My problem is this, I want to replace a list of questions in the first row of a square null matrix leaving the first zero, that is, if the matrix is m rows by n columns, I would like to insert the list of questions to from the value [m, n] = [0,1]. Where each question in the list occupies a place in that row of the matrix. Likewise, I would like to replace those same questions in the first column, leaving the first value as zero, starting with [m, n] = [1,0]. The code that I am using at the moment is the following:

```
numero_preguntas = (len(df1_number_rf.columns))
preguntas = np.array(df1_number_rf.columns.values)
matriz = np.zeros((numero_preguntas+1,numero_preguntas+1),)
```

I mean, I'd like this:

```
[[0,0,0,0]
[0,0,0,0]
[0,0,0,0]
[0,0,0,0]]
```

Based on a list of questions:

```
preguntas = [pregunta1,pregunta2,pregunta3]
```

Be transformed into this:

```
[[0,pregunta1,pregunta2,pregunta3]
[pregunta1,0,0,0]
[pregunta2,0,0,0]
[pregunta3,0,0,0]]
```

Later I have values in a matrix that I want to insert in specific values of the previous one. For example:

```
[[pregunta1,0.8]
[pregunta3,0.2]]
```

I would like to insert them in the column of question 2 in the rows that correspond, in such a way that it looks like this:

```
[[0,pregunta1,pregunta2,pregunta3]
[pregunta1,0,0.8,0]
[pregunta2,0,0,0]
[pregunta3,0,0.2,0]]
```

This last thing I need to do because I am trying to elaborate a matrix with the values of the importance obtained using random forest of each one of the questions. That is, question 2 would be the variable to be classified in a decision tree and questions 1 and 3 would become the classifiers.