Pandas Series: sub() function
Subtraction of series and other in Pandas
The sub() function is used to get subtraction of series and other, element-wise (binary operator sub).
Equivalent to series - other, but with support to substitute a fill_value for missing data in one of the inputs.
Syntax:
Series.sub(self, other, level=None, fill_value=None, axis=0)
Parameters:
Name | Description | Type/Default Value | Required / Optional |
---|---|---|---|
other | Series or scalar value | Required | |
fill_value | Fill existing missing (NaN) values, and any new element needed for successful Series alignment, with this value before computation. If data in both corresponding Series locations is missing the result will be missing. | None or float value Default Value: None (NaN) |
Required |
level | Broadcast across a level, matching Index values on the passed MultiIndex level. | int or name | Required |
Returns: Series
The result of the operation.
Example:
Python-Pandas Code:
import numpy as np
import pandas as pd
x = pd.Series([2, 1, 2, np.nan], index=['p', 'q', 'r', 's'])
x
Output:
p 2.0 q 1.0 r 2.0 s NaN dtype: float64
Python-Pandas Code:
import numpy as np
import pandas as pd
y = pd.Series([1, np.nan, 2, 1], index=['p', 'q', 's', 't'])
y
Output:
p 1.0 q NaN s 2.0 t 1.0 dtype: float64
Python-Pandas Code:
import numpy as np
import pandas as pd
x = pd.Series([2, 1, 2, np.nan], index=['p', 'q', 'r', 's'])
y = pd.Series([1, np.nan, 2, 1], index=['p', 'q', 's', 't'])
x.subtract(y, fill_value=0)
Output:
p 1.0 q 1.0 r 2.0 s -2.0 t -1.0 dtype: float64
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