我正试图在带有子图的 Pandas 图中遮蔽 Spring 月份。但它只是对最后一个子图进行着色。我如何让它遮蔽所有地 block ?
我使用 axvspan
在每年的 4 月 1 日到 6 月 30 日之间循环访问这些结束日期的分组数据帧。
这是结果。
import matplotlib.pyplot as plt
recent = daily[daily.Date.dt.year >= 2000]
# Get only April 1 and Jume 30 each year
spring_months = recent[((recent.Date.dt.month == 4) & (recent.Date.dt.day == 1)) | ( (recent.Date.dt.month == 6) & (recent.Date.dt.day == 30) )]['Date']
# Make pivot table with data, one measuring station per column.
recent = recent.pivot(index='Date', columns='Station', values = 'Niveau(m)')
recent.plot(figsize=[7,50], subplots=True)
plt.xlim(xmax='2017-07-10')
# Group the spring end-dates by year
years = spring_months.drop_duplicates().groupby(spring_months.dt.year)
# Loop through groups and add axvspan between April 1 and June 30 each year
for n, g in years:
plt.axvspan(g.iloc[0], g.iloc[1], facecolor='g', alpha=0.5)
if g.iloc[0].year == 2016:
break
最佳答案
使用尽可能多的代码,我修改了一点以伪造数据集。关键是使用 ax = df.plot...
语句捕获子图的轴句柄。
然后您可以使用列表推导式遍历所有轴并绘制 axvspan。
创建数据集:
ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index, columns=list('ABCD'))
df1 = df.rename_axis('date').reset_index()
import matplotlib.pyplot as plt
recent = df1[df1.date.dt.year >= 2000]
# Get only April 1 and Jume 30 each year
spring_months = df1[((df1.date.dt.month == 4) & (df1.date.dt.day == 1)) | ( (df1.date.dt.month == 6) & (df1.date.dt.day == 30) )]['date']
# Make pivot table with data, one measuring station per column.
#recent = recent.pivot(index='Date', columns='Station', values = 'Niveau(m)')
获取所有轴的句柄:
ax = df.plot(subplots=True, figsize=(6,6))
# Group the spring end-dates by year
years = spring_months.drop_duplicates().groupby(spring_months.dt.year)
通过列表理解遍历所有轴以绘制轴跨度
# Loop through groups and add axvspan between April 1 and June 30 each year
for n, g in years:
[i.axvspan(g.iloc[0], g.iloc[1], facecolor='g', alpha=0.5) for i in ax]
if g.iloc[0].year == 2016:
break
关于python - Pandas :将 axvspan 应用于所有子图,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/43725794/