• np.ceil(n) - rounds n up to nearest int

  • np.floor(n) - rounds n down to nearest int

  • np.rint(n) - rounds n to nearest int

  • np.round(n, [prec]) - rounds n with precision prec

  • np.clip(low, high) - trims values to low and high

8.1.1. Floor

>>> import numpy as np
>>>
>>>
>>> a = np.array([1., 1.00000001, 1.99999999])
>>>
>>> np.floor(a)
array([1., 1., 1.])

8.1.2. Ceil

>>> import numpy as np
>>>
>>>
>>> a = np.array([1., 1.00000001, 1.99999999])
>>>
>>> np.ceil(a)
array([1., 2., 2.])

8.1.3. Rint

  • Round elements of the array to the nearest integer.

>>> import numpy as np
>>>
>>>
>>> a = np.array([1., 1.00000001, 1.99999999])
>>>
>>> np.rint(a)
array([1., 1., 2.])

8.1.4. Round

  • Round elements of the array to the precision

>>> import numpy as np
>>>
>>>
>>> a = np.array([1.23, 1.456, 1.789])
>>>
>>>
>>> np.round(a)
array([1., 1., 2.])
>>>
>>> np.round(a, 1)
array([1.2, 1.5, 1.8])
>>>
>>> np.round(a, 2)
array([1.23, 1.46, 1.79])
>>>
>>> np.round(a, 3)
array([1.23 , 1.456, 1.789])

>>> import numpy as np
>>>
>>>
>>> data = 3.1415
>>>
>>> np.round(data, 2)
np.float64(3.14)

>>> import numpy as np
>>>
>>>
>>> data = np.array([3.1415, 2.7182])
>>>
>>> np.round(data, 2)
array([3.14, 2.72])

>>> import numpy as np
>>>
>>>
>>> data = np.array([[3.1415, 2.7182],
...                  [3.1415, 2.7182]])
>>>
>>> np.round(data, 2)
array([[3.14, 2.72],
       [3.14, 2.72]])

8.1.5. Clip

  • Increase smaller values to lower bound

  • Decrease higher values to upper bound

>>> import numpy as np
>>>
>>>
>>> a = np.array([1, 2, 3])
>>>
>>> a.clip(2, 5)
array([2, 2, 3])

>>> import numpy as np
>>>
>>>
>>> a = np.array([[1, 2, 3],
...               [4, 5, 6]])
>>>
>>> a.clip(2, 5)
array([[2, 2, 3],
       [4, 5, 5]])

>>> import numpy as np
>>>
>>>
>>> a = np.array([[-2, -1, 0],
...               [0, 1, 2]])
>>>
>>> a.astype(bool)
array([[ True,  True, False],
       [False,  True,  True]])
>>>
>>> a.clip(0, 1)
array([[0, 0, 0],
       [0, 1, 1]])
>>>
>>> a.clip(0, 1).astype(bool)
array([[False, False, False],
       [False,  True,  True]])

8.1.6. Assignments

# %% About
# - Name: Numpy Round Rint
# - Difficulty: easy
# - Lines: 1
# - Minutes: 3

# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author

# %% English
# 1. Round values to integers
# 2. Convert data type to `np.int8`
# 3. Run doctests - all must succeed

# %% Polish
# 1. Zaokrąglij wartości do pełnych liczb całkowitych
# 2. Przekonwertuj typ danych do `np.int8`
# 3. Uruchom doctesty - wszystkie muszą się powieść

# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0

>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'

>>> assert 'result' in globals(), \
'Variable `result` is not defined; assign result of your program to it.'

>>> assert result is not Ellipsis, \
'Variable `result` has an invalid value; assign result of your program to it.'

>>> assert type(result) is np.ndarray, \
'Variable `result` has an invalid type; expected: `np.ndarray`.'

>>> result
array([1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1],
      dtype=int8)
"""

# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`

# %% Imports
import numpy as np

# %% Types
result: np.ndarray

# %% Data
DATA = np.array([0.5488135 , 0.71518937, 0.60276338, 0.54488318, 0.4236548 ,
                 0.64589411, 0.43758721, 0.891773  , 0.96366276, 0.38344152,
                 0.79172504, 0.52889492, 0.56804456, 0.92559664, 0.07103606,
                 0.0871293 , 0.0202184 , 0.83261985, 0.77815675, 0.87001215,
                 0.97861834])

# %% Result
result = ...


# %% About
# - Name: Numpy Round Floor and Ceil
# - Difficulty: medium
# - Lines: 3
# - Minutes: 3

# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author

# %% English
# 1. Ceil round `data` values and assign to `result1`
# 2. Floor round `data` values and assign to `result2`
# 3. Round `data` values and assign to `result3`
# 4. Run doctests - all must succeed

# %% Polish
# 1. Zaokrąglij wartości `data` w górę (ceil) i przypisz do `result1`
# 2. Zaokrąglij wartości `data` w dół (floor) i przypisz do `result2`
# 3. Zaokrąglij wartości `data` i przypisz do `result3`
# 4. Uruchom doctesty - wszystkie muszą się powieść

# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0

>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'

>>> assert 'result1' in globals(), \
'Variable `result1` is not defined; assign result of your program to it.'

