- Skewness is a measure of asymmetry of a distribution. Another measure that describes the shape of a distribution is kurtosis.
- In a normal distribution, the mean divides the curve symmetrically into two equal parts at the median and the value of skewness is zero.
- When a distribution is asymmetrical the tail of the distribution is skewed to one side-to the right or to the left.
- When the value of the skewness is negative, the tail of the distribution is longer towards the left hand side of the curve.
- When the value of the skewness is positive, the tail of the distribution is longer towards the right hand side of the curve.
skewness() function in pandas:
- The DataFrame class of pandas has a method skew() that computes the skewness of the data present in a given axis of the DataFrame object.
- Skewness is computed for each row or each column of the data present in the DataFrame object.
import pandas as pd
dataVal = [(10,20,30,40,50,60,70),
dataFrame = pd.DataFrame(data=dataVal);
skewValue = dataFrame.skew(axis=1)
0 1 2 3 4 5 6
0 10 20 30 40 50 60 70
1 10 10 40 40 50 60 70
2 10 20 30 50 50 60 80
- A skewness value of 0 in the output denotes a symmetrical distribution of values in row 1.
- A negative skewness value in the output indicates an asymmetry in the distribution corresponding to row 2 and the tail is larger towards the left hand side of the distribution.
- A positive skewness value in the output indicates an asymmetry in the distribution corresponding to row 3 and the tail is larger towards the right hand side of the distribution.