如何在没有 NaN 的情况下使用 pandas 合并不同的列？

Question

I am trying to merge different columns and I used code as follows:

r1= len(data['Answer_h1_Happy'])
c1 = len(list(data))

ndata1 = list(data.Answer_h1_Happy) + list(data.Answer_h1_Happy) + 
    list(data.Answer_h1_Happy) + list(data.Answer_h1_Happy) \
    + list(data.Answer_h1_Happy) + list(data.Answer_h1_Happy) + 
    list(data.Answer_h1_Happy) + list(data.Answer_h1_Happy) \
    + list(data.Answer_h1_Happy) + list(data.Answer_h1_Happy)
r1 = len(ndata1) - r1
t1 = r1 * c1
dfnan1 = pd.DataFrame(np.reshape([np.nan]*t1, (r1,c1)), columns=list(data))
data= data.append(dfnan1)
data['Happy'] = ndata1

When I try to merge only this, it works well. But when I try to merge other columns, because of 'NaN' the column get thousands of rows.

For example, the original table looks like this: original table

And after 1st merge, NaNs are created in black rows. after 1st merge

When I try to merge other column, it gets twice longer than other. after 2nd merge

Is there any way I can merge without Nan? This is what I want

Answer 1

I move combined columns to another data frame. After that code I add,

df['Input_image_url'] = data.pop('Input_image_url').reset_index(drop=True)

and remove all NaN by,

update_data = data.drop(df.index[13:130])

And it works!!