API Reference
matplotlib.dates

`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.

By default, Matplotlib uses the units machinery described in units to convert datetime.datetime, and numpy.datetime64 objects when plotted on an x- or y-axis. The user does not need to do anything for dates to be formatted, but dates often have strict formatting needs, so this module provides many tick locators and formatters. A basic example using numpy.datetime64 is:

import numpy as np

times = np.arange(np.datetime64('2001-01-02'),
                  np.datetime64('2002-02-03'), np.timedelta64(75, 'm'))
y = np.random.randn(len(times))

fig, ax = plt.subplots()
ax.plot(times, y)

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["date.epoch"] (default: '1970-01-01T00:00:00') 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, locators and formatters are timezone aware. If no explicit timezone is provided, rcParams["timezone"] (default: 'UTC') is assumed, provided as a string. If you want to use a different timezone, pass the tz keyword argument of num2date to any date tick locators or formatters you create. This can be either a datetime.tzinfo instance or a string with the timezone name that can be parsed by gettz.

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 tick locators#

Most of the date tick locators can locate single or multiple ticks. 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 tick locators are:

MicrosecondLocator: Locate microseconds.
SecondLocator: Locate seconds.
MinuteLocator: Locate minutes.
HourLocator: Locate hours.
DayLocator: Locate specified days of the month.
WeekdayLocator: Locate days of the week, e.g., MO, TU.
MonthLocator: Locate months, e.g., 7 for July.
YearLocator: Locate years that are multiples of base.
RRuleLocator: Locate using a rrulewrapper. rrulewrapper is a simple wrapper around dateutil's dateutil.rrule which allow almost arbitrary date tick specifications. See rrule example.
AutoDateLocator: On autoscale, this class picks the best DateLocator (e.g., RRuleLocator) to set the view limits and the tick locations. If called with interval_multiples=True it will make ticks line up with sensible multiples of the tick intervals. For example, if the interval is 4 hours, it will pick hours 0, 4, 8, etc. as ticks. This behaviour is not guaranteed by default.

Date formatters#

The available date formatters are:

AutoDateFormatter: attempts to figure out the best format to use. This is most useful when used with the AutoDateLocator.
ConciseDateFormatter: also attempts to figure out the best format to use, and to make the format as compact as possible while still having complete date information. This is most useful when used with the AutoDateLocator.
DateFormatter: use strftime format strings.

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

Bases: Formatter

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

AutoDateFormatter has a .scaled dictionary that maps tick scales (the interval in days between one major tick) to format strings; this dictionary defaults to

self.scaled = {
    DAYS_PER_YEAR: rcParams['date.autoformatter.year'],
    DAYS_PER_MONTH: rcParams['date.autoformatter.month'],
    1: rcParams['date.autoformatter.day'],
    1 / HOURS_PER_DAY: rcParams['date.autoformatter.hour'],
    1 / MINUTES_PER_DAY: rcParams['date.autoformatter.minute'],
    1 / SEC_PER_DAY: rcParams['date.autoformatter.second'],
    1 / MUSECONDS_PER_DAY: rcParams['date.autoformatter.microsecond'],
}

The formatter uses the format string corresponding to the lowest key in the dictionary that is greater or equal to the current scale. Dictionary entries can be customized:

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

Custom callables can also be used instead of format strings. 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

formatter.scaled[1/(24*60)] = my_format_function

Autoformat the date labels.

Parameters:

locatorticker.Locator: Locator that this axis is using.
tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.
defaultfmtstr: The default format to use if none of the values in self.scaled are greater than the unit returned by locator._get_unit().
usetexbool, default: rcParams["text.usetex"] (default: False): To enable/disable the use of TeX's math mode for rendering the results of the formatter. If any entries in self.scaled are set as functions, then it is up to the customized function to enable or disable TeX's math mode itself.

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

Bases: 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:

tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.
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: 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, *, usetex=None)[source]#

Bases: 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 or tzinfo, default: rcParams["timezone"] (default: 'UTC')

Ticks timezone, passed to dates.num2date.

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.

usetexbool, default: rcParams["text.usetex"] (default: False)

To enable/disable the use of TeX's math mode for rendering the results of the formatter.

Examples

See Format date ticks using ConciseDateFormatter

(Source code, 2x.png, 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 representation of value for the mouseover tooltip (the coordinate display in the interactive figure window).

This should return concise, plain text (no mathtext / LaTeX). The precision is typically adapted to the current axis resolution so that neighbouring pixels produce distinguishable labels.

Defaults to Formatter.format_data; subclasses should override this to provide a plain-text representation that is independent of the current tick locations.

Note: The mouseover text can be customized by setting the Axes.fmt_xdata and Axes.fmt_ydata attributes.

format_ticks(values)[source]#

Return the tick label strings for all values.

This is the public API for generating tick labels. It calls set_locs to configure context-dependent formatting state before delegating to __call__ for each individual value.

