pandas 中的时间序列绘图不一致 [英] Time-series plotting inconsistencies in Pandas
问题描述
说我有一个数据框df
,其中df.index
由datetime
个对象组成,例如
Say I have a dataframe df
where df.index
consists of datetime
objects, e.g.
> df.index[0]
datetime.date(2014, 5, 5)
如果我将其绘制,Pandas会很好地保留图中的datetime
类型,这使用户可以更改时间序列采样以及该图的格式设置选项:
If I plot it Pandas nicely preserves the datetime
type in the plot, which allows the user to change the time-series sampling as well formatting options of the plot:
# Plot the dataframe:
f = plt.figure(figsize=(8,8))
ax = f.add_subplot(1,1,1)
lines = df.plot(ax=ax)
# Choose the sampling rate in terms of dates:
ax.xaxis.set_major_locator(matplotlib.dates.WeekdayLocator(byweekday=(0,1,2,3,4,5,6),
interval=1))
# We can also re-sample the X axis numerically if we want (e.g. every 4 steps):
N = 4
ticks = ax.xaxis.get_ticklocs()
ticklabels = [l.get_text() for l in ax.xaxis.get_ticklabels()]
ax.xaxis.set_ticks(ticks[-1::-N][::-1])
ax.xaxis.set_ticklabels(ticklabels[-1::-N][::-1])
# Choose a date formatter using a date-friendly syntax:
ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%b\n%d'))
plt.show()
但是,以上内容对于boxplot
无效(
However, the above does not work for a boxplot
(the tick labels for the x axis are rendered empty)
:
df2.boxplot(column='A', by='created_dt',ax=ax, sym="k.")
# same code as above ...
在上一个示例中,Pandas似乎将x轴标签转换为 string 类型,因此格式化程序和定位器不再起作用.
It looks like in the last example, Pandas converts the x-axis labels into string type, so the formatter and locators don't work anymore.
这篇文章重用了以下线程的解决方案:
This post re-uses solutions from the following threads:
- Accepted answer to Pandas timeseries plot setting x-axis major and minor ticks and labels
- Accepted answer to Pandas: bar plot xtick frequency
为什么?如何以允许我使用matplotlib
日期定位符和格式化程序的方式使用boxplot
?
Why? How can I use boxplot
in a way that allows me to use matplotlib
date locators and formatters?
推荐答案
不,实际上即使是折线图也无法正常工作,如果显示年份,您会注意到问题所在:而不是下面的2000例如,小提琴是在1989年.
No, actually even the line plot is not working correctly, if you have the year show up, you will notice the problem: instead of being 2000 in the following example, the xticks are in 1989.
In [49]:
df=pd.DataFrame({'Val': np.random.random(50)})
df.index=pd.date_range('2000-01-02', periods=50)
f = plt.figure()
ax = f.add_subplot(1,1,1)
lines = df.plot(ax=ax)
ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%y%b\n%d'))
print ax.get_xlim()
(10958.0, 11007.0)
In [50]:
matplotlib.dates.strpdate2num('%Y-%M-%d')('2000-01-02')
Out[50]:
730121.0006944444
In [51]:
matplotlib.dates.num2date(730121.0006944444)
Out[51]:
datetime.datetime(2000, 1, 2, 0, 1, tzinfo=<matplotlib.dates._UTC object at 0x051FA9F0>)
结果日期时间数据在pandas
和matplotlib
中的处理方式不同:在后者中,2000-1-2
应该是730121.0006944444
,而不是pandas
Turns out datetime data is handled differently in pandas
and matplotlib
: in the latter, 2000-1-2
should be 730121.0006944444
, instead of 10958.0
in pandas
为正确起见,我们需要避免使用pandas
的plot
方法:
To get it right we need to avoid using pandas
's plot
method:
In [52]:
plt.plot_date(df.index.to_pydatetime(), df.Val, fmt='-')
ax=plt.gca()
ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%y%b\n%d'))
与barplot
类似:
In [53]:
plt.bar(df.index.to_pydatetime(), df.Val, width=0.4)
ax=plt.gca()
ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('%y%b\n%d'))
这篇关于 pandas 中的时间序列绘图不一致的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!