5.16. Series Arithmetic

5.16.1. SetUp

>>> import pandas as pd
>>>
>>>
>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data
0    0.0
1    1.0
2    2.0
3    NaN
4    4.0
5    5.0
dtype: float64

5.16.2. Vectorized Operations

  • s + 2, s.add(2)

  • s - 2, s.sub(2), s.subtract(2)

  • s * 2, s.mul(2), s.multiply(2)

  • s ** 2, s.pow(2)

  • s ** (1/2), s.pow(1/2)

  • s / 2, s.div(2), s.divide()

  • s // 2, s.truediv(2)

  • s % 2, s.mod(2)

  • divmod(s, 2), s.divmod(2)

5.16.3. Add

  • Series + 100

  • Series.add(100)

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data + 100
0    100.0
1    101.0
2    102.0
3      NaN
4    104.0
5    105.0
dtype: float64

5.16.4. Subtract

  • Series - 100

  • Series.sub(100)

  • Series.subtract(100)

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data - 100
0   -100.0
1    -99.0
2    -98.0
3      NaN
4    -96.0
5    -95.0
dtype: float64

5.16.5. Multiply

  • Series * 100

  • Series.mul(100)

  • Series.multiply(100)

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data * 100
0      0.0
1    100.0
2    200.0
3      NaN
4    400.0
5    500.0
dtype: float64

5.16.6. Power

  • Series ** 2

  • Series.pow(2)

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data ** 2
0     0.0
1     1.0
2     4.0
3     NaN
4    16.0
5    25.0
dtype: float64

5.16.7. Root

  • Series ** (1/2)

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data ** (1/2)
0    0.000000
1    1.000000
2    1.414214
3         NaN
4    2.000000
5    2.236068
dtype: float64

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data ** (1/3)
0    0.000000
1    1.000000
2    1.259921
3         NaN
4    1.587401
5    1.709976
dtype: float64

5.16.8. True Division

  • Series / 100

  • Series.div(100)

  • Series.divide(100)

  • Series.truediv(100)

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data / 100
0    0.00
1    0.01
2    0.02
3     NaN
4    0.04
5    0.05
dtype: float64

5.16.9. Floor Div

  • Series // 2

  • Series.floordiv(2)

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data // 2
0    0.0
1    0.0
2    1.0
3    NaN
4    2.0
5    2.0
dtype: float64

5.16.10. Modulo

  • Series % 2

  • Series.mod(2)

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data % 2
0    0.0
1    1.0
2    0.0
3    NaN
4    0.0
5    1.0
dtype: float64

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data % 2 == 0
0     True
1    False
2     True
3    False
4     True
5    False
dtype: bool

5.16.11. Complex

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> (data+100) ** 2 / 3
0    3333.333333
1    3400.333333
2    3468.000000
3            NaN
4    3605.333333
5    3675.000000
dtype: float64

5.16.12. Fill Value

>>> data = pd.Series([0, 1, 2, None, 4, 5])
>>>
>>> data.add(10, fill_value=0)
0    10.0
1    11.0
2    12.0
3    10.0
4    14.0
5    15.0
dtype: float64

5.16.13. Assignments

# %% About
# - Name: Series Arithmetic
# - Difficulty: easy
# - Lines: 5
# - 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. Define variable `result` with result of
#    add 10 to each element of `DATA`
# 2. Do not use `.add()` method
# 3. Run doctests - all must succeed

# %% Polish
# 1. Zdefiniuj zmienną `result` z wynikiem
#    dodania 10 to każdego elementu z `DATA`
# 2. Nie używaj metody `.add()`
# 3. Uruchom doctesty - wszystkie muszą się powieść

# %% Expected
# >>> result
# 0    11.0
# 1    12.0
# 2    13.0
# 3    14.0
# 4    15.0
# dtype: float64

# %% 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 pd.Series, \
'Variable `result` has an invalid type; expected: `pd.Series`.'

>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)

>>> result
0    11.0
1    12.0
2    13.0
3    14.0
4    15.0
dtype: float64
"""

# %% 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 pandas as pd

# %% Types
result: pd.Series

# %% Data
DATA = pd.Series([1.0, 2.0, 3.0, 4.0, 5.0])

# %% Result
result = ...


# %% About
# - Name: Series Arithmetic
# - Difficulty: easy
# - Lines: 5
# - 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. Define variable `result` with result of
#    add 10 to each element of `DATA`
# 2. Use `.add()` method
# 3. Run doctests - all must succeed

# %% Polish
# 1. Zdefiniuj zmienną `result` z wynikiem
#    dodania 10 to każdego elementu z `DATA`
# 2. Użyj metodę `.add()`
# 3. Uruchom doctesty - wszystkie muszą się powieść

# %% Expected
# >>> result
# 0    11.0
# 1    12.0
# 2     NaN
# 3    14.0
# 4    15.0
# dtype: float64

# %% Hints
# - `Series.add(fill_value)`

# %% 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 pd.Series, \
'Variable `result` has an invalid type; expected: `pd.Series`.'

>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)

>>> result
0    11.0
1    12.0
2     NaN
3    14.0
4    15.0
dtype: float64
"""

# %% 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 pandas as pd

# %% Types
result: pd.Series

# %% Data
DATA = pd.Series([1.0, 2.0, None, 4.0, 5.0])

# %% Result
result = ...


# %% About
# - Name: Series Arithmetic
# - Difficulty: easy
# - Lines: 5
# - 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. Define variable `result` with result of
#    add 10 to each element of `DATA`
#    if value is not-a-number then treat it as zero
# 2. Use `.add()` method
# 3. Run doctests - all must succeed

# %% Polish
# 1. Zdefiniuj zmienną `result` z wynikiem
#    dodania 10 to każdego elementu z `DATA`
#    jeżeli wartość nie jest liczbą, to potraktuj ją jak zero
# 2. Użyj metodę `.add()`
# 3. Uruchom doctesty - wszystkie muszą się powieść

# %% Expected
# >>> result
# 0    11.0
# 1    12.0
# 2    10.0
# 3    14.0
# 4    15.0
# dtype: float64

# %% Hints
# - `Series.add(fill_value)`

# %% 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 pd.Series, \
'Variable `result` has an invalid type; expected: `pd.Series`.'

>>> pd.set_option('display.max_columns', 50)
>>> pd.set_option('display.max_rows', 200)
>>> pd.set_option('display.width', 500)
>>> pd.set_option('display.memory_usage', 'deep')
>>> pd.set_option('display.precision', 4)

>>> result
0    11.0
1    12.0
2    10.0
3    14.0
4    15.0
dtype: float64
"""

# %% 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 pandas as pd

# %% Types
result: pd.Series

# %% Data
DATA = pd.Series([1.0, 2.0, None, 4.0, 5.0])

# %% Result
result = ...