matplotlib.dates

Inheritance diagram of matplotlib.dates

Matplotlib provides sophisticated date plotting capabilities, standing on the shoulders of python datetime and the add-on module dateutil.

Matplotlib date format

Matplotlib represents dates using floating point numbers specifying the number of days since a default epoch of 1970-01-01 UTC; for example, 1970-01-01, 06:00 is the floating point number 0.25. The formatters and locators require the use of datetime.datetime objects, so only dates between year 0001 and 9999 can be represented. Microsecond precision is achievable for (approximately) 70 years on either side of the epoch, and 20 microseconds for the rest of the allowable range of dates (year 0001 to 9999). The epoch can be changed at import time via dates.set_epoch or rcParams["dates.epoch"] to other dates if necessary; see Date Precision and Epochs for a discussion.

Note

Before Matplotlib 3.3, the epoch was 0000-12-31 which lost modern microsecond precision and also made the default axis limit of 0 an invalid datetime. In 3.3 the epoch was changed as above. To convert old ordinal floats to the new epoch, users can do:

new_ordinal = old_ordinal + mdates.date2num(np.datetime64('0000-12-31'))

There are a number of helper functions to convert between datetime objects and Matplotlib dates:

datestr2num Convert a date string to a datenum using dateutil.parser.parse.
date2num Convert datetime objects to Matplotlib dates.
num2date Convert Matplotlib dates to datetime objects.
num2timedelta Convert number of days to a timedelta object.
drange Return a sequence of equally spaced Matplotlib dates.
set_epoch Set the epoch (origin for dates) for datetime calculations.
get_epoch Get the epoch used by dates.

Note

Like Python's datetime.datetime, Matplotlib uses the Gregorian calendar for all conversions between dates and floating point numbers. This practice is not universal, and calendar differences can cause confusing differences between what Python and Matplotlib give as the number of days since 0001-01-01 and what other software and databases yield. For example, the US Naval Observatory uses a calendar that switches from Julian to Gregorian in October, 1582. Hence, using their calculator, the number of days between 0001-01-01 and 2006-04-01 is 732403, whereas using the Gregorian calendar via the datetime module we find:

In [1]: date(2006, 4, 1).toordinal() - date(1, 1, 1).toordinal()
Out[1]: 732401

All the Matplotlib date converters, tickers and formatters are timezone aware. If no explicit timezone is provided, rcParams["timezone"] (default: 'UTC') is assumed. If you want to use a custom time zone, pass a datetime.tzinfo instance with the tz keyword argument to num2date, plot_date, and any custom date tickers or locators you create.

A wide range of specific and general purpose date tick locators and formatters are provided in this module. See matplotlib.ticker for general information on tick locators and formatters. These are described below.

The dateutil module provides additional code to handle date ticking, making it easy to place ticks on any kinds of dates. See examples below.

Date tickers

Most of the date tickers can locate single or multiple values. For example:

# import constants for the days of the week
from matplotlib.dates import MO, TU, WE, TH, FR, SA, SU

# tick on mondays every week
loc = WeekdayLocator(byweekday=MO, tz=tz)

# tick on mondays and saturdays
loc = WeekdayLocator(byweekday=(MO, SA))

In addition, most of the constructors take an interval argument:

# tick on mondays every second week
loc = WeekdayLocator(byweekday=MO, interval=2)

The rrule locator allows completely general date ticking:

# tick every 5th easter
rule = rrulewrapper(YEARLY, byeaster=1, interval=5)
loc = RRuleLocator(rule)

The available date tickers are:

Date formatters

The available date formatters are:

class matplotlib.dates.AutoDateFormatter(locator, tz=None, defaultfmt='%Y-%m-%d')[source]

Bases: matplotlib.ticker.Formatter

A Formatter which attempts to figure out the best format to use. This is most useful when used with the AutoDateLocator.

