In a column with categorical or distinct values, it is important to know the number of occurrences of each value. In this short how-to article, we will learn how to perform this task in Pandas and PySpark DataFrames.
The value_counts function returns the distinct values in a column along with their number of occurrences.
df["Color"].value_counts()Missing values are ignored by default. If we know that there are missing values in a column, it is best to count them as well. The dropna parameter is set to False to include the missing values.
df["Color"].value_counts(dropna=False)To count the number of occurrences of distinct values in a column, we use the groupby and count functions. The rows are grouped by the column of interest and then the count function is applied.
df.groupby("name").count().show()The missing values are included in this calculation.
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