Last Updated : 29 Jun, 2021
Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Pandas Series.abs() method is used to get the absolute numeric value of each element in Series/DataFrame.
Syntax: Series.abs()
Parameters: No parameters
Returns: Return the Series or DataFrame containing the absolute value of each element.
Code #1:
# importing pandas module
import pandas as pd
# creating lists
lst = [2, -10.87, -3.14, 0.12]
lst2 = [-10.87 + 4j]
ser = pd.Series(lst)
ser1 = pd.Series(lst2)
# printing values explaining abs()
print(ser1.abs(), '\n\n', ser.abs())
Output:
0 11.582612 dtype: float64 0 2.00 1 10.87 2 3.14 3 0.12 dtype: float64
Code #2: Explaining use of abs() on specific row
# importing pandas module
import pandas as pd
df = pd.DataFrame({'Name': ['John', 'Hari', 'Peter', 'Loani'],
'Age': [31, 29, 57, 40],
'val': [98, 48, -80, -14]})
df['ope'] = (df.val - 87).abs()
df
Output:
Name Age val ope 0 John 31 98 11 1 Hari 29 48 39 2 Peter 57 -80 167 3 Loani 40 -14 101
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