Pandas Series: abs() function
Pandas absolute value of column
The abs() function is used to get a Series/DataFrame with absolute numeric value of each element.
This function only applies to elements that are all numeric.
Syntax:
Series.abs(self)
Parameters: No parameters
Returns: Series/DataFrame containing the absolute value of each element.
Notes: For complex inputs, 1.2 + 1j, the absolute value is √
Example - Absolute numeric values in a Series:
Python-Pandas Code:
import numpy as np
import pandas as pd
s = pd.Series([-2.8, 3, -4.44, 5])
s.abs()
Output:
0 2.80 1 3.00 2 4.44 3 5.00 dtype: float64
Example - Absolute numeric values in a Series with complex numbers:
Python-Pandas Code:
import numpy as np
import pandas as pd
s = pd.Series([2.2 + 1j])
s.abs()
Output:
0 2.416609 dtype: float64
Example - Absolute numeric values in a Series with a Timedelta element:
Python-Pandas Code:
import numpy as np
import pandas as pd
s = pd.Series([pd.Timedelta('2 days')])
s.abs()
Output:
0 2 days dtype: timedelta64[ns]
Example - Select rows with data closest to certain value using argsort:
Python-Pandas Code:
import numpy as np
import pandas as pd
df = pd.DataFrame({
'p': [2, 3, 4, 5],
'q': [10, 20, 30, 40],
'r': [200, 60, -40, -60]
})
df
Output:
p q r 0 2 10 200 1 3 20 60 2 4 30 -40 3 5 40 -60
Python-Pandas Code:
import numpy as np
import pandas as pd
df = pd.DataFrame({
'p': [2, 3, 4, 5],
'q': [10, 20, 30, 40],
'r': [200, 60, -40, -60]
})
df.loc[(df.r - 45).abs().argsort()]
Output:
p q r 1 3 20 60 2 4 30 -40 3 5 40 -60 0 2 10 200
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https://w3resource.com/pandas/series/series-abs.php
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