Assertion. In a dataset, there can be missing values that cannot contribute to any computation.

Reason. In a dataset, NULL, NaN or None are considered the missing values.

1. Both A and R are true and R is the correct explanation of A.
2. Both A and R are true but R is not the correct explanation of A.
3. A is true but R is false.
4. A is false but R is true.

Assertion (A). The output of addition of two series will be NaN, if one of the elements or both the elements have no value(s).

Reason (R). While performing mathematical operations on a series, by default all missing values are filled in with 0.

1. Both A and R are true and R is the correct explanation of A.
2. Both A and R are true but R is not the correct explanation of A.
3. A is true but R is false.
4. A is false but R is true.

Name the function to iterate over a DataFrame vertically.

Write equivalent expressions for the given functions :

(i) A.add(B)

(ii) B.add(A)

(iii) A.sub(B)

(iv) B.sub(A)

(v) A.rsub(B)

(vi) B.mul(A)

(vii) A.rdiv(B)

(viii) B.div(A)

(ix) B.rdiv(A)

(x) A.div(B)