Pandas Series.cummax() is used to find the cumulative maximum of a series. At the cumulative maximum, the length of the returned series is the same as the input series, and each element is equal to the greater one between the current element and the previous element.
Syntax: Series.cummax (axis = None, skipna = True)
Parameters:
axis: 0 or ’index’ for row wise operation and 1 or ’columns ’for column wise operation.
skipna: Skips NaN addition for elements after the very next one if True.Return type: Series
Example # 1:
This example creates a series from a Python list. The list also contains a Null value, and the skipna parameter remains the default, which is True.
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Output:
0 3.0 1 4.0 2 NaN 3 7.0 4 7.0 5 7.0 dtype: float64
Explanation: Cummax — it is a comparison of the current value with the previous value. The first element is always the first of the caller.
3 4 (4" 3) NaN (Since NaN cannot be compared to integer values) 7 (7" 4) 7 (7" 2) 7 (7" 0)
Example # 2: saving skipna = False
This example creates a series in the same way as above example. But the skipna parameter remains False. Therefore, NULL values will not be ignored and they will be compared each time they are found.
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Exit:
0 9.0 1 9.0 2 33.0 3 NaN 4 NaN 5 NaN 6 NaN 7 NaN dtype: float64
Explanation: How and in the above example, the maximum current and previous values were kept at each position until NaN appeared. Since NaN is NaN compared to anything, and skipna remains False, the cumulative maximum after it appears is NaN due to the comparison of all values to NaN.
