pandas.DataFrame.max¶

Return the maximum of the values for the requested axis.

If you want the index of the maximum, use idxmax. This is the equivalent of the numpy.ndarray method argmax.

param axis

{index (0), columns (1)}: Axis for the function to be applied on.

param skipna

bool, default True: Exclude NA/null values when computing the result.

param level

int or level name, default None: If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series.

param numeric_only

bool, default None: Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series. **kwargs Additional keyword arguments to be passed to the function.

return

Series or DataFrame (if level specified)

Limitations¶

Parameters axis, level and numeric_only are unsupported.

Examples¶

Return the maximum of the values for the columns.¶

import pandas as pd
import numpy as np
from numba import njit


@njit
def dataframe_max():
    df = pd.DataFrame({"A": [.2, .0, .6, .2],
                       "B": [2, 0, 6, 2],
                       "C": [-1, np.nan, 1, np.inf]})

    return df.max()


print(dataframe_max())

$ python ./dataframe/dataframe_max.py
A    0.6
B    6.0
C    inf
dtype: float64

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pandas.DataFrame.max¶

Limitations¶

Examples¶