使用pandas.DataFrame.plot方法时的Timeserie Datetick问题 [英] Timeserie datetick problems when using pandas.DataFrame.plot method

问题描述

当使用 pandas.DataFrame 的 plot 方法时，我刚刚发现了一些非常奇怪的东西.我正在使用熊猫 0.19.1 .这是我的MWE:

I just discovered something really strange when using plot method of pandas.DataFrame. I am using pandas 0.19.1. Here is my MWE:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas as pd

t = pd.date_range('1990-01-01', '1990-01-08', freq='1H')
x = pd.DataFrame(np.random.rand(len(t)), index=t)

fig, axe = plt.subplots()
x.plot(ax=axe)
plt.show(axe)

xt = axe.get_xticks()

当我尝试格式化我的xticklabel时，我得到奇怪的行为，然后我抽出了一些要理解的对象，发现了以下内容:

When I try to format my xticklabels I get strange beahviours, then I insepcted objects to understand and I have found the following:

• t [-1]-t [0] = Timedelta('7 days 00:00:00')，确认 DateTimeIndex 是我所期望的；
• xt = [175320，175488] ， xticks 是整数，但它们不等于自纪元以来的天数(我不知道它是什么是)；
• xt [-1]-xt [0] = 168 有更多类似的索引，与 len(x)= 169 相同.
li>

• t[-1] - t[0] = Timedelta('7 days 00:00:00'), confirming the DateTimeIndex is what I expect;
• xt = [175320, 175488], xticks are integers but they are not equals to a number of days since epoch (I do not have any idea about what it is);
• xt[-1] - xt[0] = 168 there are more like index, there is the same amount that len(x) = 169.

这说明了为什么我无法成功使用以下方式格式化斧头

This explains why I cannot succed to format my axe using:

axe.xaxis.set_major_locator(mdates.HourLocator(byhour=(0,6,12,18)))
axe.xaxis.set_major_formatter(mdates.DateFormatter("%a %H:%M"))

第一个引发一个错误，该错误产生的滴答声很多第二个显示我的第一个刻度是 Fri 00:00 ，但应该是 Mon 00:00 (实际上， matplotlib 假定第一个刻度为是 0481-01-03 00:00 ，哎呀，这是我的错误所在).

The first raise an error that there is to many ticks to generate The second show that my first tick is Fri 00:00 but it should be Mon 00:00 (in fact matplotlib assumes the first tick to be 0481-01-03 00:00, oops this is where my bug is).

在 pandas 和 matplotlib 整数到日期的转换之间似乎有些不兼容，但是我无法找到解决此问题的方法.

It looks like there is some incompatibility between pandas and matplotlib integer to date conversion but I cannot find out how to fix this issue.

如果我改为跑步:

fig, axe = plt.subplots()
axe.plot(x)
axe.xaxis.set_major_formatter(mdates.DateFormatter("%a %H:%M"))
plt.show(axe)

xt = axe.get_xticks()

一切正常，但是我错过了 pandas.DataFrame.plot 方法的所有出色功能，例如曲线标注等.这里的 xt = [726468.726475.] .

Everything works as expected but I miss all cool features from pandas.DataFrame.plot method such as curve labeling, etc. And here xt = [726468. 726475.].

如何使用 pandas.DataFrame.plot 方法而不是 axe.plot 正确设置刻度线格式，并避免出现此问题?

How can I properly format my ticks using pandas.DataFrame.plot method instead of axe.plot and avoiding this issue?

更新

问题似乎与用于日期表示的基础数字的来源和规模(单位)有关.无论如何，即使将其强制为正确的类型，我也无法控制它:

The problem seems to be about origin and scale (units) of underlying numbers for date representation. Anyway I cannot control it, even by forcing it to the correct type:

t = pd.date_range('1990-01-01', '1990-01-08', freq='1H', origin='unix', units='D')

matplotlib和熊猫表示形式之间存在差异.而且我找不到有关此问题的任何文档.

There is a discrepancy between matplotlib and pandas representation. And I could not find any documentation of this problem.

推荐答案

这是您要干的吗?请注意，我缩短了date_range以便于查看标签.

Is this what you are going for? Note I shortened the date_range to make it easier to see the labels.

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt 
import matplotlib.dates as dates

t = pd.date_range('1990-01-01', '1990-01-04', freq='1H')
x = pd.DataFrame(np.random.rand(len(t)), index=t)

# resample the df to get the index at 6-hour intervals
l = x.resample('6H').first().index

# set the ticks when you plot. this appears to position them, but not set the label
ax = x.plot(xticks=l)

# set the display value of the tick labels
ax.set_xticklabels(l.strftime("%a %H:%M"))
# hide the labels from the initial pandas plot
ax.set_xticklabels([], minor=True)
# make pretty
ax.get_figure().autofmt_xdate()

plt.show()

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