title: Broken y-axis from 0 to value-start with matplotlib and pandas data
body: <p>My sample data start with values beginning with 700 so that there is nothing between 0 and 700. I want to cut that range out of the line plot but I also want to point the reader to that cut by visualizing it like this.
  This example picture is manipulated via a drawing software just to explain what I want.</p>
  <p><a href="https://i.stack.imgur.com/Pd77z.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Pd77z.png" alt="enter image description here" /></a></p>
  <p>Something like this is explained in the <a href="https://matplotlib.org/stable/gallery/subplots_axes_and_figures/broken_axis.html" rel="nofollow noreferrer">matplotlib documentation</a>. But I do not understand what happens there in the example code. And I am not sure if it fits to my case because the example cutting data. And I just want to cut the area where is no data present.</p>
  <p>Here is a minimal working example producing line figure where the y-axis starts at 700 not 0. Can we start from here?</p>
  <pre><code>#!/usr/bin/env python3
  import random as rd
  import matplotlib.pyplot as plt
  import pandas as pd
  
  # version info
  print(pd.__version__)  # 1.2.5
  print(matplotlib.__version__)  # 3.5.1
  print(plt.get_backend())  # TkAgg
  
  # sample data
  rd.seed(0)
  data = [rd.sample(range(700, 850), 12) for i in range(3)]
  df = pd.DataFrame(data)
  
  # not sure if this is a usual maptlotlib/pyplot approach to
  # simply plot three lines
  fig, (ax) = plt.subplots(1, 1)
  for row in range(3):
      ax.plot(df.iloc[row])
  
  # limit range of y-axis to the data only
  ax.set_ylim(bottom=650,
              top=900)
  
  plt.show()
  </code></pre>
  <p>That is the result.</p>
  <p><a href="https://i.stack.imgur.com/1D0gI.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/1D0gI.png" alt="enter image description here" /></a></p>
  <p>By the way: I am also often confused by all the matplotlib based approaches how to draw figures; there are submodules (pyplot, ...) and pandas itself have an API (<code>pandas.DataFrame.plot()</code>). It is hard bringing this together and to decide where to start.</p>