matplotlib.dates
¶Matplotlib provides sophisticated date plotting capabilities, standing on the
shoulders of python datetime
, the addon modules pytz
and
dateutil
. datetime
objects are converted to floating point
numbers which represent time in days since 00010101 UTC, plus 1. For
example, 00010101, 06:00 is 1.25, not 0.25. The helper functions
date2num()
, num2date()
and drange()
are used to facilitate
easy conversion to and from datetime
and numeric ranges.
Note
Like Python’s datetime, mpl 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 mpl give as the number of days since 00010101 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 00010101 and 20060401 is 732403, whereas using the Gregorian calendar via the datetime module we find:
In [31]:date(2006,4,1).toordinal()  date(1,1,1).toordinal()
Out[31]:732401
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.
All the matplotlib date converters, tickers and formatters are
timezone aware, and the default timezone is given by the timezone
parameter in your matplotlibrc
file. If you leave out a
tz
timezone instance, the default from your rc file will be
assumed. If you want to use a custom time zone, pass a
pytz.timezone
instance with the tz keyword argument to
num2date()
, plot_date()
, and any custom date tickers or
locators you create. See pytz for
information on pytz
and timezone handling.
The dateutil module provides additional code to handle date ticking, making it easy to place ticks on any kinds of dates. See examples below.
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)
Here are all the date tickers:
MinuteLocator
: locate minutesHourLocator
: locate hoursDayLocator
: locate specified days of the monthWeekdayLocator
: Locate days of the week, e.g., MO, TUMonthLocator
: locate months, e.g., 7 for julyYearLocator
: locate years that are multiples of baseRRuleLocator
: locate using amatplotlib.dates.rrulewrapper
. Therrulewrapper
is a simple wrapper around adateutil.rrule
(dateutil) which allow almost arbitrary date tick specifications. See rrule example.AutoDateLocator
: On autoscale, this class picks the bestMultipleDateLocator
to set the view limits and the tick locations.
Here all all the date formatters:
AutoDateFormatter
: attempts to figure out the best format to use. This is most useful when used with theAutoDateLocator
.DateFormatter
: usestrftime()
format stringsIndexDateFormatter
: date plots with implicit x indexing.
matplotlib.dates.
date2num
(d)¶Converts datetime objects to Matplotlib dates.
Parameters:  d : 

Returns:  float or sequence of floats

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.
num2date
(x, tz=None)¶Parameters:  x : float or sequence of floats
tz : string, optional


Returns: 
If x is a sequence, a sequence of 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.
num2timedelta
(x)¶Converts number of days to a timdelta
object.
If x is a sequence, a sequence of timedelta
objects will
be returned.
Parameters:  x : float, sequence of floats


Returns: 

