Formatting of DateTimeIndex in plot pandas

问题:

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.

回答1:

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]) 

文章来源: Formatting of DateTimeIndex in plot pandas