matplotlib & pandas

Python/matplotlab/gallery/text_labels_and_annotations/date.md

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+# 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](https://matplotlib.org/api/dates_api.html#matplotlib.dates.date2num) 和[matplotlib.dates.num2date](https://matplotlib.org/api/dates_api.html#matplotlib.dates.num2date)。这些可以在[datetime.datetime](https://docs.python.org/3/library/datetime.html#datetime.datetime) 对象和 ``numpy.datetime64`` 对象之间进行转换。
+
+![日期刻度标签示例](https://matplotlib.org/_images/sphx_glr_date_001.png)
+
+```python
+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
+            
+- [下载python源码: date.py](https://matplotlib.org/_downloads/date.py)
+- [下载Jupyter notebook: date.ipynb](https://matplotlib.org/_downloads/date.ipynb)