matplotlib HourLocator 窃取我的 x 标签

Question

When I plot my half hourly time series, my axis labels are odd (like 16:33:12h or so...) When I use HourLocator to fix this (16:33h -> 16:00h), then my x label disappear completely.

My code is:

from datetime import date, timedelta, datetime, time
from matplotlib.dates import DayLocator, HourLocator
import matplotlib.pyplot as plt

start = time(0, 0, 0)
delta = timedelta(minutes=30)
times = []

for i in range(len(day_load)):
    dt = datetime.combine(date.today(), time(0, 0)) + delta * i
    times.append(dt.time())

load = [i/48 for i in range(48)]

fig, ax = plt.subplots()
ax.plot_date(times, load)
ax.xaxis.set_major_locator(HourLocator())
plt.show()

How can I achieve "even" labels (in a best practice way - I don't want to rewrite code for every other plot again). When I comment second last line, I get normal "odd" labels :(

Thanks for answers!

Answer 1

There are two main issues:

• You need to work with complete datetime objects, not only with time. So instead of dt.time() you should append dt directly.
• You not only need a locator, but also a formatter to produce nice ticklabels. Here you may use a DateFormatter("%H:%M") to show hours and minutes.

Complete code:

from datetime import date, timedelta, datetime, time
from matplotlib.dates import DayLocator, HourLocator,DateFormatter
import matplotlib.pyplot as plt

start = time(0, 0, 0)
delta = timedelta(minutes=30)
times = []
n=48

for i in range(n):
    # use complete datetime object, not only time
    dt = datetime.combine(date.today(), time(0, 0)) + delta * i
    times.append(dt)

load = [i/float(n) for i in range(n)]

fig, ax = plt.subplots()
ax.plot_date(times, load)

# set a locator, as well as a formatter
ax.xaxis.set_major_locator(HourLocator())
ax.xaxis.set_major_formatter(DateFormatter("%H:%M"))

#optionally rotate the labels and make more space for them
fig.autofmt_xdate()
plt.show()

Answer 2

This is an old question, but for anyone else facing this problem: you can leave the data types what they should be and use matplotlib.ticker.IndexLocator to get the axis ticks located nicely.

For example,

locator = mpl.ticker.IndexLocator(base=2 * 60 * 60, offset=0)
ax.xaxis.set_major_locator(locator)

places ticks at every two full hours, ie it uses the total number of seconds since midnight, regardless of the length of the intervals in the data.

Answer 3

Your code doesn't run, because day_load is undefined and I get other issues as well.

Not an answer, but I think you're better of using pandas . It makes it easy to create a date_range , and plotting is handled pretty well without adjustments.

from scipy import stats
import pandas as pd

n = 20
index = pd.date_range(start = '2016-01-01', periods = n, freq='1H')
df = pd.DataFrame(index = index)
df["value"] = stats.norm().rvs(n)

df.plot()