matplotlib命令与格式之tick坐标轴日期格式(设置日期主副刻度)

技术  /  管理员 发布于 7年前   472

1.横坐标设置时间格式

import matplotlib.pyplot as pltimport matplotlib.dates as mdates# 配置横坐标为日期格式plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y/%m/%d'))plt.gca().xaxis.set_major_locator(mdates.DayLocator())

例子:

from datetime import datetimeimport matplotlib.dates as mdatesimport matplotlib.pyplot as plt# 生成横纵坐标信息dates = ['01/02/1991', '01/03/1991', '01/04/1991']xs = [datetime.strptime(d, '%m/%d/%Y').date() for d in dates]ys = range(len(xs))# 配置横坐标plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%m/%d/%Y'))plt.gca().xaxis.set_major_locator(mdates.DayLocator())# Plotplt.plot(xs, ys)plt.gcf().autofmt_xdate() # 自动旋转日期标记plt.show()

2.设置日期坐标轴主副刻度值

所有坐标轴日期格式类型

MinuteLocator: locate minutes（f）

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 matplotlib.dates.rrulewrapper. The rrulewrapper 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 best MultipleDateLocator to set the view limits and the tick locations.

(1)获取坐标轴日期格式类型

from matplotlib.dates import DateFormatter, WeekdayLocator, DayLocator, MONDAY,YEARLY#获取每月一日数据monthdays = MonthLocator()#获取每周一的日期数据mondays = WeekdayLocator(MONDAY)#获取每日数据alldays = DayLocator()# import constants for the days of the weekfrom matplotlib.dates import MO, TU, WE, TH, FR, SA, SU# tick on mondays every weekloc = WeekdayLocator(byweekday=MO, tz=tz)# tick on mondays and saturdaysloc = WeekdayLocator(byweekday=(MO, SA))# tick on mondays every second weekloc = WeekdayLocator(byweekday=MO, interval=2)# tick every 5th easter(每隔5个选1个)rule = rrulewrapper(YEARLY, byeaster=1, interval=5)loc = RRuleLocator(rule)

(2)设置坐标轴日期格式

#设置主副刻度ax.xaxis.set_major_locator(mondays)ax.xaxis.set_minor_locator(alldays)#设置坐标轴刻度标签格式mondayFormatter = DateFormatter('%Y-%m-%d') # 如：2-29-2015dayFormatter = DateFormatter('%d') # 如：12ax.xaxis.set_major_formatter(mondayFormatter)#字符串旋转for label in ax1.get_xticklabels(): label.set_rotation(30) label.set_horizontalalignment('right')

(3)例子

import matplotlib.pyplot as pltimport matplotlib.dates as mdatesfrom datetime import datetime #销售数据dates=[20171101,20171102,20171103,20171104]sales=[102.1,100.6,849,682]#将dates改成日期格式x= [datetime.strptime(str(d), '%Y%m%d').date() for d in dates] #figure布局fig=plt.figure(figsize=(8,4))ax1=fig.add_subplot(1,1,1) #绘图ax1.plot(x,y,ls='--',lw=3,color='b',marker='o',ms=6, mec='r',mew=2, mfc='w',label='业绩趋势走向')plt.gcf().autofmt_xdate() # 自动旋转日期标记 #设置x轴主刻度格式alldays = mdates.DayLocator()        #主刻度为每天ax1.xaxis.set_major_locator(alldays)     #设置主刻度ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y%m%d')) #设置副刻度格式hoursLoc = mpl.dates.HourLocator(interval=6) #为6小时为1副刻度ax1.xaxis.set_minor_locator(hoursLoc)ax1.xaxis.set_minor_formatter(mdates.DateFormatter('%H'))#参数pad用于设置刻度线与标签间的距离ax1.tick_params(pad=10) #显示图像plt.show()

3.设置日期时间刻度值

import matplotlib.pyplot as pltimport numpy as npimport matplotlib as mplimport datetime as dt fig = plt.figure()ax2 = fig.add_subplot(212)date2_1 = dt.datetime(2008,9,23)date2_2 = dt.datetime(2008,10,3)delta2 = dt.timedelta(days=1)dates2 = mpl.dates.drange(date2_1, date2_2, delta2)y2 = np.random.rand(len(dates2))ax2.plot_date(dates2, y2, linestyle='-')dateFmt = mpl.dates.DateFormatter('%Y-%m-%d')ax2.xaxis.set_major_formatter(dateFmt) daysLoc = mpl.dates.DayLocator()hoursLoc = mpl.dates.HourLocator(interval=6)ax2.xaxis.set_major_locator(daysLoc)ax2.xaxis.set_minor_locator(hoursLoc) fig.autofmt_xdate(bottom=0.18)fig.subplots_adjust(left=0.18) ax1 = fig.add_subplot(211)date1_1 = dt.datetime(2008, 9, 23)date1_2 = dt.datetime(2009, 2, 16)delta1 = dt.timedelta(days=10)dates1 = mpl.dates.drange(date1_1, date1_2, delta1)y1 = np.random.rand(len(dates1))ax1.plot_date(dates1, y1, linestyle='--')monthsLoc = mpl.dates.MonthLocator()weeksLoc = mpl.dates.WeekdayLocator()ax1.xaxis.set_major_locator(monthsLoc)ax1.xaxis.set_minor_locator(weeksLoc)monthsFmt = mpl.dates.DateFormatter('%b')ax1.xaxis.set_major_formatter(monthsFmt) plt.show()

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