The AutoDateFormatter has a scale dictionary that maps the scale of the tick (the distance in days between one major tick) and a format string. The default looks like this:

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 algorithm picks the key in the dictionary that is >= the current scale and uses that format string. You can customize this dictionary by doing:

>>> locator = AutoDateLocator()
>>> formatter = AutoDateFormatter(locator)
>>> formatter.scaled[1/(24.*60.)] = '%M:%S' # only show min and sec

A custom FuncFormatter can also be used. The following example shows how to use a custom format function to strip trailing zeros from decimal seconds and adds the date to the first ticklabel:

>>> def my_format_function(x, pos=None):
...     x = matplotlib.dates.num2date(x)
...     if pos == 0:
...         fmt = '%D %H:%M:%S.%f'
...     else:
...         fmt = '%H:%M:%S.%f'
...     label = x.strftime(fmt)
...     label = label.rstrip("0")
...     label = label.rstrip(".")
...     return label
>>> from matplotlib.ticker import FuncFormatter
>>> formatter.scaled[1/(24.*60.)] = FuncFormatter(my_format_function)

Autoformat the date labels. The default format is the one to use if none of the values in self.scaled are greater than the unit returned by locator._get_unit().

class matplotlib.dates.AutoDateLocator(tz=None, minticks=5, maxticks=None, interval_multiples=True)[source]

Bases: matplotlib.dates.DateLocator

On autoscale, this class picks the best DateLocator to set the view limits and the tick locations.

Attributes:
intervalddict

Mapping of tick frequencies to multiples allowed for that ticking. The default is

self.intervald = {
    YEARLY  : [1, 2, 4, 5, 10, 20, 40, 50, 100, 200, 400, 500,
               1000, 2000, 4000, 5000, 10000],
    MONTHLY : [1, 2, 3, 4, 6],
    DAILY   : [1, 2, 3, 7, 14, 21],
    HOURLY  : [1, 2, 3, 4, 6, 12],
    MINUTELY: [1, 5, 10, 15, 30],
    SECONDLY: [1, 5, 10, 15, 30],
    MICROSECONDLY: [1, 2, 5, 10, 20, 50, 100, 200, 500,
                    1000, 2000, 5000, 10000, 20000, 50000,
                    100000, 200000, 500000, 1000000],
}

where the keys are defined in dateutil.rrule.

The interval is used to specify multiples that are appropriate for the frequency of ticking. For instance, every 7 days is sensible for daily ticks, but for minutes/seconds, 15 or 30 make sense.

When customizing, you should only modify the values for the existing keys. You should not add or delete entries.

Example for forcing ticks every 3 hours:

locator = AutoDateLocator()
locator.intervald[HOURLY] = [3]  # only show every 3 hours
Parameters:
tzdatetime.tzinfo

Ticks timezone.

minticksint

The minimum number of ticks desired; controls whether ticks occur yearly, monthly, etc.

maxticksint

The maximum number of ticks desired; controls the interval between ticks (ticking every other, every 3, etc.). For fine-grained control, this can be a dictionary mapping individual rrule frequency constants (YEARLY, MONTHLY, etc.) to their own maximum number of ticks. This can be used to keep the number of ticks appropriate to the format chosen in AutoDateFormatter. Any frequency not specified in this dictionary is given a default value.

interval_multiplesbool, default: True

Whether ticks should be chosen to be multiple of the interval, locking them to 'nicer' locations. For example, this will force the ticks to be at hours 0, 6, 12, 18 when hourly ticking is done at 6 hour intervals.

get_locator(dmin, dmax)[source]

Pick the best locator based on a distance.

nonsingular(vmin, vmax)[source]

Given the proposed upper and lower extent, adjust the range if it is too close to being singular (i.e. a range of ~0).

tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.

