Assertion. A series object stores values of homogeneous types.

Reason. Even if values appear to be of different types, internally they are stored in a common datatype.

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. Arithmetic operations on two series objects take place on matching indexes.

Reason. Non-matching indexes are removed from the result of arithmetic operation on series objects.

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. While changing the values of a column in a dataframe, if the column does not exist, an error occurs.

Reason. If values are provided for a non-existing column in a dataframe, a new column is added with those 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. .loc() is a label based data selecting method to select a specific row(s) or column(s) which we want to select.

Reason. .iloc() can not be used with default indices if customized indices are provided.

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.