我创建了一个类似于
我有几个问题:
以下是用于生成此图的代码
Following is the code used to generate this plot
ax4=df4.plot(kind='bar',stacked=True,title='Mains 1 Breakdown');
ax4.set_ylabel('Power (W)');
idx_weekend=df4.index[df4.index.dayofweek>=5]
ax.bar(idx_weekend.to_datetime(),[1800 for x in range(10)])
ax.bar
专门用于突出显示周末,但它不会产生任何可见的输出.(问题 1)对于问题 2,我尝试使用 Major Formatter 和 Locators,代码如下:
The ax.bar
is specifically for highlighting weekends, but it does not produce any visible output. (Problem 1)
For Problem 2 i tried to use Major Formatter and Locators, the code is as follows:
ax4=df4.plot(kind='bar',stacked=True,title='Mains 1 Breakdown');
ax4.set_ylabel('Power (W)');
formatter=matplotlib.dates.DateFormatter('%d-%b');
locator=matplotlib.dates.DayLocator(interval=1);
ax4.xaxis.set_major_formatter(formatter);
ax4.xaxis.set_major_locator(locator);
产生的输出如下:
了解 Dataframe 的样子可能会有所帮助
It may be helpful to know what the Dataframe looks like
In [122]:df4
Out[122]:
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 36 entries, 2011-04-19 00:00:00 to 2011-05-24 00:00:00
Data columns:
(0 to 6 AM) Dawn 19 non-null values
(12 to 6 PM) Dusk 19 non-null values
(6 to 12 Noon) Morning 19 non-null values
(6PM to 12 Noon) Night 20 non-null values
dtypes: float64(4)
我尝试了很多,现在这些技巧有效.等待更 Pythonic 和一致的解决方案.标注问题的解决方案:
I tried a lot and for now these hacks work. Await a more Pythonic and consistent solutions. Solution to labeling problems:
def correct_labels(ax):
labels = [item.get_text() for item in ax.get_xticklabels()]
days=[label.split(" ")[0] for label in labels]
months=["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"]
final_labels=[]
for i in range(len(days)):
a=days[i].split("-")
final_labels.append(a[2]+"
"+months[int(a[1])-1])
ax.set_xticklabels(final_labels)
另外,在绘图时,我进行了以下更改
Also while plotting i make the following change
ax=df.plot(kind='bar',rot=0)
这会使标签旋转为 0.
This makes the labels at 0 rotation.
为了找到周末并突出显示它们,我编写了以下两个函数:
For finding weekends and highlighting them, i wrote the following two functions:
def find_weekend_indices(datetime_array):
indices=[]
for i in range(len(datetime_array)):
if datetime_array[i].weekday()>=5:
indices.append(i)
return indices
def highlight_weekend(weekend_indices,ax):
i=0
while i<len(weekend_indices):
ax.axvspan(weekend_indices[i], weekend_indices[i]+2, facecolor='green', edgecolor='none', alpha=.2)
i+=2
现在,该图看起来更加有用,并且涵盖了这些用例.
Now, the plot looks much more useful and covers these use cases.
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