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.count() function return the count of non-NA/null observations in the given Series object.
Syntax: Series.count(level=None)
Parameter :
level : If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a smaller SeriesReturns : nobs : int or Series (if level specified)
Example #1: Use Series.count() function to find the count of non-missing values in the given series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([80, 25, 3, 25, 24, 6]) # Create the Index index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp'] # set the index sr.index = index_ # Print the series print(sr) |
Output :
Now we will use Series.count() function to find the count of non-missing values in the given series object.
# find the count of non-missing values # in the given series object result = sr.count() # Print the result print(result) |
Output :
As we can see in the output, the Series.count() function has successfully returned the count of non-missing values in the given series object.
Example #2 : Use Series.count() function to find the count of non-missing values in the given series object. The given series object contains some missing values.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([100, None, None, 18, 65, None, 32, 10, 5, 24, None]) # Create the Index index_ = pd.date_range('2010-10-09', periods = 11, freq ='M') # set the index sr.index = index_ # Print the series print(sr) |
Output :
Now we will use Series.count() function to find the count of non-missing values in the given series object.
# find the count of non-missing values # in the given series object result = sr.count() # Print the result print(result) |
Output :
As we can see in the output, the Series.count() function has successfully returned the count of non-missing values in the given series object.
