return max value from pandas dataframe as a whole, not based on column or rows

The max of all the values in the DataFrame can be obtained using df.to_numpy().max(), or for pandas < 0.24.0 we use df.values.max():

In [10]: df.to_numpy().max()
Out[10]: 'f'

The max is f rather than 43.0 since, in CPython2,

In [11]: 'f' > 43.0
Out[11]: True

In CPython2, Objects of different types ... are ordered by their type names. So any str compares as greater than any int since 'str' > 'int'.

In Python3, comparison of strings and ints raises a TypeError.

To find the max value in the numeric columns only, use

df.select_dtypes(include=[np.number]).max()

Hi the simplest answer is the following. Answer:

df.max().max()

Explanation:
series = df.max() give you a Series containing the maximum values for each column.
Therefore series.max()gives you the maximum for the whole dataframe.

:) best answers are usually the simplest

An alternative way:

df.melt().value.max()

Essentially melt() transforms the DataFrame into one long column.