日期时间表的格式化 [英] Formatting of DateTimeIndex in plot pandas

问题描述

例如：

$ b $我无法解密文件，用于更改蝙蝠频率和日期格式的大熊猫。 b

  import numpy as np 
 import pandas as pd 
 import pandas.io.data as web 
 import matplotlib as mpl 
％ matplotlib inline 
 
 mpl.style.use（'ggplot'）
 mpl.rcParams ['figure.figsize'] =（8,6）
 
＃grab一些价格数据
 px = web.DataReader（'AAPL'，yahoo，'2010-12-01'）['Adj Close'] 
 px_m = px.asfreq（'M' ='ffill'）
 rets_m = px_m.pct_change（）
 
 rets_m.plot（kind ='bar'）
  

生成此图：

Yikes。如何让每一个季度或每季度有所？？？日期格式如何改变以摆脱时间？

我已经尝试过各种各样的东西与 ax.set_xticks（）和 ax.xaxis.set_major_formatter ，但无法弄清楚。

解决方案

如果您在 pandas 中使用 plot 方法， set_major_locator 和 set_major_formatter 方法 matplotlib 很可能

I'm having trouble deciphering the documentation for changing tick frequency and date formatting with pandas.

For example:

import numpy as np
import pandas as pd
import pandas.io.data as web
import matplotlib as mpl
%matplotlib inline

mpl.style.use('ggplot')
mpl.rcParams['figure.figsize'] = (8,6)

# grab some price data
px = web.DataReader('AAPL', "yahoo", '2010-12-01')['Adj Close']
px_m = px.asfreq('M', method='ffill')
rets_m = px_m.pct_change()

rets_m.plot(kind='bar')

generates this plot:

Yikes. How can I get the ticks to be every month or quarter or something sensible? And how can the date formatting be changed to get rid of times?

I've tried various things with ax.set_xticks() and ax.xaxis.set_major_formatter but haven't been able to figure it out.

解决方案

If you use the plot method in pandas, the set_major_locator and set_major_formatter methods of matplotlib is likely to fail. It might just be easier to manually adjust the ticks, if you want to stay with pandas``plot methods.

#True if it is the first month of a quarter, False otherwise
xtick_idx = np.hstack((True, 
                       np.diff(rets_m.index.quarter)!=0))

#Year-Quarter string for the tick labels.
xtick     = ['{0:d} quarter {1:d}'.format(*item) 
             for item in zip(rets_m.index.year, rets_m.index.quarter)]
ax        =rets_m.plot(kind='bar')

#Only put ticks on the 1st months of each quarter
ax.xaxis.set_ticks(np.arange(len(xtick))[xtick_idx])

#Adjust the ticklabels
ax.xaxis.set_ticklabels(np.array(xtick)[xtick_idx])

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