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

Question

I am trying to get the max value from a panda dataframe as whole. I am not interested in what row or column it came from. I am just interested in a single max value within t

Answer 1

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.

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

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

Answer 2

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

Answer 3

For the max, check the previous answer... For the max of the values use e.g.:

val_cols = [c for c in df.columns if c.startswith('val')]
print df[val_cols].max()

Answer 4

Max can be found in these two steps:

maxForRow = allData.max(axis=0) #max for each row
globalMax = maxForRow.max(); #max across all rows

Answer 5

An alternative way:

df.melt().value.max()

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