Note

To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance:

>>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]
class matplotlib.dates.ConciseDateConverter(formats=None, zero_formats=None, offset_formats=None, show_offset=True, *, interval_multiples=True)[source]

Bases: matplotlib.dates.DateConverter

axisinfo(unit, axis)[source]

Return the AxisInfo for unit.

unit is a tzinfo instance or None. The axis argument is required but not used.

class matplotlib.dates.ConciseDateFormatter(locator, tz=None, formats=None, offset_formats=None, zero_formats=None, show_offset=True)[source]

Bases: matplotlib.ticker.Formatter

A Formatter which attempts to figure out the best format to use for the date, and to make it as compact as possible, but still be complete. This is most useful when used with the AutoDateLocator:

>>> locator = AutoDateLocator()
>>> formatter = ConciseDateFormatter(locator)
Parameters:
locatorticker.Locator

Locator that this axis is using.

tzstr, optional

Passed to dates.date2num.

formatslist of 6 strings, optional

Format strings for 6 levels of tick labelling: mostly years, months, days, hours, minutes, and seconds. Strings use the same format codes as strftime. Default is ['%Y', '%b', '%d', '%H:%M', '%H:%M', '%S.%f']

zero_formatslist of 6 strings, optional

Format strings for tick labels that are "zeros" for a given tick level. For instance, if most ticks are months, ticks around 1 Jan 2005 will be labeled "Dec", "2005", "Feb". The default is ['', '%Y', '%b', '%b-%d', '%H:%M', '%H:%M']

offset_formatslist of 6 strings, optional

Format strings for the 6 levels that is applied to the "offset" string found on the right side of an x-axis, or top of a y-axis. Combined with the tick labels this should completely specify the date. The default is:

['', '%Y', '%Y-%b', '%Y-%b-%d', '%Y-%b-%d', '%Y-%b-%d %H:%M']
show_offsetbool, default: True

Whether to show the offset or not.

Examples

See Formatting date ticks using ConciseDateFormatter

(Source code, png, pdf)

../_images/dates_api-1.png

Autoformat the date labels. The default format is used to form an initial string, and then redundant elements are removed.

format_data_short(value)[source]

Return a short string version of the tick value.

Defaults to the position-independent long value.

format_ticks(values)[source]

Return the tick labels for all the ticks at once.

get_offset()[source]
class matplotlib.dates.DateConverter(*, interval_multiples=True)[source]

Bases: matplotlib.units.ConversionInterface

Converter for datetime.date and datetime.datetime data, or for date/time data represented as it would be converted by date2num.

The 'unit' tag for such data is None or a tzinfo instance.

axisinfo(unit, axis)[source]

Return the AxisInfo for unit.

unit is a tzinfo instance or None. The axis argument is required but not used.

static convert(value, unit, axis)[source]

If value is not already a number or sequence of numbers, convert it with date2num.

The unit and axis arguments are not used.

static default_units(x, axis)[source]

Return the tzinfo instance of x or of its first element, or None

class matplotlib.dates.DateFormatter(fmt, tz=None)[source]

Bases: matplotlib.ticker.Formatter

Format a tick (in days since the epoch) with a strftime format string.

Parameters:
fmtstr

strftime format string

tzdatetime.tzinfo, default: rcParams["timezone"] (default: 'UTC')

Ticks timezone.

property illegal_s
set_tzinfo(tz)[source]
class matplotlib.dates.DateLocator(tz=None)[source]

Bases: matplotlib.ticker.Locator

Determines the tick locations when plotting dates.

This class is subclassed by other Locators and is not meant to be used on its own.

Parameters:
tzdatetime.tzinfo
datalim_to_dt()[source]

Convert axis data interval to datetime objects.

hms0d = {'byhour': 0, 'byminute': 0, 'bysecond': 0}
nonsingular(vmin, vmax)[source]

Given the proposed upper and lower extent, adjust the range if it is too close to being singular (i.e. a range of ~0).

set_tzinfo(tz)[source]

Set time zone info.

viewlim_to_dt()[source]

Convert the view interval to datetime objects.

class matplotlib.dates.DayLocator(bymonthday=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator

Make ticks on occurrences of each day of the month. For example, 1, 15, 30.

Mark every day in bymonthday; bymonthday can be an int or sequence.

