title: autoscaling in matplotlib, plotting different time series in same chart
body: <p>I have a 'master' panda dataframe that has a time series of 'polarity' values for several terms. I want to work with 4 of them, so I extracted 4 separate dataframes, containing the time series(same time series for all of the terms, but different polarity values.)</p>
  
  <p>I plotted them in 4 separate matplotlib graphs, using the code below</p>
  
  <pre><code>fig, axes = plt.subplots(nrows=2, ncols=2)
  polarity_godzilla.plot(ax=axes[0,0]); axes[0,0].set_title('Godzilla')
  polarity_henry_kissinger.plot(ax=axes[0,1]); axes[0,1].set_title('Henry Kissinger')
  polarity_bmwi.plot(ax=axes[1,0]); axes[1,0].set_title('BMWi')
  polarity_duran_duran.plot(ax=axes[1,1]); axes[1,1].set_title('Duran Duran')
  </code></pre>
  
  <p>Now, I want to graph them all in the same graph so I have an idea of the magnitude of each graph, because the auto scaling of matplotlib can give the wrong impression about the magnitude by just looking at the graphs.
  <img src="https://i.stack.imgur.com/5K9Zr.png" alt="enter image description here"></p>
  
  <p>Two questions:
  1) Is there are way to set the min and max values of the Y-axis when plotting? 
  2) I am not an expert in matplotlib, so I am not sure how to plot the 4 variables in the same graph using different colors, markers, labels, etc. I tried nrows = 1, ncols = 1 but can't plot anything.</p>
  
  <p>Thank you</p>