matplotlib.dates.
drange
(dstart, dend, delta)¶Return a date range as float Gregorian ordinals. dstart and
dend are datetime
instances. delta is a
datetime.timedelta
instance.
matplotlib.dates.
epoch2num
(e)¶Convert an epoch or sequence of epochs to the new date format, that is days since 0001.
matplotlib.dates.
num2epoch
(d)¶Convert days since 0001 to epoch. d can be a number or sequence.
matplotlib.dates.
mx2num
(mxdates)¶Convert mx datetime
instance (or sequence of mx
instances) to the new date format.
matplotlib.dates.
DateFormatter
(fmt, tz=None)¶Bases: matplotlib.ticker.Formatter
Tick location is seconds since the epoch. Use a strftime()
format string.
Python only supports datetime
strftime()
formatting
for years greater than 1900. Thanks to Andrew Dalke, Dalke
Scientific Software who contributed the strftime()
code
below to include dates earlier than this year.
strftime()
format string; tz is thetzinfo
instance.illegal_s
= re.compile('((^[^%])(%%)*%s)')¶set_tzinfo
(tz)¶strftime
(dt, fmt=None)¶Refer to documentation for datetime.strftime.
fmt is a strftime()
format string.
Warning: For years before 1900, depending upon the current locale it is possible that the year displayed with %x might be incorrect. For years before 100, %y and %Y will yield zeropadded strings.
strftime_pre_1900
(dt, fmt=None)¶Call time.strftime for years before 1900 by rolling forward a multiple of 28 years.
fmt is a strftime()
format string.
Dalke: I hope I did this math right. Every 28 years the calendar repeats, except through century leap years excepting the 400 year leap years. But only if you’re using the Gregorian calendar.
matplotlib.dates.
IndexDateFormatter
(t, fmt, tz=None)¶Bases: matplotlib.ticker.Formatter
Use with IndexLocator
to cycle format
strings by index.
t is a sequence of dates (floating point days). fmt is a
strftime()
format string.
matplotlib.dates.
AutoDateFormatter
(locator, tz=None, defaultfmt='%Y%m%d')¶Bases: matplotlib.ticker.Formatter
This class 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()
.
matplotlib.dates.
DateLocator
(tz=None)¶Bases: matplotlib.ticker.Locator
Determines the tick locations when plotting dates.
tz is a tzinfo
instance.
datalim_to_dt
()¶Convert axis data interval to datetime objects.
hms0d
= {'byhour': 0, 'byminute': 0, 'bysecond': 0}¶nonsingular
(vmin, vmax)¶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)¶Set time zone info.
viewlim_to_dt
()¶Converts the view interval to datetime objects.
matplotlib.dates.
RRuleLocator
(o, tz=None)¶Bases: matplotlib.dates.DateLocator
autoscale
()¶Set the view limits to include the data range.
get_unit_generic
(freq)¶tick_values
(vmin, vmax)¶matplotlib.dates.
AutoDateLocator
(tz=None, minticks=5, maxticks=None, interval_multiples=False)¶Bases: matplotlib.dates.DateLocator
On autoscale, this class picks the best
DateLocator
to set the view limits and the tick
locations.
minticks is the minimum number of ticks desired, which is used to select the type of ticking (yearly, monthly, etc.).
maxticks is the maximum number of ticks desired, which controls
any interval between ticks (ticking every other, every 3, etc.).
For really finegrained 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.
tz is a tzinfo
instance.
interval_multiples is a boolean that indicates whether ticks should be chosen to be multiple of the interval. This will lock ticks 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.
The AutoDateLocator has an interval dictionary that maps the frequency of the tick (a constant from dateutil.rrule) and a multiple allowed for that ticking. The default looks like this:
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],
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],
}
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. You can customize this dictionary by doing:
locator = AutoDateLocator()
locator.intervald[HOURLY] = [3] # only show every 3 hours
autoscale
()¶Try to choose the view limits intelligently.
get_locator
(dmin, dmax)¶Pick the best locator based on a distance.
nonsingular
(vmin, vmax)¶refresh
()¶Refresh internal information based on current limits.
set_axis
(axis)¶tick_values
(vmin, vmax)¶matplotlib.dates.
YearLocator
(base=1, month=1, day=1, tz=None)¶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).
autoscale
()¶Set the view limits to include the data range.
tick_values
(vmin, vmax)¶matplotlib.dates.
MonthLocator
(bymonth=None, bymonthday=1, interval=1, tz=None)¶Bases: matplotlib.dates.RRuleLocator
Make ticks on occurances of each month 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 occurance.
matplotlib.dates.
WeekdayLocator
(byweekday=1, interval=1, tz=None)¶Bases: matplotlib.dates.RRuleLocator
Make ticks on occurances 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.
matplotlib.dates.
DayLocator
(bymonthday=None, interval=1, tz=None)¶Bases: matplotlib.dates.RRuleLocator
Make ticks on occurances 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)
matplotlib.dates.
HourLocator
(byhour=None, interval=1, tz=None)¶Bases: matplotlib.dates.RRuleLocator
Make ticks on occurances 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.
matplotlib.dates.
MinuteLocator
(byminute=None, interval=1, tz=None)¶Bases: matplotlib.dates.RRuleLocator
Make ticks on occurances 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.
matplotlib.dates.
SecondLocator
(bysecond=None, interval=1, tz=None)¶Bases: matplotlib.dates.RRuleLocator
Make ticks on occurances 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.
matplotlib.dates.
MicrosecondLocator
(interval=1, tz=None)¶Bases: matplotlib.dates.DateLocator
Make ticks on occurances of each microsecond.
interval is the interval between each iteration. For
example, if interval=2
, mark every second microsecond.
set_axis
(axis)¶set_data_interval
(vmin, vmax)¶set_view_interval
(vmin, vmax)¶tick_values
(vmin, vmax)¶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)¶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: 


replace
(**kwargs)¶Return new rrule with same attributes except for those attributes given new values by whichever keyword arguments are specified.
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 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 aritmetic
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 aritmetic operation on the original datetime value
with the information in the relativedelta.
weekday:
One of the weekday instances (MO, TU, etc). 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.
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 nonleap year day (jump leap days).
These are converted to day/month/leapdays information.
Here is the behavior of operations with relativedelta:
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. 

weeks
¶matplotlib.dates.
seconds
(s)¶Return seconds as days.
matplotlib.dates.
minutes
(m)¶Return minutes as days.
matplotlib.dates.
hours
(h)¶Return hours as days.
matplotlib.dates.
weeks
(w)¶Return weeks as days.