# 日期刻度标签

演示如何使用日期刻度定位器和格式化程序在matplotlib中创建日期图。有关控制主要和次要刻度的更多信息,请参阅major_minor_demo1.py

所有matplotlib日期绘图都是通过将日期实例转换为自 0001-01-01 00:00:00 UTC 加上一天后的天数(由于历史原因)来完成的。 转换,刻度定位和格式化是在幕后完成的,因此这对您来说是最透明的。 日期模块提供了几个转换器函数 matplotlib.dates.date2num (opens new window)matplotlib.dates.num2date (opens new window)。这些可以在datetime.datetime (opens new window) 对象和 numpy.datetime64 对象之间进行转换。

日期刻度标签示例

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import matplotlib.cbook as cbook

years = mdates.YearLocator()   # every year
months = mdates.MonthLocator()  # every month
yearsFmt = mdates.DateFormatter('%Y')

# Load a numpy record array from yahoo csv data with fields date, open, close,
# volume, adj_close from the mpl-data/example directory. The record array
# stores the date as an np.datetime64 with a day unit ('D') in the date column.
with cbook.get_sample_data('goog.npz') as datafile:
    r = np.load(datafile)['price_data'].view(np.recarray)

fig, ax = plt.subplots()
ax.plot(r.date, r.adj_close)

# format the ticks
ax.xaxis.set_major_locator(years)
ax.xaxis.set_major_formatter(yearsFmt)
ax.xaxis.set_minor_locator(months)

# round to nearest years...
datemin = np.datetime64(r.date[0], 'Y')
datemax = np.datetime64(r.date[-1], 'Y') + np.timedelta64(1, 'Y')
ax.set_xlim(datemin, datemax)


# format the coords message box
def price(x):
    return '$%1.2f' % x
ax.format_xdata = mdates.DateFormatter('%Y-%m-%d')
ax.format_ydata = price
ax.grid(True)

# rotates and right aligns the x labels, and moves the bottom of the
# axes up to make room for them
fig.autofmt_xdate()

plt.show()

# 下载这个示例