is_datetimelike_v_numeric(a, b)

Parameters

a : array-like, scalar

The first object to check.

b : array-like, scalar

The second object to check.

Returns

boolean

Whether we return a comparing a datetime-like to a numeric object.

Check if we are comparing a datetime-like object to a numeric object. By "numeric," we mean an object that is either of an int or float dtype.

Examples

This example is valid syntax, but we were not able to check execution

>>> from datetime import datetime
... dt = np.datetime64(datetime(2017, 1, 1))
>>>

This example is valid syntax, but we were not able to check execution

>>> is_datetimelike_v_numeric(1, 1)
False

This example is valid syntax, but we were not able to check execution

>>> is_datetimelike_v_numeric(dt, dt)
False

This example is valid syntax, but we were not able to check execution

>>> is_datetimelike_v_numeric(1, dt)
True

This example is valid syntax, but we were not able to check execution

>>> is_datetimelike_v_numeric(dt, 1)  # symmetric check
True

This example is valid syntax, but we were not able to check execution

>>> is_datetimelike_v_numeric(np.array([dt]), 1)
True

This example is valid syntax, but we were not able to check execution

>>> is_datetimelike_v_numeric(np.array([1]), dt)
True

This example is valid syntax, but we were not able to check execution

>>> is_datetimelike_v_numeric(np.array([dt]), np.array([1]))
True

This example is valid syntax, but we were not able to check execution

>>> is_datetimelike_v_numeric(np.array([1]), np.array([2]))
False

This example is valid syntax, but we were not able to check execution

>>> is_datetimelike_v_numeric(np.array([dt]), np.array([dt]))
False

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

pandas.core.dtypes.common.is_datetimelike_v_numeric

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