如何在 pandas dataframe 與 matplotlib 在 ZA7F117F35426B56227 中繪制時保持 xaxis 中的日期時間格式不變？

Question

我有一個 pandas dataframe df ，如下所示：

Monthly Peak Demand
2019-07-31  1313.080833
2019-08-31  1407.938078
2019-09-30  1289.603335
2019-10-31  1266.722083
2019-11-30  1242.099010
2019-12-31  1374.902243
2020-01-31  1340.754667
2020-02-29  1256.317174
2020-03-31  1206.196696
2020-04-30  1023.634417
2020-05-31  1231.634719
2020-06-30  1301.517750
2020-07-31  1352.991333
2020-08-31  1315.315792
2020-09-30  1406.191792
2020-10-31  1381.831375
2020-11-30  1363.881792
2020-12-31  1466.332000
2021-01-31  1474.792542
2021-02-28  1350.772708
2021-03-31  1463.005418
2021-04-30  1481.848996
2021-05-31  1361.796917
2021-06-30  1455.569800
2021-07-31  1527.489190
2021-08-31  1579.947292
2021-09-30  1614.845556

df.to_dict()如下：

{'Monthly Peak Demand': {Timestamp('2019-07-31 00:00:00', freq='M'): 1313.0808326666668,
  Timestamp('2019-08-31 00:00:00', freq='M'): 1407.9380777333333,
  Timestamp('2019-09-30 00:00:00', freq='M'): 1289.6033353333332,
  Timestamp('2019-10-31 00:00:00', freq='M'): 1266.7220833333333,
  Timestamp('2019-11-30 00:00:00', freq='M'): 1242.0990104666666,
  Timestamp('2019-12-31 00:00:00', freq='M'): 1374.9022425333333,
  Timestamp('2020-01-31 00:00:00', freq='M'): 1340.7546666666667,
  Timestamp('2020-02-29 00:00:00', freq='M'): 1256.3171739333334,
  Timestamp('2020-03-31 00:00:00', freq='M'): 1206.1966956,
  Timestamp('2020-04-30 00:00:00', freq='M'): 1023.6344166666667,
  Timestamp('2020-05-31 00:00:00', freq='M'): 1231.6347192666665,
  Timestamp('2020-06-30 00:00:00', freq='M'): 1301.51775,
  Timestamp('2020-07-31 00:00:00', freq='M'): 1352.9913333333334,
  Timestamp('2020-08-31 00:00:00', freq='M'): 1315.3157916666667,
  Timestamp('2020-09-30 00:00:00', freq='M'): 1406.1917916666666,
  Timestamp('2020-10-31 00:00:00', freq='M'): 1381.831375,
  Timestamp('2020-11-30 00:00:00', freq='M'): 1363.8817916666667,
  Timestamp('2020-12-31 00:00:00', freq='M'): 1466.3319997333335,
  Timestamp('2021-01-31 00:00:00', freq='M'): 1474.7925416666667,
  Timestamp('2021-02-28 00:00:00', freq='M'): 1350.7727083333334,
  Timestamp('2021-03-31 00:00:00', freq='M'): 1463.005418466667,
  Timestamp('2021-04-30 00:00:00', freq='M'): 1481.8489957333331,
  Timestamp('2021-05-31 00:00:00', freq='M'): 1361.7969166666667,
  Timestamp('2021-06-30 00:00:00', freq='M'): 1455.5698004666665,
  Timestamp('2021-07-31 00:00:00', freq='M'): 1527.4891895833332,
  Timestamp('2021-08-31 00:00:00', freq='M'): 1579.9472916666666,
  Timestamp('2021-09-30 00:00:00', freq='M'): 1614.8455562708332}}

df.plot()返回以下 plot：

但是，當我想獲得酒吧 plot 使用

df.plot.bar()或df.plot(kind = "bar")我得到以下 plot：

為什么這些圖中 x 軸上的標簽顯示不同？ 我想在 plot 欄中獲得帶有月份和年份名稱的 plot？ 如何在 Python 中使用 matplotlib 獲得它？

Answer 1

Pandas 將條形圖繪制為分類，因此您需要直接使用 matplotlib。 Pandas 為周期時間序列注冊了自己的轉換器以獲得這種漂亮的格式。 盡管將索引轉換為周期索引（ df.index.to_period(freq='M') ）很容易，但我無法將此轉換器與 matplotlib 一起用於條形圖。

我能想到的最接近的是使用 matplotlibs ConciseDateFormatter ：

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

fig, ax = plt.subplots()

col = 'Monthly Peak Demand'
ax.bar(df.index, df[col], width=20, label=col)
ax.xaxis.set_major_locator(mdates.AutoDateLocator())
ax.xaxis.set_major_formatter(mdates.ConciseDateFormatter(locator))
ax.legend()

Answer 2

import pandas as pd
from io import StringIO

data = '''
 "Monthly Peak Demand"
2019-07-31  1313.080833
2019-08-31  1407.938078
2019-09-30  1289.603335
2019-10-31  1266.722083
2019-11-30  1242.099010
2019-12-31  1374.902243
2020-01-31  1340.754667
2020-02-29  1256.317174
2020-03-31  1206.196696
2020-04-30  1023.634417
2020-05-31  1231.634719
2020-06-30  1301.517750
2020-07-31  1352.991333
2020-08-31  1315.315792
2020-09-30  1406.191792
2020-10-31  1381.831375
2020-11-30  1363.881792
2020-12-31  1466.332000
2021-01-31  1474.792542
2021-02-28  1350.772708
2021-03-31  1463.005418
2021-04-30  1481.848996
2021-05-31  1361.796917
2021-06-30  1455.569800
2021-07-31  1527.489190
2021-08-31  1579.947292
2021-09-30  1614.845556
'''

s = pd.read_csv(
    StringIO(data), 
    sep='\s+', 
    squeeze=True, 
    parse_dates=True,
)

labels = s.index.format(date_format='%b %Y')

ax = s.plot.bar(figsize=(12,5))
ax.set_xticklabels(labels);

labels = s.index.format(
    formatter=lambda x: f'{x:%Y %b}' if x.month == 1 else f'{x:%b}'
)

ax = s.plot.bar(figsize=(12,5))
ax.set_xticklabels(labels);