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# Python | Pandas Series.skew()

• Last Updated : 05 Feb, 2019

Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.

Pandas` Series.skew()` function return unbiased skew over requested axis Normalized by N-1. Skewness is asymmetry in a statistical distribution, in which the curve appears distorted or skewed either to the left or to the right.

Syntax: Series.skew(axis=None, skipna=None, level=None, numeric_only=None, **kwargs)

Parameter :
axis : Axis for the function to be applied on.
skipna : Exclude NA/null values when computing the result.
level : If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar.
numeric_only : Include only float, int, boolean columns.
**kwargs : Additional keyword arguments to be passed to the function.

Returns : skew : scalar or Series (if level specified)

Example #1 : Use `Series.skew()` function to find the skewness in the data of the given Series object.

 `# importing pandas as pd``import` `pandas as pd`` ` `# Creating the Series``sr ``=` `pd.Series([``100``, ``25``, ``32``, ``118``, ``24``, ``65``])`` ` `# Print the series``print``(sr)`

Output : Now we will use `Series.skew()` function to find the skewness in the data.

 `# find skewness``sr.skew()`

Output : As we can see in the output, `Series.skew()` function has successfully calculated the skewness in the data of the given Series object.

Example #2 : Use `Series.skew()` function to find the skewness in the data of the given Series object. We have some missing values in our series object, so skip those missing values.

 `# importing pandas as pd``import` `pandas as pd`` ` `# Creating the Series``sr ``=` `pd.Series([``19.5``, ``16.8``, ``None``, ``22.78``, ``None``, ``20.124``, ``None``, ``18.1002``, ``None``])`` ` `# Print the series``print``(sr)`

Output : Now we will use `Series.skew()` function to find the skewness in the data.

 `# find skewness``sr.skew(skipna ``=` `True``)`

Output : As we can see in the output, `Series.skew()` function has successfully calculated the skewness in the data of the given Series object. Missing values has been skipped while calculating the skewness in the given data.

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