['Coupon'] into each column of a corresponding row of the array for as many columns as the number numberofcoupon_payments = row1['months_to_maturity']/6. I get the error ValueError: could not broadcast input array from shape (1,2) into shape (1,61) in the line np.insert(matrix_of_coupons_and_facevalues, row_no+1, rowtobeadded, 0) and I understand why, but I don't know how to proceed.

The code I am using is as follows:

matrix_of_coupons_and_facevalues = np.zeros((number_of_rows_and_columns, number_of_rows_and_columns))
        rowtobeadded = np.zeros(number_of_rows_and_columns)
        for (i1,row1) in df.iterrows():
            numberofcoupon_payments = row1['months_to_maturity']/6
            for row_no in range(int(number_of_rows_and_columns)):
                for index_no in range(int(numberofcoupon_payments)):
                    coupon = row1['coupon']
                    rowtobeadded = np.full((1, numberofcoupon_payments), coupon)
                    np.insert(matrix_of_coupons_and_facevalues, row_no+1, rowtobeadded, 0)

Edit: The dataframe df looks like this:

   months_to_maturity          on_the_run_dt          asset_id  \
0                    5  2015-07-02 00:00:00.0  00102CC07F4B02CA   
1                    6  2015-06-25 00:00:00.0  00102CD0FB2A023F   
2                   11  2015-04-02 00:00:00.0  00102CFED3C500D4   
3                   12  2015-06-25 00:00:00.0  00102C37122B0230   
4                   23  2015-03-02 00:00:00.0  00102C76082B0069

              orig_iss_dt            maturity_dt  pay_freq_cd  coupon  \
0   2015-07-02 00:00:00.0  2015-12-31 00:00:00.0          NaN   0.000   
1   2015-06-25 00:00:00.0  2015-12-24 00:00:00.0          NaN   0.000   
2   2015-04-02 00:00:00.0  2016-03-31 00:00:00.0          NaN   0.000   
3   2015-06-25 00:00:00.0  2016-06-23 00:00:00.0          NaN   0.000   
4   2015-03-02 00:00:00.0  2017-02-28 00:00:00.0            2   0.500


       closing_price cpn_type_cd  months_to_maturity_1  FACE_VALUE  
0       99.944389        FXDI                     5  24000101.6  
1       99.960889        FXDI                     6  24000366.4  
2       99.866806        FXDI                    11  25000267.5

Desired output Array: For example I need the array to look like this, if the months_to_maturity column of df has values 6,12,18:

array([[coupon     0     0      0], 
       [coupon   coupon  0      0], 
       [coupon   coupon coupon  0]])

Thank You