old_contents: import matplotlib.pylab as plt
  import pandas as pd
  from matplotlib.dates import DateFormatter
  
  data_path = "/Users/jaredbowden/Google Drive/cave_in_a_lake/data/"
  
  dateparse = lambda x: pd.datetime.strptime(x, '%Y/%d/%m %H:%M:%S')
  
  raw_data = pd.read_csv(data_path + "speed_frame.csv",
                         parse_dates=['Time'],
                         date_parser=dateparse)
  
  temp_color = []
  
  for line in raw_data["location"]:
  
      if line == "0":
  
          temp_color.append("grey")
  
      elif "Austin" in line:
  
          temp_color.append("green")
  
      else:
  
          temp_color.append("red")
  
  raw_data["temp_color"] = temp_color
  """
  raw_data["Time"] = pd.to_datetime(raw_data["Time"])
  
  plt.scatter(
      range(len(raw_data["Time"])),
      raw_data["Download"],
      color=raw_data["temp_color"],
      alpha=0.8)
  """
  
  # This is going to be a variation on the plotting option
  fig, ax = plt.subplots()
  
  ax.plot_date(x=raw_data["Time"],
               y=raw_data["Download"],
               alpha=0.8,
               color=raw_data["temp_color"])
  
  myFmt = DateFormatter('%b %G')
  ax.xaxis.set_major_formatter(myFmt)
  
  ax.autoscale_view()
  
  fig.autofmt_xdate()
  
  plt.title("Moontower Internet Speed")
  plt.xlabel("Time")
  plt.ylabel("Speed")
  
  plt.show()
  plt.close()
  
  # TODO add a histogram of speed. Would like to do things in a way that
  # makes a distinction between VPN and Time Warner.
  
  # TODO add some weekly and monthly summaries
  
new_contents: __author__ = "Jared B Bowden"
  __version__ = 1.2
  """
  Plot of internet speed
  """
  
  import matplotlib.pylab as plt
  import pandas as pd
  from matplotlib.dates import DateFormatter
  
  data_path = "/Users/jaredbowden/Google Drive/cave_in_a_lake/data/"
  
  dateparse = lambda x: pd.datetime.strptime(x, '%Y/%d/%m %H:%M:%S')
  
  raw_data = pd.read_csv(data_path + "speed_frame.csv",
                         parse_dates=['Time'],
                         date_parser=dateparse)
  
  location_tag = []
  
  for line in raw_data["location"]:
  
      if line == "0":
  
          location_tag.append("Empty")
  
      elif "Austin" in line:
  
          location_tag.append("Time Warner")
  
      else:
  
          location_tag.append("VPN")
  
  raw_data["location_tag"] = location_tag
  
  # Plot things up
  fig, ax = plt.subplots()
  
  location = ["Empty", "Time Warner", "VPN"]
  marker_color = ["0.75", "g", "r"]
  
  for color, plot_layer in enumerate(location):
      ax.plot_date(
          x=raw_data[raw_data["location_tag"] == plot_layer]["Time"],
          y=raw_data[raw_data["location_tag"] == plot_layer]["Download"],
          marker="o",
          fillstyle="full",
          linestyle='None',
          alpha=0.5,
          markeredgewidth=0.0,
          fmt=marker_color[color])
  
  myFmt = DateFormatter('%b %G')
  ax.xaxis.set_major_formatter(myFmt)
  
  ax.autoscale_view()
  
  fig.autofmt_xdate()
  
  plt.title("Moontower Internet Speed")
  plt.xlabel("Time")
  plt.ylabel("Speed")
  
  plt.show()
  plt.close()
  
  # TODO add a histogram of speed. Would like to do things in a way that
  # makes a distinction between VPN and Time Warner.
  
  # TODO add some weekly and monthly summaries
  
subject: Clean up formatting