>>> assert result1 is not Ellipsis, \
'Variable `result1` has an invalid value; assign result of your program to it.'

>>> assert type(result1) is np.ndarray, \
'Variable `result1` has an invalid type; expected: `np.ndarray`.'

>>> assert 'result2' in globals(), \
'Variable `result2` is not defined; assign result of your program to it.'

>>> assert result2 is not Ellipsis, \
'Variable `result2` has an invalid value; assign result of your program to it.'

>>> assert type(result2) is np.ndarray, \
'Variable `result2` has an invalid type; expected: `np.ndarray`.'

>>> assert 'result3' in globals(), \
'Variable `result3` is not defined; assign result of your program to it.'

>>> assert result3 is not Ellipsis, \
'Variable `result3` has an invalid value; assign result of your program to it.'

>>> assert type(result3) is np.ndarray, \
'Variable `result3` has an invalid type; expected: `np.ndarray`.'

>>> result1
array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
       1., 1., 1., 1.])

>>> result2
array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
       0., 0., 0., 0.])

>>> result3
array([1., 1., 1., 1., 0., 1., 0., 1., 1., 0., 1., 1., 1., 1., 0., 0., 0.,
       1., 1., 1., 1.])
"""

# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`

# %% Imports
import numpy as np

# %% Types
result1: np.ndarray
result2: np.ndarray
result3: np.ndarray

# %% Data
np.random.seed(0)

DATA = np.array([0.5488135 , 0.71518937, 0.60276338, 0.54488318, 0.4236548 ,
                 0.64589411, 0.43758721, 0.891773  , 0.96366276, 0.38344152,
                 0.79172504, 0.52889492, 0.56804456, 0.92559664, 0.07103606,
                 0.0871293 , 0.0202184 , 0.83261985, 0.77815675, 0.87001215,
                 0.97861834])

# %% Result
result1 = ...
result2 = ...
result3 = ...


# %% About
# - Name: Numpy Round Clip
# - Difficulty: medium
# - Lines: 2
# - Minutes: 5

# %% License
# - Copyright 2025, Matt Harasymczuk <matt@python3.info>
# - This code can be used only for learning by humans
# - This code cannot be used for teaching others
# - This code cannot be used for teaching LLMs and AI algorithms
# - This code cannot be used in commercial or proprietary products
# - This code cannot be distributed in any form
# - This code cannot be changed in any form outside of training course
# - This code cannot have its license changed
# - If you use this code in your product, you must open-source it under GPLv2
# - Exception can be granted only by the author

# %% English
# 1. Create `result: np.ndarray` copy of `DATA`
# 2. Clip numbers only in first column to 50 (inclusive) to 80 (exclusive)
# 3. Print `result`
# 4. Run doctests - all must succeed

# %% Polish
# 1. Stwórz `result: np.ndarray` z kopią danych z `DATA`
# 2. Przytnij liczby w pierwszej kolumnie od 50 (włącznie) do 80 (rozłącznie)
# 3. Wypisz `result`
# 4. Uruchom doctesty - wszystkie muszą się powieść

# %% Hints
# - `result[:, 0]`

# %% Doctests
"""
>>> import sys; sys.tracebacklimit = 0

>>> assert sys.version_info >= (3, 9), \
'Python has an is invalid version; expected: `3.9` or newer.'

>>> assert 'result' in globals(), \
'Variable `result` is not defined; assign result of your program to it.'

>>> assert result is not Ellipsis, \
'Variable `result` has an invalid value; assign result of your program to it.'

>>> assert type(result) is np.ndarray, \
'Variable `result` has an invalid type; expected: `np.ndarray`.'

>>> result
array([[50, 47, 64],
       [67, 67,  9],
       [80, 21, 36],
       [80, 70, 88],
       [80, 12, 58],
       [65, 39, 87],
       [50, 88, 81]])
"""

# %% Run
# - PyCharm: right-click in the editor and `Run Doctest in ...`
# - PyCharm: keyboard shortcut `Control + Shift + F10`
# - Terminal: `python -m doctest -f -v myfile.py`

# %% Imports
import numpy as np

# %% Types
result: np.ndarray

# %% Data
DATA = np.array([[44, 47, 64],
                 [67, 67,  9],
                 [83, 21, 36],
                 [87, 70, 88],
                 [88, 12, 58],
                 [65, 39, 87],
                 [46, 88, 81]])

# %% Result
result = ...