Hướng dẫn maximum in dataframe python

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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.

Pandas dataframe.max[] function returns the maximum of the values in the given object. If the input is a series, the method will return a scalar which will be the maximum of the values in the series. If the input is a dataframe, then the method will return a series with maximum of values over the specified axis in the dataframe. By default the axis is the index axis.

Syntax: DataFrame.max[axis=None, skipna=None, level=None, numeric_only=None, **kwargs]

Parameters :
axis : {index [0], columns [1]}
skipna : Exclude NA/null values when computing the result
level : If the axis is a MultiIndex [hierarchical], count along a particular level, collapsing into a Series
numeric_only : Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.

Returns : max : Series or DataFrame [if level specified]

Example #1: Use max[] function to find the maximum value over the index axis.

import pandas as pd

df = pd.DataFrame[{"A":[12, 4, 5, 44, 1],

                   "B":[5, 2, 54, 3, 2],

                   "C":[20, 16, 7, 3, 8], 

                   "D":[14, 3, 17, 2, 6]}]

df

Let’s use the dataframe.max[] function to find the maximum value over the index axis

Output :

import pandas as pd

df = pd.DataFrame[{"A":[12, 4, 5, None, 1], 

                   "B":[7, 2, 54, 3, None],

                   "C":[20, 16, 11, 3, 8],

                   "D":[14, 3, None, 2, 6]}]

df.max[axis = 1, skipna = True]

Output :