Plotting time in Python with Matplotlib

You can also plot the timestamp, value pairs using pyplot.plot (after parsing them from their string representation). (Tested with matplotlib versions 1.2.0 and 1.3.1.)

Example:

import datetime
import random
import matplotlib.pyplot as plt

# make up some data
x = [datetime.datetime.now() + datetime.timedelta(hours=i) for i in range(12)]
y = [i+random.gauss(0,1) for i,_ in enumerate(x)]

# plot
plt.plot(x,y)
# beautify the x-labels
plt.gcf().autofmt_xdate()

plt.show()

Resulting image:

Line Plot


Here's the same as a scatter plot:

import datetime
import random
import matplotlib.pyplot as plt

# make up some data
x = [datetime.datetime.now() + datetime.timedelta(hours=i) for i in range(12)]
y = [i+random.gauss(0,1) for i,_ in enumerate(x)]

# plot
plt.scatter(x,y)
# beautify the x-labels
plt.gcf().autofmt_xdate()

plt.show()

Produces an image similar to this:

Scatter Plot


7 years later and this code has helped me. However, my times still were not showing up correctly.

enter image description here

Using Matplotlib 2.0.0 and I had to add the following bit of code from Editing the date formatting of x-axis tick labels in matplotlib by Paul H.

import matplotlib.dates as mdates
myFmt = mdates.DateFormatter('%d')
ax.xaxis.set_major_formatter(myFmt)

I changed the format to (%H:%M) and the time displayed correctly. enter image description here

All thanks to the community.


Update:

This answer is outdated since matplotlib version 3.5. The plot function now handles datetime data directly. See https://matplotlib.org/3.5.1/api/_as_gen/matplotlib.pyplot.plot_date.html

The use of plot_date is discouraged. This method exists for historic reasons and may be deprecated in the future.

datetime-like data should directly be plotted using plot.

If you need to plot plain numeric data as Matplotlib date format or need to set a timezone, call ax.xaxis.axis_date / ax.yaxis.axis_date before plot. See Axis.axis_date.


Old, outdated answer:

You must first convert your timestamps to Python datetime objects (use datetime.strptime). Then use date2num to convert the dates to matplotlib format.

Plot the dates and values using plot_date:

import matplotlib.pyplot
import matplotlib.dates

from datetime import datetime

x_values = [datetime(2021, 11, 18, 12), datetime(2021, 11, 18, 14), datetime(2021, 11, 18, 16)]
y_values = [1.0, 3.0, 2.0]

dates = matplotlib.dates.date2num(x_values)
matplotlib.pyplot.plot_date(dates, y_values)

enter image description here


I had trouble with this using matplotlib version: 2.0.2. Running the example from above I got a centered stacked set of bubbles.

graph with centered stack of bubbles

I "fixed" the problem by adding another line:

plt.plot([],[])

The entire code snippet becomes:

import datetime
import random
import matplotlib.pyplot as plt
import matplotlib.dates as mdates


# make up some data
x = [datetime.datetime.now() + datetime.timedelta(minutes=i) for i in range(12)]
y = [i+random.gauss(0,1) for i,_ in enumerate(x)]

# plot
plt.plot([],[])
plt.scatter(x,y)

# beautify the x-labels
plt.gcf().autofmt_xdate()
myFmt = mdates.DateFormatter('%H:%M')
plt.gca().xaxis.set_major_formatter(myFmt)

plt.show()
plt.close()

This produces an image with the bubbles distributed as desired.

graph with bubbles distributed over time