Default is to tick every day of the month: bymonthday=range(1, 32).

class matplotlib.dates.HourLocator(byhour=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator

Make ticks on occurrences of each hour.

Mark every hour in byhour; byhour can be an int or sequence. Default is to tick every hour: byhour=range(24)

interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.

class matplotlib.dates.IndexDateFormatter(**kwargs)[source]

Bases: matplotlib.ticker.Formatter

[Deprecated] Use with IndexLocator to cycle format strings by index.

Notes

Deprecated since version 3.3.

Parameters:
tlist of float

A sequence of dates (floating point days).

fmtstr

A strftime format string.

class matplotlib.dates.MicrosecondLocator(interval=1, tz=None)[source]

Bases: matplotlib.dates.DateLocator

Make ticks on regular intervals of one or more microsecond(s).

Note

By default, Matplotlib uses a floating point representation of time in days since the epoch, so plotting data with microsecond time resolution does not work well for dates that are far (about 70 years) from the epoch (check with get_epoch).

If you want sub-microsecond resolution time plots, it is strongly recommended to use floating point seconds, not datetime-like time representation.

If you really must use datetime.datetime() or similar and still need microsecond precision, change the time origin via dates.set_epoch to something closer to the dates being plotted. See Date Precision and Epochs.

interval is the interval between each iteration. For example, if interval=2, mark every second microsecond.

set_axis(axis)[source]
set_data_interval(vmin, vmax)[source]
set_view_interval(vmin, vmax)[source]
tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.

Note

To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance:

>>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]
class matplotlib.dates.MinuteLocator(byminute=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator

Make ticks on occurrences of each minute.

Mark every minute in byminute; byminute can be an int or sequence. Default is to tick every minute: byminute=range(60)

interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.

class matplotlib.dates.MonthLocator(bymonth=None, bymonthday=1, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator

Make ticks on occurrences of each month, e.g., 1, 3, 12.

Mark every month in bymonth; bymonth can be an int or sequence. Default is range(1, 13), i.e. every month.

interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.

class matplotlib.dates.RRuleLocator(o, tz=None)[source]

Bases: matplotlib.dates.DateLocator

Parameters:
tzdatetime.tzinfo
static get_unit_generic(freq)[source]
tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.

Note

To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance:

>>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]
class matplotlib.dates.SecondLocator(bysecond=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator

Make ticks on occurrences of each second.

Mark every second in bysecond; bysecond can be an int or sequence. Default is to tick every second: bysecond = range(60)

interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.

class matplotlib.dates.WeekdayLocator(byweekday=1, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator

Make ticks on occurrences of each weekday.

Mark every weekday in byweekday; byweekday can be a number or sequence.

Elements of byweekday must be one of MO, TU, WE, TH, FR, SA, SU, the constants from dateutil.rrule, which have been imported into the matplotlib.dates namespace.

interval specifies the number of weeks to skip. For example, interval=2 plots every second week.

class matplotlib.dates.YearLocator(base=1, month=1, day=1, tz=None)[source]

Bases: matplotlib.dates.DateLocator

Make ticks on a given day of each year that is a multiple of base.

Examples:

# Tick every year on Jan 1st
locator = YearLocator()

# Tick every 5 years on July 4th
locator = YearLocator(5, month=7, day=4)

Mark years that are multiple of base on a given month and day (default jan 1).

tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.

Note

To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance:

>>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]
matplotlib.dates.date2num(d)[source]

Convert datetime objects to Matplotlib dates.

Parameters:
ddatetime.datetime or numpy.datetime64 or sequences of these
Returns:
float or sequence of floats

Number of days since the epoch. See get_epoch for the epoch, which can be changed by rcParams["date.epoch"] (default: '1970-01-01T00:00:00') or set_epoch. If the epoch is "1970-01-01T00:00:00" (default) then noon Jan 1 1970 ("1970-01-01T12:00:00") returns 0.5.

Notes

The Gregorian calendar is assumed; this is not universal practice. For details see the module docstring.

matplotlib.dates.datestr2num(d, default=None)[source]

Convert a date string to a datenum using dateutil.parser.parse.