The output may contain mathtext or LaTeX markup.

Use this method (rather than __call__) whenever formatting a complete set of tick values, so that formatters which need to see all tick locations (e.g. to determine precision, offsets, or which date components to display) can work correctly.

get_offset()[source]#

property offset_string[source]#

[Deprecated]

Notes

Deprecated since version 3.11: Use get_offset() instead.

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

Bases: 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, *, usetex=None)[source]#

Bases: Formatter

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

Parameters:

fmtstr: strftime format string
tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.
usetexbool, default: rcParams["text.usetex"] (default: False): To enable/disable the use of TeX's math mode for rendering the results of the formatter.

set_tzinfo(tz)[source]#

class matplotlib.dates.DateLocator(tz=None)[source]#

Bases: 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:

tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.

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 timezone info.

Parameters:

tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.

viewlim_to_dt()[source]#: Convert the view interval to datetime objects.

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

Bases: RRuleLocator

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

Parameters:

bymonthdayint or list of int, default: all days: Ticks will be placed on every day in bymonthday. Default is bymonthday=range(1, 32), i.e., every day of the month.
intervalint, default: 1: The interval between each iteration. For example, if interval=2, mark every second occurrence.
tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.

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

Bases: RRuleLocator

Make ticks on occurrences of each hour.

Parameters:

byhourint or list of int, default: all hours: Ticks will be placed on every hour in byhour. Default is byhour=range(24), i.e., every hour.
intervalint, default: 1: The interval between each iteration. For example, if interval=2, mark every second occurrence.
tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.

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

Bases: 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.

Parameters:

intervalint, default: 1: The interval between each iteration. For example, if interval=2, mark every second occurrence.
tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.

set_axis(axis)[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: RRuleLocator

Make ticks on occurrences of each minute.

Parameters:

byminuteint or list of int, default: all minutes: Ticks will be placed on every minute in byminute. Default is byminute=range(60), i.e., every minute.
intervalint, default: 1: The interval between each iteration. For example, if interval=2, mark every second occurrence.
tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.

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

Bases: RRuleLocator

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

Parameters:

bymonthint or list of int, default: all months: Ticks will be placed on every month in bymonth. Default is range(1, 13), i.e. every month.
bymonthdayint, default: 1: The day on which to place the ticks.
intervalint, default: 1: The interval between each iteration. For example, if interval=2, mark every second occurrence.
tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.

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

Bases: DateLocator

Parameters:

tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.

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: RRuleLocator

Make ticks on occurrences of each second.

Parameters:

bysecondint or list of int, default: all seconds: Ticks will be placed on every second in bysecond. Default is bysecond = range(60), i.e., every second.
intervalint, default: 1: The interval between each iteration. For example, if interval=2, mark every second occurrence.
tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.

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

Bases: RRuleLocator

Make ticks on occurrences of each weekday.

Parameters:

byweekdayint, list of int, constant from dateutil.rrule, or list of constants, default: 1 (Tuesday)

Ticks will be placed on every weekday in byweekday. Default is every Tuesday.

Elements of byweekday (if a sequence) must be either integers or MO, TU, WE, TH, FR, SA, SU, the constants from dateutil.rrule, which have been imported into the matplotlib.dates namespace.

intervalint, default: 1

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

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

Ticks timezone. If a string, tz is passed to dateutil.tz.

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

Bases: RRuleLocator

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)

Parameters:

baseint, default: 1: Mark ticks every base years.
monthint, default: 1: The month on which to place the ticks, starting from 1. Default is January.
dayint, default: 1: The day on which to place the ticks.
tzstr or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Ticks timezone. If a string, tz is passed to dateutil.tz.

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.get_epoch()[source]#

Get the epoch used by dates.

Returns:

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

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 or tzinfo, default: rcParams["timezone"] (default: 'UTC'): Timezone of x. If a string, tz is passed to dateutil.tz.

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

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)#

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:

Year
Month
Day
Hours
Minutes
Seconds
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()#

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.rrulewrapper(freq, tzinfo=None, **kwargs)[source]#

Bases: object

A simple wrapper around a dateutil.rrule allowing flexible date tick specifications.

Parameters:

freq{YEARLY, MONTHLY, WEEKLY, DAILY, HOURLY, MINUTELY, SECONDLY}: Tick frequency. These constants are defined in dateutil.rrule, but they are accessible from matplotlib.dates as well.
tzinfodatetime.tzinfo, optional: Time zone information. The default is None.
**kwargs: Additional keyword arguments are passed to the dateutil.rrule.

set(**kwargs)[source]#: Set parameters for an existing wrapper.

matplotlib.dates.set_epoch(epoch)[source]#

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

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

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 of 2^52.

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

matplotlib.dates#

Matplotlib date format#

Date tick locators#

Date formatters#

`matplotlib.dates`#