I think you’re confused on a few points about how matplotlib handles dates.
You’re not actually plotting dates, at the moment. You’re plotting things on the x-axis with [0,1,2,...] and then manually labeling every point with a string representation of the date.
Matplotlib will automatically position ticks. However, you’re over-riding matplotlib’s tick positioning functionality (Using xticks is basically saying: “I want ticks in exactly these positions”.)
At the moment, you’ll get ticks at [10, 20, 30, ...] if matplotlib automatically positions them. However, these will correspond to the values that you used to plot them, not the dates (which you didn’t use when plotting).
You probably want to actually plot things using dates.
Currently, you’re doing something like this:
import datetime as dt
import matplotlib.dates as mdates
import numpy as np
import matplotlib.pyplot as plt
# Generate a series of dates (these are in matplotlib's internal date format)
dates = mdates.drange(dt.datetime(2010, 01, 01), dt.datetime(2012,11,01),
dt.timedelta(weeks=3))
# Create some data for the y-axis
counts = np.sin(np.linspace(0, np.pi, dates.size))
# Set up the axes and figure
fig, ax = plt.subplots()
# Make a bar plot, ignoring the date values
ax.bar(np.arange(counts.size), counts, align='center', width=1.0)
# Force matplotlib to place a tick at every bar and label them with the date
datelabels = mdates.num2date(dates) # Go back to a sequence of datetimes...
ax.set(xticks=np.arange(dates.size), xticklabels=datelabels) #Same as plt.xticks
# Make space for and rotate the x-axis tick labels
fig.autofmt_xdate()
plt.show()
Instead, try something like this:
import datetime as dt
import matplotlib.dates as mdates
import numpy as np
import matplotlib.pyplot as plt
# Generate a series of dates (these are in matplotlib's internal date format)
dates = mdates.drange(dt.datetime(2010, 01, 01), dt.datetime(2012,11,01),
dt.timedelta(weeks=3))
# Create some data for the y-axis
counts = np.sin(np.linspace(0, np.pi, dates.size))
# Set up the axes and figure
fig, ax = plt.subplots()
# By default, the bars will have a width of 0.8 (days, in this case) We want
# them quite a bit wider, so we'll make them them the minimum spacing between
# the dates. (To use the exact code below, you'll need to convert your sequence
# of datetimes into matplotlib's float-based date format.
# Use "dates = mdates.date2num(dates)" to convert them.)
width = np.diff(dates).min()
# Make a bar plot. Note that I'm using "dates" directly instead of plotting
# "counts" against x-values of [0,1,2...]
ax.bar(dates, counts, align='center', width=width)
# Tell matplotlib to interpret the x-axis values as dates
ax.xaxis_date()
# Make space for and rotate the x-axis tick labels
fig.autofmt_xdate()
plt.show()
