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Python | Pandas DataFrame.abs()

  • Last Updated : 16 Nov, 2018

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.

dataframe.abs() is one of the simplest pandas dataframe function. It returns an object with absolute value taken and it is only applicable to objects that are all numeric. It does not work with any Nan value either. abs() function can also be used with complex numbers to find their absolute value.

For complex numbers, the absolute value is defined as:

Syntax:  DataFrame.abs()
Returns: type of caller

For link to CSV file Used in Code, click here

Example #1: Replace team “Boston Celtics” with “Omega Warrior” in the nba.csv file






# importing pandas as pd
import pandas as pd
  
# Making data frame from the csv file
df = pd.read_csv("nba.csv")
  
# Printing the first 10 rows of the
# data frame for visualization
df[:10]

In order to find the absolute value, we also need to have negative values in the dataframe. So, let’s change some values to be negative for the demonstration purpose.




# This will set the Number column
# to be all negative.
df.Number = df.Number*(-1)

Output:

Now let’s use abs() function to find only the absolute value of the Number column.




# Applying abs() value on one column only
df.Number.abs()

Output:

 
Example #2: Applying abs() on a series with complex numbers.




# Importing pandas as pd
import pandas as pd
  
# Creating a series
ser = pd.Series([1.2 + 1j, 2 + 5j, 1 + 8j, 3.2 + 2j])
  
# let's print the values in ser
ser




# Using abs() function to find the
# absolute value of the complex numbers
absolute_values = s.abs()
  
# Print the absolute values of all complex numbers
absolute_values

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