Create one row with values from table with data in diagonal only

I have the following table in pandas-

>>>index1   index2   index3   index4   index5   index6   index7
0   sig      null    null     null     null     null     null
1   null      sig     null     null     null     null     null
2   null      null    sig      null     null     null     null
3   null      null    null     sig      null     null     null
4   null      null    null     null     no sig   null     null
5   null      null    null     null     null     no sig   null
6   null      null    null     null     null     null     sig

I would like to get rid of the reduce the null values and to have the data in one row like this:

>>>index1   index2   index3   index4   index5   index6   index7
0   sig      sig     sig      sig      no sig   no sig   sig

It's important to say that I get the first table with the null data by if statemnt; I have calculated statistic test for each index and based on the p value, I give each index value of sig or no sig, using append:

for i in indices:
    stat, p = friedmanchisquare(df[1][i],df[2][i],df[3][i],df[4][i],df[5][i])
    #print(i,p)
    if p<0.05:
        friedman=friedman.append({i:'sig'},ignore_index=True)
    else:
        friedman=friedman.append({i:'no sig'},ignore_index=True)

So I believe that the append creates the big table with the many null values.

My end goal: to get the one row table, either in the of loop stage (e.g to use something else than append?) or to "fix" the big table after to get the one row