Python: Plot a graph with the same x-axis values

Question

Say that I have two lists:

yvalues = [30, 40, -20, 0, -10, 20, 45, 12, -5, ....]
Dates = ['20110103', '20110103', '20110103', '20110108', '20110108', '20110108', '20110113', '20110113', '20110113', ....]

The first entry in Dates does correspond to the first value in yvalues and so on. The dates repeat themselves because I observe multiple yvalues every 5 days.

Now if I want to plot the yvalues with Dates as x-axis, I do:

plt.plot(yvalues) 
plt.xticks(dates)

It gives me an error. If I try: plt.plot(Dates, yvalues), I get this nasty graph:

How can I plot on the x-axis the correct date values (i.e. 20110103) and without the straight lines that separates the observation?

UPDATE

I don't want my values to be plotted on the same vertical line for each day but one after the other. In fact there is 5 minutes time difference between each observations. I decided to convert my Dates list using:

Dates = [datetime.date(int(d[0:4]), int(d[4:6]), int(d[6:8])) for d in Dates]

Then I do:

plt.plot(dates, yvalues) 

and get the following plot:

Clearly, this picture shows the values on the same date to be on the same vertical lines. I still have the annoying straight lines that separate each dates.

Now if I don't use any dates as for the x-axis, I get the following graph (which is the one that I want but I want the x-axis as dates):

Sample dataset available here

Answer 1

Well after a bit of discussion, here's what i eventually landed on;

import datetime
import random
import numpy as np
import datetime
import itertools


dates, allSpillovers, allBins, allDigitised = [], [], [], []
with open("year.dat") as year:
  previousDate = None
  spillovers = []
  for line in year.readlines()[1:]:
    _, strdate, spillover = line.split(",")
    spillover = float(spillover)
    year, month, day = [int(i) for i in strdate.split("-")]

    date = datetime.date(year, month, day)

    if previousDate == date:
      spillovers.append(spillover)
    elif previousDate != None:
      mean = np.mean(spillovers)
      stdev = np.std(spillovers)

      spillovers.sort()
      if len(spillovers) > 70:
          allSpillovers.append([mean, mean-stdev, mean+stdev] + spillovers)
          dates.append(date)
      spillovers = []

    previousDate = date



#itertools.izip_longest(*allSpillovers, fillvalue=0)
allSpillovers = zip(*allSpillovers)


from matplotlib import pyplot

print len(dates), len(allSpillovers[0]), len(allSpillovers[1])

fig = pyplot.figure()
ax = fig.add_subplot(1,1,1)


for i in range(3, len(allSpillovers)-1):
  alpha = 0.5 - abs(i / float(len(allSpillovers)) - 0.5)
  print len(dates), len(allSpillovers[i]), len(allSpillovers[i+1])
  ax.fill_between(dates, allSpillovers[i], allSpillovers[i+1], facecolor='green', interpolate=True, alpha=alpha, linewidth=0)

#ax.fill_between(dates, allSpillovers[1], allSpillovers[2], facecolor='green', interpolate=True, alpha=0.5)

#for b, d in bins, digitised:



ax.plot(dates, allSpillovers[0], color="blue", linewidth=2)
ax.plot(dates, [0 for _ in dates], color="red", linewidth=2)
ax.grid()

fig.autofmt_xdate()

pyplot.show()

Answer 2

Try this:

>>> from matplotlib import pyplot as plt
>>> Dates = ['20110103', '20110103', '20110103', '20110108', '20110108', '20110108', '20110113', '20110113', '20110113']
>>> yvalues = [30, 40, -20, 0, -10, 20, 45, 12, -5]
>>> x=range(len(Dates))
>>> plt.xticks(x,Dates)
>>> plt.plot(x,yvalues)
>>> plt.show()