Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
dataframe.count() is used to count the no. of non-NA/null observations across the given axis. It works with non-floating type data as well.
Syntax: DataFrame.count(axis=0, level=None, numeric_only=False)
axis : 0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise
level : If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a DataFrame
numeric_only : Include only float, int, boolean data
Returns: count : Series (or DataFrame if level specified)
Example #1: Use
count() function to find the number of non-NA/null value across the row axis.
Now find the count of non-NA value across the row axis
Example #2: Use
count() function to find the number of non-NA/null value across the column.
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