The message that you are getting is not for the default Exception of Python:
For a fresh python list, IndexError is thrown only on index not being in range (even docs say so).
>>> l = []
>>> l[1]
IndexError: list index out of range
If we try passing multiple items to list, or some other value, we get the TypeError:
>>> l[1, 2]
TypeError: list indices must be integers, not tuple
>>> l[float('NaN')]
TypeError: list indices must be integers, not float
However, here, you seem to be using matplotlib that internally uses numpy for handling arrays. On digging deeper through the codebase for numpy, we see:
static NPY_INLINE npy_intp
unpack_tuple(PyTupleObject *index, PyObject **result, npy_intp result_n)
{
npy_intp n, i;
n = PyTuple_GET_SIZE(index);
if (n > result_n) {
PyErr_SetString(PyExc_IndexError,
"too many indices for array");
return -1;
}
for (i = 0; i < n; i++) {
result[i] = PyTuple_GET_ITEM(index, i);
Py_INCREF(result[i]);
}
return n;
}
where, the unpack method will throw an error if it the size of the index is greater than that of the results.
So, Unlike Python which raises a TypeError on incorrect Indexes, Numpy raises the IndexError because it supports multidimensional arrays.