How to convert list of `numpy.datetime64` to `matplotlib.dates`?

Question

Here is my simple object:

[numpy.datetime64('2017-01-03T00:00:00.000000000'),
 numpy.datetime64('2017-01-04T00:00:00.000000000'),
 numpy.datetime64('2017-01-05T00:00:00.000000000'),
 numpy.datetime64('2017-01-06T00:00:00.000000000'),
 numpy.datetime64('2017-01-09T00:00:00.000000000'),
 numpy.datetime64('2017-01-10T00:00:00.000000000'),
 numpy.datetime64('2017-01-11T00:00:00.000000000'),
 numpy.datetime64('2017-01-12T00:00:00.000000000'),
 numpy.datetime64('2017-01-13T00:00:00.000000000'),
 numpy.datetime64('2017-01-16T00:00:00.000000000'),
 numpy.datetime64('2017-01-17T00:00:00.000000000'),
 numpy.datetime64('2017-01-18T00:00:00.000000000'),
 numpy.datetime64('2017-01-19T00:00:00.000000000'),
 numpy.datetime64('2017-01-20T00:00:00.000000000'),
 numpy.datetime64('2017-01-23T00:00:00.000000000'),
 numpy.datetime64('2017-01-24T00:00:00.000000000'),
 numpy.datetime64('2017-01-25T00:00:00.000000000'),
 numpy.datetime64('2017-01-26T00:00:00.000000000'),
 numpy.datetime64('2017-01-27T00:00:00.000000000'),
 numpy.datetime64('2017-02-01T00:00:00.000000000')]

instead of using a loop an empty list convert one by one, is there any shortcuts for that? Thanks.

Hmm, list comprehensions / generator expressions? But they still process items one by one. — user3159253
– user3159253, Commented Sep 23, 2017 at 5:14

ImportanceOfBeingErnest · Accepted Answer · 2017-09-23 11:24:23Z

My favourite solution here would be one that seems a bit hidden in this thread: Converting between datetime, Timestamp and datetime64, which is to use tolist(). Because tolist() returns different types, depending on the array type, a conversion to ms is needed to get datetime objects. datetime objects can be directly plotted with matplotlib, or one can apply matplotlib.dates.date2num() on them.

So if a is the numpy array as above,

x = a.astype("M8[ms]").tolist()

results in a list of datetime objects.

Complete example:

import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime
import matplotlib.dates as mdates

a = np.array([np.datetime64('2017-01-03T00:00:00.000000000'),
     np.datetime64('2017-01-04T00:00:00.000000000'),
     np.datetime64('2017-01-05T00:00:00.000000000'),
     np.datetime64('2017-01-06T00:00:00.000000000'),
     np.datetime64('2017-01-09T00:00:00.000000000'),
     np.datetime64('2017-01-10T00:00:00.000000000'),
     np.datetime64('2017-01-11T00:00:00.000000000'),
     np.datetime64('2017-01-12T00:00:00.000000000'),
     np.datetime64('2017-01-13T00:00:00.000000000'),
     np.datetime64('2017-01-16T00:00:00.000000000'),
     np.datetime64('2017-01-17T00:00:00.000000000'),
     np.datetime64('2017-01-18T00:00:00.000000000'),
     np.datetime64('2017-01-19T00:00:00.000000000'),
     np.datetime64('2017-01-20T00:00:00.000000000'),
     np.datetime64('2017-01-23T00:00:00.000000000'),
     np.datetime64('2017-01-24T00:00:00.000000000'),
     np.datetime64('2017-01-25T00:00:00.000000000'),
     np.datetime64('2017-01-26T00:00:00.000000000'),
     np.datetime64('2017-01-27T00:00:00.000000000'),
     np.datetime64('2017-02-01T00:00:00.000000000')])

x = a.astype("M8[ms]").tolist()
y = np.random.rand(len(a))

plt.plot(x, y, color="limegreen")

plt.show()

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