Parameters:
dstr or sequence of str

The dates to convert.

defaultdatetime.datetime, optional

The default date to use when fields are missing in d.

matplotlib.dates.drange(dstart, dend, delta)[source]

Return a sequence of equally spaced Matplotlib dates.

The dates start at dstart and reach up to, but not including dend. They are spaced by delta.

Parameters:
dstart, denddatetime

The date limits.

deltadatetime.timedelta

Spacing of the dates.

Returns:
numpy.array

A list floats representing Matplotlib dates.

matplotlib.dates.epoch2num(e)[source]

Convert UNIX time to days since Matplotlib epoch.

Parameters:
elist of floats

Time in seconds since 1970-01-01.

Returns:
numpy.array

Time in days since Matplotlib epoch (see get_epoch()).

matplotlib.dates.get_epoch()[source]

Get the epoch used by dates.

Returns:
epoch: str

String for the epoch (parsable by numpy.datetime64).

matplotlib.dates.mx2num(mxdates)[source]

[Deprecated] Convert mx datetime instance (or sequence of mx instances) to the new date format.

Notes

Deprecated since version 3.2.

matplotlib.dates.num2date(x, tz=None)[source]

Convert Matplotlib dates to datetime objects.

Parameters:
xfloat or sequence of floats

Number of days (fraction part represents hours, minutes, seconds) since the epoch. See get_epoch for the epoch, which can be changed by rcParams["date.epoch"] (default: '1970-01-01T00:00:00') or set_epoch.

tzstr, default: rcParams["timezone"] (default: 'UTC')

Timezone of x.

Returns:
datetime or sequence of datetime

Dates are returned in timezone tz.

If x is a sequence, a sequence of datetime objects will be returned.

Notes

The addition of one here is a historical artifact. Also, note that the Gregorian calendar is assumed; this is not universal practice. For details, see the module docstring.

matplotlib.dates.num2epoch(d)[source]

Convert days since Matplotlib epoch to UNIX time.

Parameters:
dlist of floats

Time in days since Matplotlib epoch (see get_epoch()).

Returns:
numpy.array

Time in seconds since 1970-01-01.

matplotlib.dates.num2timedelta(x)[source]

Convert number of days to a timedelta object.

If x is a sequence, a sequence of timedelta objects will be returned.

Parameters:
xfloat, sequence of floats

Number of days. The fraction part represents hours, minutes, seconds.

Returns:
datetime.timedelta or list[datetime.timedelta]
class matplotlib.dates.relativedelta(dt1=None, dt2=None, years=0, months=0, days=0, leapdays=0, weeks=0, hours=0, minutes=0, seconds=0, microseconds=0, year=None, month=None, day=None, weekday=None, yearday=None, nlyearday=None, hour=None, minute=None, second=None, microsecond=None)[source]

Bases: object

The relativedelta type is designed to be applied to an existing datetime and can replace specific components of that datetime, or represents an interval of time.

It is based on the specification of the excellent work done by M.-A. Lemburg in his mx.DateTime extension. However, notice that this type does NOT implement the same algorithm as his work. Do NOT expect it to behave like mx.DateTime's counterpart.

There are two different ways to build a relativedelta instance. The first one is passing it two date/datetime classes:

relativedelta(datetime1, datetime2)

The second one is passing it any number of the following keyword arguments:

relativedelta(arg1=x,arg2=y,arg3=z...)

year, month, day, hour, minute, second, microsecond:
    Absolute information (argument is singular); adding or subtracting a
    relativedelta with absolute information does not perform an arithmetic
    operation, but rather REPLACES the corresponding value in the
    original datetime with the value(s) in relativedelta.

years, months, weeks, days, hours, minutes, seconds, microseconds:
    Relative information, may be negative (argument is plural); adding
    or subtracting a relativedelta with relative information performs
    the corresponding arithmetic operation on the original datetime value
    with the information in the relativedelta.

