如何在matplotlib中设置两个时间格式器? [英] How to set two time formatters in matplotlib?
问题描述
此图表是由Excel构建的.如何使用matplotlib做同样的事情?
This chart is built by Excel. How can I do the same using matplotlib?
我的意思是如何添加两个格式化程序:
I mean how to add two formatters:
- 年
- 个月.
现在我使用这样的东西:
Now i use something like this:
fig, ax = plt.subplots(1,1)
ax.margins(x=0)
ax.plot(list(df['Date']), list(df['Value']), color="g")
ax.xaxis.set_major_locator(matplotlib.dates.YearLocator())
ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%Y'))
plt.text(df["Date"].iloc[-1], df["Value"].iloc[-1], df["Value"].iloc[-1])
plt.title(title)
plt.get_current_fig_manager().full_screen_toggle()
plt.grid(axis = 'y')
plt.savefig('pict\\'+sheet.cell_value(row,1).split(',')[0]+'.png', dpi=300, format='png')
#plt.show()
plt.close(fig)
它绘制:
推荐答案
对于 year 标签，应使用辅助轴，对于 month 标签，应使用辅助轴..您可以使用以下内容生成辅助轴:
You should use a secondary axis for the year labels, while using the primary for the month label. You can generate a secondary axis with something like:
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import host_subplot
import mpl_toolkits.axisartist as AA
import matplotlib.dates as md
fig = plt.figure()
months = host_subplot(111, axes_class = AA.Axes, figure = fig)
plt.subplots_adjust(bottom = 0.1)
years = months.twiny()
然后，您应使用以下命令将辅助轴移至底部:
Then you should move the secondary axis to the bottom with:
offset = -20
new_fixed_axis = years.get_grid_helper().new_fixed_axis
years.axis['bottom'] = new_fixed_axis(loc = 'bottom',
axes = years,
offset = (0, offset))
最后绘制并使用 md.MonthLocator 和 md.YearLocator 调整主轴和辅助轴的格式.像这样的东西应该没问题:
Finally you plot and then adjust the primary and secondary axes format with md.MonthLocator and md.YearLocator. Something like this should be fine:
months.xaxis.set_major_locator(md.MonthLocator(interval = 1)
months.xaxis.set_major_formatter(md.DateFormatter('%B'))
months.set_xlim([df['Date'].iloc[0], df['Date'].iloc[-1]])
years.xaxis.set_major_locator(md.YearLocator(interval = 1))
years.xaxis.set_major_formatter(md.DateFormatter('%H'))
years.set_xlim([df['Date'].iloc[0], df['Date'].iloc[-1]])
尝试检查以下两个答案，使这些代码适合您的情况应该不难:
Try to check these two answers, it should not be difficult to adapt those codes to your case:
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