plotting dates from time() since the epoch with matplotlib

Question

I'm sourcing date in second since the epoch as a floating point number ( from time.time() ) and I'm trying to plot it converting it like this (line[0]):

x,y = [],[]
csv_reader = csv.reader(open(csvFile))
for line in csv_reader:
    x.append(float(line[1]))
    y.append(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(float(line[0]))))


fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x,y,'o-')
fig.autofmt_xdate()

plt.show()

but matplotlib keeps on erroring out like this :

ValueError: invalid literal for float(): 2013-07-08 15:04:50

Any idea on how to format it properly ?

Cheers

Why are you taking a float of a quantity of the form 2013-07-08 15:04:50? It's not a float... — Pablo
– Pablo, Commented Jul 8, 2013 at 20:10
because if I use float(line[0]) by itself if gives me a very strange result, I'm aware I'm not feeding proper data but I don't know how to format my time.time() for matplotlib properly — Finger twist
– Finger twist, Commented Jul 8, 2013 at 20:12
Could you give us more details about which is the repr() of line[0] & line[1]? — Pablo
– Pablo, Commented Jul 8, 2013 at 20:13
Currently, your y values a strings, like '2013-07-08 15:04:50', and your x values are floats. Do you want y values which are dates? That is possible, but it is usually done the other way around.(with dates on the x-axis.) — unutbu
– unutbu, Commented Jul 8, 2013 at 20:13
@Pablo : repr(line[0]'1373292290.671339' repr(line[1]) '57.2' — Finger twist
– Finger twist, Commented Jul 8, 2013 at 20:16

Community · Accepted Answer · 2020-06-20 09:12:55Z

3

You get a ValueError since that format is invalid for float(). Instead of formatting it to a float value, try appending the formatted string to a list and use the yticks() function as follows.

>>> yAxis = ['2013-07-08 15:04:50', '2013-07-08 15:03:50', '2013-07-08 5:04:50']
>>> from random import randint
>>> xAxis = [randint(0, 10) for _ in range(3)]
>>> import pylab as plt
>>> plt.plot(xAxis, range(len(xAxis)))
>>> plt.yticks(range(len(yAxis)), yAxis, size='small')
>>> plt.show()

This gives you a plot like the following, hopefully, that was what you were looking for :

enter image description here

P.S - Did you want the dates on the X-Axis?

edited Jun 20, 2020 at 9:12

CommunityBot

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answered Jul 8, 2013 at 20:13

Sukrit Kalra

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5 Comments

Finger twist Over a year ago

yes, I meant to have the date on the X-Axis ( still trying to figure out that xticks trick .. )

Sukrit Kalra Over a year ago

Just do plt.plot(yAxis) and then plt.xticks(range(len(xAxis)), xAxis, size="small"). And, ofcourse, appropriately change xAxis and yAxis.

Finger twist Over a year ago

nice ! seems to work fine. Would you know how to "skip" dates, it is obviously trying to cram all the dates on the graph and there are way too many !

Finger twist Over a year ago

duh, I'll just keep what I want from the date list :)

Pablo Over a year ago

I think that it could be done better. What happens if the time interval is not constant? You must to take into account this...

Pablo · Accepted Answer · 2013-07-08 21:06:59Z

Here there is another example, where the spacing between dates are not uniform, and could be randomly distributed:

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

time_data = np.array([1373316370.877059, 
                      1373316373.95448, 
                      1373316378.018756, 
                      1373316381.960965, 
                      1373316383.586567, 
                      1373316387.111703, 
                      1373316387.611037, 
                      1373316391.923015, 
                      1373316393.80545, 
                      1373316398.294916])

ydata = np.random.rand(len(time_data))
time_formatted = []
for element in time_data:
    time_formatted.append(time.strftime('%Y-%m-%d %H:%M:%S',
                                        time.localtime(element)))

isort = np.argsort(time_data) #Sorting time_data
plt.xticks(time_data[isort],
           np.array(time_formatted)[isort],
           size='small',
           rotation=35)
plt.plot(time_data[isort],ydata[isort],'k-')
plt.show()

enter image description here

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