Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
matplotlib.dates.AutoDateFormatter
The matplotlib.dates.AutoDateFormatter class is used to figure out the best format to use for the date. This is best used with AutoDateLocator. It has a dictionary that maps scale of the tick and a format string. By default it looks as below:
self.scaled = {
DAYS_PER_YEAR: rcParams[‘date.autoformat.year’],
DAYS_PER_MONTH: rcParams[‘date.autoformat.month’],
1.0: rcParams[‘date.autoformat.day’],
1. / HOURS_PER_DAY: rcParams[‘date.autoformat.hour’],
1. / (MINUTES_PER_DAY): rcParams[‘date.autoformat.minute’],
1. / (SEC_PER_DAY): rcParams[‘date.autoformat.second’],
1. / (MUSECONDS_PER_DAY): rcParams[‘date.autoformat.microsecond’],
}
The key in that dictionary that is greater then or equal to the current scale is picked by this algorithm and is used to format strings. This dictionary can also be customized like below:
locator = AutoDateLocator() formatter = AutoDateFormatter(locator) # only show hour and minute formatter.scaled[1/(24.*60.)] = '%H:%M'
The default format is used if no value in self.scaled is greater than the unit returned by locator._get_unit().
Syntax: class matplotlib.dates.AutoDateFormatter(locator, tz=None, defaultfmt=’%Y-%m-%d’)
Parameters:
- locator: It determines the tick locations when plotting dates.
- tz: It holds the time-zone information
- defaultfmt: If no format matches=ches the requirement this format is used as a default in years-months-days format.
Example 1:
Python3
import datetimeimport matplotlib.pyplot as pltfrom matplotlib.dates import AutoDateLocator, AutoDateFormatter, date2num# make my own data:date = '2020-02-23'low = 10# how to format dates:date_datetime = datetime.datetime.strptime(date, '% Y-% m-% d')int_date = date2num( date_datetime)# create plots:figure, axes = plt.subplots()# plot data:axes.bar(int_date, low, label ="", color ="green")# format date locator = AutoDateLocator()axes.xaxis.set_major_locator(locator)axes.xaxis.set_major_formatter( AutoDateFormatter(locator) )# apply autoformatter for displaying of datesmin_date = date2num( datetime.datetime.strptime('2020-02-16', '% Y-% m-% d') )max_date = date2num( datetime.datetime.strptime('2020-02-28', '% Y-% m-% d') )axes.set_xlim([min_date, max_date])figure.autofmt_xdate()# show plot: plt.show() |
Output:
Example 2:
Python3
import randomimport matplotlib.pyplot as pltimport matplotlib.dates as mdates# generate some random data for# approx 5 yrsrandom_data = [float(random.randint(1487517521, 14213254713)) for _ in range(1000)]# convert the epoch format to# matplotlib date format mpl_data = mdates.epoch2num(random_data)# plotting the graphfig, axes = plt.subplots(1, 1)axes.hist(mpl_data, bins = 51, color ='green')locator = mdates.AutoDateLocator()axes.xaxis.set_major_locator(locator)axes.xaxis.set_major_formatter(mdates.AutoDateFormatter(locator))plt.show() |
Output:
