matplotlib命令与格式之tick坐标轴⽇期格式（设置⽇期主副
刻度）
1.横坐标设置时间格式
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
# 配置横坐标为⽇期格式
例⼦:
from datetime import datetime
import matplotlib.dates as mdates
import 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
# Plot
plt.plot(xs, ys)
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
: locate minutes（f）
: locate hours
: locate specified days of the month
: Locate days of the week, e.g., MO, TU
: locate months, e.g., 7 for july
: locate years that are multiples of base
: locate using a ulewrapper. The rrulewrapper is a simple wrapper ule () which allow almost arbitrary date tick specifications. See .
:
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 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))
# tick on mondays every second week
loc = 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
matplotlib中subplot
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 _xticklabels(): label.set_rotation(30) label.set_horizontalalignment('right')
(3)例⼦
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from 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')
#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 plt
import numpy as np
import matplotlib as mpl
import 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()
以上就是本⽂的全部内容，希望对⼤家的学习有所帮助，也希望⼤家多多⽀持。

版权声明：本站内容均来自互联网，仅供演示用，请勿用于商业和其他非法用途。如果侵犯了您的权益请与我们联系QQ:729038198，我们将在24小时内删除。