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How could I convert the values of column 'count' to absolute value?
A summary of my dataframe this:
datetime count
0 2011-01-20 00:00:00 14.565996
1 2011-01-20 01:00:00 10.204177
2 2011-01-20 02:00:00 -1.261569
3 2011-01-20 03:00:00 1.938322
4 2011-01-20 04:00:00 1.938322
5 2011-01-20 05:00:00 -5.963259
6 2011-01-20 06:00:00 73.711525
298
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.
Python comes built-in with a function for calculating absolute values. This function is called the abs() function. The function takes a single parameter, either an integer, a floating point value, or a complex number. The function returns the absolute value of whatever number is passed into it.
Python abs() Function The abs() function returns the absolute value of the specified number.
To calculate the mean of whole columns in the DataFrame, use pandas. Series. mean() with a list of DataFrame columns. You can also get the mean for all numeric columns using DataFrame.
Use pandas.DataFrame.abs().
import pandas as pd
df = pd.DataFrame(data={'count':[1, -1, 2, -2, 3, -3]})
df['count'] = df['count'].abs()
print(df)
count
#0 1
#1 1
#2 2
#3 2
#4 3
#5 3
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