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# How to count the valid elements from a series object in Pandas?

The count() method in the pandas series is used to count the valid elements of a series object. This means it counts the number of non-null values of a series object.

This method takes only one parameter “level”, which takes an integer value for selecting the particular level of a MultiIndex object, by default the parameter value is None.

The output for this counting method is an integer value, which indicates the number of non-null values of a given series.

## Example 1

import pandas as pd import numpy as np #create a pandas Series series = pd.Series([18,23,44,32,np.nan,76,34,1,4,np.nan,21,34,90]) print(series) print("apply count method: ",series.count())

## Explanation

In this following example, we have created a pandas Series with a python list of integer values. And we applied the count() method to get the number of valid elements of the series.

## Output

0 18.0 1 23.0 2 44.0 3 32.0 4 NaN 5 76.0 6 34.0 7 1.0 8 4.0 9 NaN 10 21.0 11 34.0 12 90.0 dtype: float64 apply count method: 11

The original series object has two NaN values and there are a total of 13 elements present in the series. The count() method only counts the valid elements of the series so that the output of the following example is 11.

## Example 2

import pandas as pd import numpy as np #create a pandas Series series = pd.Series([98,2,32,45,56]) print(series) print("apply count method: ",series.count())

## Explanation

Initially, we have created a pandas Series with a python list of integer values. After that, we calculated the total number of valid elements of the series by using the series.count() method.

## Output

0 98 1 2 2 32 3 45 4 56 dtype: int64 apply count method: 5

For the following example, the number of valid elements is 5.

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