更改轴子图的 X 刻度
Change X ticks for axes subplot
我正在尝试设置轴子图的 x 刻度，但它对我不起作用。
现在我有以下数据框：
Data Frame
我正在使用以下代码绘制此图：
ax=predictions.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
ax
结果如下：
Plot
如您所见，8 月写为 2021 年 8 月。我希望能够将所有 x 刻度更改为仅月份或年份月份（例如，保留 7 月或设置 2021 年 7 月)
我一直在尝试使用 ax.set_xticks ，但到目前为止它对我不起作用。
提前致谢！
不要将 predictions.plot() 输出保存到 ax。您只会得到一个行列表。实施下面的解决方案后，您可以使用 plt.show().
查看输出
处理 datetime 对象的日期时
对于带有 'Jul 2021'、'Aug 2021' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{date.strftime("%b")} {date.strftime("%Y")}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
对于带有 'Jul 21'、'Aug 21' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{date.strftime("%b")} {date.strftime("%y")}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
对于带有 'Jul'、'Aug' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{date.strftime("%b")}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
处理 str 个对象的日期时
对于带有 'Jul 2021'、'Aug 2021' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{(datetime.datetime.strptime(date, "%Y-%m-%d")).strftime("%b")} {datetime.datetime.strptime(date, "%Y-%m-%d").year}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
对于带有 'Jul 21'、'Aug 21' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{(datetime.datetime.strptime(date, "%Y-%m-%d")).strftime("%b")} {datetime.datetime.strptime(date, "%Y-%m-%d").strftime("%y")}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
对于带有 'Jul'、'Aug' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{(datetime.datetime.strptime(date, "%Y-%m-%d")).strftime("%b")}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
我正在尝试设置轴子图的 x 刻度，但它对我不起作用。 现在我有以下数据框：
Data Frame
我正在使用以下代码绘制此图：
ax=predictions.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
ax
结果如下：
Plot
如您所见，8 月写为 2021 年 8 月。我希望能够将所有 x 刻度更改为仅月份或年份月份（例如，保留 7 月或设置 2021 年 7 月)
我一直在尝试使用 ax.set_xticks ，但到目前为止它对我不起作用。
提前致谢！
不要将 predictions.plot() 输出保存到 ax。您只会得到一个行列表。实施下面的解决方案后，您可以使用 plt.show().
处理 datetime 对象的日期时
对于带有 'Jul 2021'、'Aug 2021' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{date.strftime("%b")} {date.strftime("%Y")}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
对于带有 'Jul 21'、'Aug 21' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{date.strftime("%b")} {date.strftime("%y")}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
对于带有 'Jul'、'Aug' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{date.strftime("%b")}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
处理 str 个对象的日期时
对于带有 'Jul 2021'、'Aug 2021' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{(datetime.datetime.strptime(date, "%Y-%m-%d")).strftime("%b")} {datetime.datetime.strptime(date, "%Y-%m-%d").year}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
对于带有 'Jul 21'、'Aug 21' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{(datetime.datetime.strptime(date, "%Y-%m-%d")).strftime("%b")} {datetime.datetime.strptime(date, "%Y-%m-%d").strftime("%y")}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot
对于带有 'Jul'、'Aug' 等的标签，使用
import datetime
import matplotlib.pyplot as plt # Matplotlib.pyplot object
# Please note that df is a DataFrame object. Substitute your DataFrame object's name below.
dates_index = df.index
# You can use df.index in the list comprehension as well as in the plt.plot and plt.xticks operations as an alternative to dates_index.
labels = [f'{(datetime.datetime.strptime(date, "%Y-%m-%d")).strftime("%b")}' for date in dates_index]
print(labels)
plt.plot(y=['Actual','add_add','add_mul','mul_add','mul_mul','Philips'],figsize=(5,4),
legend=True,color=['b','r','g','m','y','black'],ylabel='Quantity',xlabel='Date')
plt.xticks(dates_index, labels)
plt.show() # Visualize the plot