Floor or ceiling of a pandas series in python?

Question

I have a pandas series series. If I want to get the element-wise floor or ceiling, is there a built in method or do I have to write the function and use apply?

Answer 1

clip_lower / clip_upper

With Pandas, you can set a floor via clip_lower or ceiling via clip_upper:

s = pd.Series([-1, 0, -5, 3])

print(s.clip_lower(0))
# 0    0
# 1    0
# 2    0
# 3    3
# dtype: int64

print(s.clip_upper(0))
# 0   -1
# 1    0
# 2   -5
# 3    0
# dtype: int64

clip

pd.Series.clip supports more generalised functionality, e.g. applying and flooring a ceiling simultaneously, e.g. s.clip(-1, 1).

Answer 2

UPDATE: THIS ANSWER IS WRONG, DO NOT DO THIS

Explanation: using Series.apply() with a native vectorized Numpy function makes no sense in most cases as it will run the Numpy function in a Python loop, leading to much worse performance. You'd be much better off using np.floor(series) directly, as suggested by several other answers.

You could do something like this using NumPy's floor, for instance, with a dataframe:

floored_data = data.apply(np.floor)

Can't test it right now but an actual and working solution might not be far from it.

Answer 3

You can use NumPy's built in methods to do this: np.ceil(series) or np.floor(series).

Both return a Series object (not an array) so the index information is preserved.

Answer 4

I am the OP, but I tried this and it worked:

np.floor(series)