controlling the x ticks date values

Question

I have the following data sample as x,y pairs and both x and y are Unix time-stamps:

1354648326,1354648326
1354649456,1371775551
1354649664,1429649819
135464         


        

Answer 1

Limits of your x-axis data is only from 2012-12-05 06:12:06 to 2012-12-05 08:22:19. You have to expand date range.

However you may use this code to set x-axis ticks every 3 month:

import matplotlib.pyplot as plt
from itertools import izip
import datetime
import numpy as np
import pandas as pd

def grouped(iterable, n):
    return izip(*[iter(iterable)]*n)

def getLabels(s,t):
    labels =[]
    for x in pd.date_range(start=s, end=t, freq='3M'):
        labels.append(x.strftime("%Y-%m-%d"))
    print labels
    return labels

arr = [1354648326,1354648326,
1354649456,1371775551,
...
1354655889,1426675579,
1354656139,1420486774]

# convert timestamps to datetime objects
X = list()
Y = list()
for x, y in grouped(arr, 2):
    X.append(datetime.datetime.fromtimestamp(x))
    Y.append(datetime.datetime.fromtimestamp(y))

# range of X list is only one day: 2012-12-05
# you have to enlarge data of X
print np.min(X),np.max(X)

# sample data
data = np.random.uniform(-10, 10, size=len(X)*len(Y))

# plot
plt.scatter(X, Y, s = data)
ax = plt.gca()
# set limits for X-axis
ax.set_xlim([np.min(X),np.max(X)])
# generate labels
xlabels = getLabels(np.min(X),np.max(X))
# set ticks and labels
ax.set_xticks(xlabels)
ax.set_xticklabels(xlabels,rotation=20)

plt.show()

If I expand x-axis limits I get something like this on your data:

...
# plot
plt.scatter(X, Y, s = data)
ax = plt.gca()
# set limits for X-axis
xmin = datetime.datetime(2012,1,1,0,0,0) # np.min(X)
xmax = xmin + datetime.timedelta(days = 360) # np.max(X)
ax.set_xlim([xmin, xmax])
# generate labels every 3 month
xlabels = getLabels(xmin, xmax)
# set ticks and labels
ax.set_xticks(xlabels)
ax.set_xticklabels(xlabels,rotation=20)
plt.show()

If you want more complicated datetime tick labels read this answer.

Answer 2

Your problem is that your graph only has five ticks, so it can only display five labels. If you want to display all the labels, then you need to make sure that you have the same number of ticks.

I don't have pandas installed, and anyway, don't have the full data so can't re-create the labels. I have simply copied the list of labels you have provided. I have also 'reverse-engineered' the min & max for the x-axis from the labels (so that the data plots in the right place).

This line: ax.xaxis.set_ticks(np.arange(min_x, max_x, int((max_x-min_x)/len(labels)))) Ensures that you have the same number of ticks as labels.

Note that I have also changed the horizontal alignment of the labels so that, even when squashed up, it is still clear which tick the label corresponds to. This slice of the data appears to plot in the right location, so I'm pretty sure the labels are in the right place.

(Obviously the y-axis can be treated in the same way)

import matplotlib.pyplot as plt
import numpy as np
import time
import datetime

labels =['2012-06-30', '2012-09-30', '2012-12-31', '2013-03-31',
         '2013-06-30', '2013-09-30', '2013-12-31', '2014-03-31',
         '2014-06-30', '2014-09-30', '2014-12-31', '2015-03-31',
         '2015-06-30', '2015-09-30', '2015-12-31', '2016-03-31']
x = []
y = []
with open('data.txt','r') as myfile:
    for line in myfile:
        _x, _y = line.strip().split(',')
        x.append(int(_x))
        y.append(int(_y))

min_x = int(time.mktime(datetime.datetime.strptime('2012-06-30','%Y-%m-%d').timetuple()))
max_x = int(time.mktime(datetime.datetime.strptime('2016-03-31','%Y-%m-%d').timetuple()))

print (datetime.datetime.fromtimestamp(min(x)).strftime('%Y-%m-%d')) 
# Confirm that we are plotting in the right place for this sample

fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.set_xlim(min_x, max_x)
ax.xaxis.set_ticks(np.arange(min_x, max_x, int((max_x-min_x)/len(labels))))
ax.set_xticklabels(labels, rotation=20, horizontalalignment = 'right')
ax.scatter(x,y)
plt.show()