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POPandas timeseries plot setting x-axis major and minor ticks and labels
 

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  1. POPandas timeseries plot setting x-axis major and minor ticks and labels
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    <p>I want to be able to set the major and minor xticks and their labels for a time series graph plotted from a Pandas time series object. </p> <p>The Pandas 0.9 "what's new" page says: </p> <blockquote> <p>"you can either use to_pydatetime or register a converter for the Timestamp type"</p> </blockquote> <p>but I can't work out how to do that so that I can use the matplotlib <code>ax.xaxis.set_major_locator</code> and <code>ax.xaxis.set_major_formatter</code> (and minor) commands.</p> <p>If I use them without converting the pandas times, the x-axis ticks and labels end up wrong.</p> <p>By using the 'xticks' parameter I can pass the major ticks to pandas.plot, and then set the major tick labels. I can't work out how to do the minor ticks using this approach. (I can set the labels on the default minor ticks set by pandas.plot)</p> <p>Here is my test code:</p> <pre class="lang-py prettyprint-override"><code>import pandas print 'pandas.__version__ is ', pandas.__version__ print 'matplotlib.__version__ is ', matplotlib.__version__ dStart = datetime.datetime(2011,5,1) # 1 May dEnd = datetime.datetime(2011,7,1) # 1 July dateIndex = pandas.date_range(start=dStart, end=dEnd, freq='D') print "1 May to 1 July 2011", dateIndex testSeries = pandas.Series(data=np.random.randn(len(dateIndex)), index=dateIndex) ax = plt.figure(figsize=(7,4), dpi=300).add_subplot(111) testSeries.plot(ax=ax, style='v-', label='first line') # using MatPlotLib date time locators and formatters doesn't work with new # pandas datetime index ax.xaxis.set_minor_locator(matplotlib.dates.WeekdayLocator(byweekday=(1), interval=1)) ax.xaxis.set_minor_formatter(matplotlib.dates.DateFormatter('%d\n%a')) ax.xaxis.grid(True, which="minor") ax.xaxis.grid(False, which="major") ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter('\n\n\n%b%Y')) plt.show() # set the major xticks and labels through pandas ax2 = plt.figure(figsize=(7,4), dpi=300).add_subplot(111) xticks = pandas.date_range(start=dStart, end=dEnd, freq='W-Tue') print "xticks: ", xticks testSeries.plot(ax=ax2, style='-v', label='second line', xticks=xticks.to_pydatetime()) ax2.set_xticklabels([x.strftime('%a\n%d\n%h\n%Y') for x in xticks]); # set the text of the first few minor ticks created by pandas.plot # ax2.set_xticklabels(['a','b','c','d','e'], minor=True) # remove the minor xtick labels set by pandas.plot ax2.set_xticklabels([], minor=True) # turn the minor ticks created by pandas.plot off # plt.minorticks_off() plt.show() print testSeries['6/4/2011':'6/7/2011'] </code></pre> <p>and its output:</p> <pre><code>pandas.__version__ is 0.9.1.dev-3de54ae matplotlib.__version__ is 1.1.1 1 May to 1 July 2011 &lt;class 'pandas.tseries.index.DatetimeIndex'&gt; [2011-05-01 00:00:00, ..., 2011-07-01 00:00:00] Length: 62, Freq: D, Timezone: None </code></pre> <p><img src="https://i.stack.imgur.com/8ndjM.png" alt="Graph with strange dates on xaxis"></p> <pre><code>xticks: &lt;class 'pandas.tseries.index.DatetimeIndex'&gt; [2011-05-03 00:00:00, ..., 2011-06-28 00:00:00] Length: 9, Freq: W-TUE, Timezone: None </code></pre> <p><img src="https://i.stack.imgur.com/hQy8v.png" alt="Graph with correct dates"></p> <pre><code>2011-06-04 -0.199393 2011-06-05 -0.043118 2011-06-06 0.477771 2011-06-07 -0.033207 Freq: D </code></pre> <p><strong>Update:</strong> I've been able to get closer to the layout I wanted by using a loop to build the major xtick labels:</p> <pre><code># only show month for first label in month month = dStart.month - 1 xticklabels = [] for x in xticks: if month != x.month : xticklabels.append(x.strftime('%d\n%a\n%h')) month = x.month else: xticklabels.append(x.strftime('%d\n%a')) </code></pre> <p>However, this is a bit like doing the x-axis using <code>ax.annotate</code>: possible but not ideal.</p>
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    1. USJoel Aufrecht
    1. USbrenda
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    1. COI know this doesn't really answer the question, but as a general approach when I really care about how a plot looks, I generally just try to get a vector version of it and make it look nice in Illustrator or Inkscape. I've found most other people I know seem to do the same.
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      1. USJohn McDonnell
    2. COCan you just totally ignore the arguments to the pandas `plot` function and set all the ticks after plotting, by using matplotlib methods of the returned `ax` object (e.g., `ax.set_xticks`)?
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      1. POPandas timeseries plot setting x-axis major and minor ticks and labels
      1. USBrenBarn
    3. CO@BrenBarn I couldn't figure out how to get the date as a python date instead of a pandas datetime for the matplotlib methods. The answer by bmu fixes that by converting the dates before plotting.
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      1. USbrenda
 

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