Sau*_*rav 4 python matplotlib pandas
如何1st Lockdown, 2nd Lockdown像 Plotly 一样在 Matplotlib 中添加注释文本示例?
这是一个使用 的示例ax.annotate,正如另一个答案所建议的那样:
import matplotlib.pyplot as plt
import pandas as pd
dr = pd.date_range('02-01-2020', '07-01-2020', freq='1D')
y = pd.Series(range(len(dr))) ** 2
fig, ax = plt.subplots()
ax.plot(dr, y)
ax.annotate('1st Lockdown',
xy=(dr[50], y[50]), #annotate the 50th data point; you could select this in a better way
xycoords='data', #the xy we passed refers to the data
xytext=(0, 100), #where we put the text relative to the xy
textcoords='offset points', #what the xytext coordinates mean
arrowprops=dict(arrowstyle="->"), #style of the arrow
ha='center') #center the text horizontally
ax.annotate('2nd Lockdown',
xy=(dr[100], y[100]), xycoords='data',
xytext=(0, 100), textcoords='offset points',
arrowprops=dict(arrowstyle="->"), ha='center')
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annotate有很多选项,所以我会寻找一个与您想要做的事情相匹配的示例,然后尝试遵循它。
注释似乎是在 中执行此操作的“智能”方式matplotlib;您也可以只使用axvlineand text,但您可能需要添加额外的格式以使事情看起来更好:
import matplotlib.pyplot as plt
import pandas as pd
dr = pd.date_range('02-01-2020', '07-01-2020', freq='1D')
y = pd.Series(range(len(dr))) ** 2
fig, ax = plt.subplots()
ax.plot(dr, y)
ax.axvline(dr[50], ymin=0, ymax=.7, color='gray')
ax.text(dr[50], .7, '1st Lockdown', transform=ax.get_xaxis_transform(), color='gray')
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