weekday: 
    One of the weekday instances (MO, TU, etc) available in the
    relativedelta module. These instances may receive a parameter N,
    specifying the Nth weekday, which could be positive or negative
    (like MO(+1) or MO(-2)). Not specifying it is the same as specifying
    +1. You can also use an integer, where 0=MO. This argument is always
    relative e.g. if the calculated date is already Monday, using MO(1)
    or MO(-1) won't change the day. To effectively make it absolute, use
    it in combination with the day argument (e.g. day=1, MO(1) for first
    Monday of the month).

leapdays:
    Will add given days to the date found, if year is a leap
    year, and the date found is post 28 of february.

yearday, nlyearday:
    Set the yearday or the non-leap year day (jump leap days).
    These are converted to day/month/leapdays information.

There are relative and absolute forms of the keyword arguments. The plural is relative, and the singular is absolute. For each argument in the order below, the absolute form is applied first (by setting each attribute to that value) and then the relative form (by adding the value to the attribute).

The order of attributes considered when this relativedelta is added to a datetime is:

  1. Year
  2. Month
  3. Day
  4. Hours
  5. Minutes
  6. Seconds
  7. Microseconds

Finally, weekday is applied, using the rule described above.

For example

>>> from datetime import datetime
>>> from dateutil.relativedelta import relativedelta, MO
>>> dt = datetime(2018, 4, 9, 13, 37, 0)
>>> delta = relativedelta(hours=25, day=1, weekday=MO(1))
>>> dt + delta
datetime.datetime(2018, 4, 2, 14, 37)

First, the day is set to 1 (the first of the month), then 25 hours are added, to get to the 2nd day and 14th hour, finally the weekday is applied, but since the 2nd is already a Monday there is no effect.

normalized()[source]

Return a version of this object represented entirely using integer values for the relative attributes.

>>> relativedelta(days=1.5, hours=2).normalized()
relativedelta(days=+1, hours=+14)
Returns:Returns a dateutil.relativedelta.relativedelta object.
property weeks
class matplotlib.dates.rrule(freq, dtstart=None, interval=1, wkst=None, count=None, until=None, bysetpos=None, bymonth=None, bymonthday=None, byyearday=None, byeaster=None, byweekno=None, byweekday=None, byhour=None, byminute=None, bysecond=None, cache=False)[source]

Bases: dateutil.rrule.rrulebase

That's the base of the rrule operation. It accepts all the keywords defined in the RFC as its constructor parameters (except byday, which was renamed to byweekday) and more. The constructor prototype is:

rrule(freq)

Where freq must be one of YEARLY, MONTHLY, WEEKLY, DAILY, HOURLY, MINUTELY, or SECONDLY.

Note

Per RFC section 3.3.10, recurrence instances falling on invalid dates and times are ignored rather than coerced:

Recurrence rules may generate recurrence instances with an invalid date (e.g., February 30) or nonexistent local time (e.g., 1:30 AM on a day where the local time is moved forward by an hour at 1:00 AM). Such recurrence instances MUST be ignored and MUST NOT be counted as part of the recurrence set.

This can lead to possibly surprising behavior when, for example, the start date occurs at the end of the month:

>>> from dateutil.rrule import rrule, MONTHLY
>>> from datetime import datetime
>>> start_date = datetime(2014, 12, 31)
>>> list(rrule(freq=MONTHLY, count=4, dtstart=start_date))
... 
[datetime.datetime(2014, 12, 31, 0, 0),
 datetime.datetime(2015, 1, 31, 0, 0),
 datetime.datetime(2015, 3, 31, 0, 0),
 datetime.datetime(2015, 5, 31, 0, 0)]

Additionally, it supports the following keyword arguments:

Parameters:
  • dtstart -- The recurrence start. Besides being the base for the recurrence, missing parameters in the final recurrence instances will also be extracted from this date. If not given, datetime.now() will be used instead.
  • interval -- The interval between each freq iteration. For example, when using YEARLY, an interval of 2 means once every two years, but with HOURLY, it means once every two hours. The default interval is 1.
  • wkst -- The week start day. Must be one of the MO, TU, WE constants, or an integer, specifying the first day of the week. This will affect recurrences based on weekly periods. The default week start is got from calendar.firstweekday(), and may be modified by calendar.setfirstweekday().
  • count --

    If given, this determines how many occurrences will be generated.

