new function to plot datetimes. Can pass multiple lists and labels to plot multiple datatypes

plotdatetimes.py

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import datetime
import random

import matplotlib.ticker as mticker

from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()


# Generate random datetime's
def getRandDate(i):
	randDate = '{}-{}-{}'.format(2019, random.randint(1, 12), i) #random.randint(1,28))
	randTime = '{}:{}:{}'.format(random.randint(1,23), random.randint(1,59), random.randint(1,59))
	timeStrng = randDate + ' ' + randTime
	return datetime.datetime.strptime(timeStrng, '%Y-%m-%d %H:%M:%S')


def plotDateTime(dtLists, labels, title): 
	# Plotting
	fig, ax = plt.subplots()

	# Iterate over lists of datetimes and plot them. 
	count = 0 
	colors = ['ro', 'go', 'bo', 'yo']
	for dtms in dtLists:
		x_axis, y_axis = zip(*[(item.date(),item.time()) for item in dtms])
		ax.plot(x_axis, y_axis, colors[count], markersize=1, label=labels[count])
		count += 1

	# Format the axis
	ax.set_ylim(["00:00:00", "23:59:59"])
	ax.xaxis.set_major_locator(mdates.MonthLocator())
	ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d')) 
	ax.xaxis.set_minor_locator(mdates.DayLocator())
	ax.tick_params(axis='both', which='major', labelsize=4)
	#ax.yaxis.set_major_locator(mdates.HourLocator()) 
	#ax.yaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))

	# Plot everything dammit
	mticker.Locator.MAXTICKS = 2000

	# Put a legend to the right of the current axis
	fig.legend(loc=4, frameon=True, framealpha=0.1, fontsize='xx-small', bbox_to_anchor=(1, 0.5)) # loc=0

	fig.autofmt_xdate()
	plt.title(title)
	plt.ylabel('Time', fontsize=10)
	plt.xlabel('Date', fontsize=10)
	plt.show()

if __name__ == '__main__':
	dteTms1 = [getRandDate(i) for i in range(1,28)]
	dteTms2 = [getRandDate(i) for i in range(1,28)]

	dtLists = [dteTms1, dteTms2]
	labels = ['red', 'green']