# Return the maximum of an array along axis 0 or maximum ignoring any NaNs in Python

To return the maximum of an array along axis 0 in Python, we can use the `numpy.amax()` function. Here's an example:

``````import numpy as np

arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
max_arr = np.amax(arr, axis=0)

print(max_arr)
``````

Output:

``````[7 8 9]
``````

Here, we first import the `numpy` library and create a 2D array `arr`. We then use the `numpy.amax()` function to find the maximum value along axis 0 (i.e., column-wise). The resulting array `max_arr` contains the maximum value of each column.

To return the maximum ignoring any NaNs in Python, we can use the `numpy.nanmax()` function. Here's an example:

``````import numpy as np

arr = np.array([1, 2, np.nan, 4, 5])
max_arr = np.nanmax(arr)

print(max_arr)
``````

Output:

``````5.0
``````

Here, we first import the `numpy` library and create a 1D array `arr` with a NaN value. We then use the `numpy.nanmax()` function to find the maximum value ignoring any NaNs. The resulting value `max_arr` is 5.0, which is the maximum value in the array after ignoring the NaN value. 