Python 如何像Pandas 图一样格式化 matplotlib 图的时间序列轴

发布于05月19日

I've created following graph with pd.Series([1]*month_limits.size, month_limits).plot(ax=ax)
How do I recreate same x ticks labels with just matplotlib? I mean years and month not overriding each other

我得到的最好的是同时拥有几年和几个月，但几年压倒了几个月

import datetime

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas as pd

month_limits = pd.date_range('2021-08', '2023-01', freq="1m",
                             normalize=True) + datetime.timedelta(days=1)
plt.plot(month_limits, [1]*month_limits.size)

l1 = mdates.YearLocator()
l2 = mdates.MonthLocator(interval=1)
ax.xaxis.set_major_locator(l1)
ax.xaxis.set_minor_locator(l2)
ax.xaxis.set_major_formatter(mdates.ConciseDateFormatter(l1))
ax.xaxis.set_minor_formatter(mdates.ConciseDateFormatter(l2))

推荐答案

使用set_minor_locator和set_minor_formatter表示月份'%b'
Use set_major_locator and set_major_formatter for the month and year '%b\n%Y'
- mdates.YearLocator(month=1)，其中month是显示年份的月份.
一百零二

month_limits = pd.date_range('2021-08', '2023-01', freq="1m", normalize=True) +  pd.Timedelta(days=1)

fig, ax = plt.subplots(figsize=(6, 4))
ax.plot(month_limits, [1]*month_limits.size)

# set locators
ax.xaxis.set_minor_locator(mdates.MonthLocator(interval=2))
ax.xaxis.set_major_locator(mdates.YearLocator(month=1))
# set formatters
ax.xaxis.set_major_formatter(mdates.DateFormatter('%b\n%Y'))
ax.xaxis.set_minor_formatter(mdates.DateFormatter('%b'))

month_limits = pd.date_range('2021-08', '2023-01', freq="1m", normalize=True) + pd.Timedelta(days=1)

fig, ax = plt.subplots(figsize=(6, 4))
ax.plot(month_limits, [1]*month_limits.size)

# set locators
ax.xaxis.set_minor_locator(mdates.MonthLocator(bymonth=range(1, 13, 3)))
ax.xaxis.set_major_locator(mdates.YearLocator(month=1))
# set formatter
ax.xaxis.set_major_formatter(mdates.DateFormatter('%b\n%Y'))
ax.xaxis.set_minor_formatter(mdates.DateFormatter('%b'))