**Skewness** refers to distortion or asymmetry in a symmetrical bell curve, or normal distribution, in a set of data. If the curve is shifted to the left or to the right, it is said to be skewed. Skewness can be quantified as a representation of the extent to which a given distribution varies from a normal distribution.

Use **df.skew()** or **df['column1'].skew()** to calculate skewness in pandas.

**Kurtosis** is a statistical measure that defines how heavily the tails of distribution differ from the tails of a normal distribution. In other words, kurtosis identifies whether the tails of a given distribution contain extreme values.

Use **df.kurtosis()** or **df['column1'].kurtosis()** to calculate kurtosis in pandas.

The ideal value for both is close to 0 for a normal distribution when calculated using pandas.

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