    Note

    As of version 2.5.0, the use of the keyword until in conjunction with count is deprecated, to make sure dateutil is fully compliant with RFC-5545 Sec. 3.3.10. Therefore, until and count must not occur in the same call to rrule.

  • until --

    If given, this must be a datetime instance specifying the upper-bound limit of the recurrence. The last recurrence in the rule is the greatest datetime that is less than or equal to the value specified in the until parameter.

    Note

    As of version 2.5.0, the use of the keyword until in conjunction with count is deprecated, to make sure dateutil is fully compliant with RFC-5545 Sec. 3.3.10. Therefore, until and count must not occur in the same call to rrule.

  • bysetpos -- If given, it must be either an integer, or a sequence of integers, positive or negative. Each given integer will specify an occurrence number, corresponding to the nth occurrence of the rule inside the frequency period. For example, a bysetpos of -1 if combined with a MONTHLY frequency, and a byweekday of (MO, TU, WE, TH, FR), will result in the last work day of every month.
  • bymonth -- If given, it must be either an integer, or a sequence of integers, meaning the months to apply the recurrence to.
  • bymonthday -- If given, it must be either an integer, or a sequence of integers, meaning the month days to apply the recurrence to.
  • byyearday -- If given, it must be either an integer, or a sequence of integers, meaning the year days to apply the recurrence to.
  • byeaster -- If given, it must be either an integer, or a sequence of integers, positive or negative. Each integer will define an offset from the Easter Sunday. Passing the offset 0 to byeaster will yield the Easter Sunday itself. This is an extension to the RFC specification.
  • byweekno -- If given, it must be either an integer, or a sequence of integers, meaning the week numbers to apply the recurrence to. Week numbers have the meaning described in ISO8601, that is, the first week of the year is that containing at least four days of the new year.
  • byweekday -- If given, it must be either an integer (0 == MO), a sequence of integers, one of the weekday constants (MO, TU, etc), or a sequence of these constants. When given, these variables will define the weekdays where the recurrence will be applied. It's also possible to use an argument n for the weekday instances, which will mean the nth occurrence of this weekday in the period. For example, with MONTHLY, or with YEARLY and BYMONTH, using FR(+1) in byweekday will specify the first friday of the month where the recurrence happens. Notice that in the RFC documentation, this is specified as BYDAY, but was renamed to avoid the ambiguity of that keyword.
  • byhour -- If given, it must be either an integer, or a sequence of integers, meaning the hours to apply the recurrence to.
  • byminute -- If given, it must be either an integer, or a sequence of integers, meaning the minutes to apply the recurrence to.
  • bysecond -- If given, it must be either an integer, or a sequence of integers, meaning the seconds to apply the recurrence to.
  • cache -- If given, it must be a boolean value specifying to enable or disable caching of results. If you will use the same rrule instance multiple times, enabling caching will improve the performance considerably.
replace(**kwargs)[source]

Return new rrule with same attributes except for those attributes given new values by whichever keyword arguments are specified.

matplotlib.dates.set_epoch(epoch)[source]

Set the epoch (origin for dates) for datetime calculations.

The default epoch is rcParams["dates.epoch"] (by default 1970-01-01T00:00).

If microsecond accuracy is desired, the date being plotted needs to be within approximately 70 years of the epoch. Matplotlib internally represents dates as days since the epoch, so floating point dynamic range needs to be within a factor fo 2^52.

set_epoch must be called before any dates are converted (i.e. near the import section) or a RuntimeError will be raised.

See also Date Precision and Epochs.

Parameters:
epochstr

valid UTC date parsable by numpy.datetime64 (do not include timezone).