Python DateTime到matplotlib日期转换导致烛台图不正确

我正在try 绘制烛台图，数据如下:

               openDateTime open    high    low close
1763    2023-11-04 20:45:00 34735.1 34758.6 34735.1 34751.9
1764    2023-11-04 21:00:00 34751.8 34764.1 34749.4 34761.5
1765    2023-11-04 21:15:00 34761.6 34894.0 34761.5 34858.4
1766    2023-11-04 21:30:00 34858.4 34880.9 34812.0 34825.9
1767    2023-11-04 21:45:00 34826.0 34826.0 34795.4 34801.0


Data columns (total 5 columns):
 #   Column           Non-Null Count  Dtype         
---  ------           --------------  -----         
 0   openDateTime     5 non-null      datetime64[ns]
 1   open             5 non-null      float64       
 2   high             5 non-null      float64       
 3   low              5 non-null      float64       
 4   close            5 non-null      float64       
dtypes: datetime64[ns](1), float64(4)

然而，在try 使用mpl_dates.date2num将openDateTime转换为matplotlib日期时间时，我得到了不正确的结果.

我的完整代码如下，图表不正确:

import matplotlib.pyplot as plt
from mplfinance.original_flavor import candlestick_ohlc
import pandas as pd
import matplotlib.dates as mpdates
 
df['openDateTime'] = df['openDateTime'].apply(mpl_dates.date2num) #<-- this is where I think incorrect conversion occurs but this is due to  df['openDateTime'] being in incorrect format for .apply(mpl_dates.date2num) ???
# creating Subplots
fig, ax = plt.subplots()
 
# plotting the data
candlestick_ohlc(ax, df.values, width = 0.6,
                 colorup = 'green', colordown = 'red', 
                 alpha = 0.8)
 
# allow grid
ax.grid(True)
 
# Setting labels 
ax.set_xlabel('openDateTime')
ax.set_ylabel('open')
 
date_format = mpdates.DateFormatter('%d-%m-%Y %H:%m:%S')
ax.xaxis.set_major_formatter(date_format)
fig.autofmt_xdate()
 
fig.tight_layout()
 
# show the plot
plt.show()

转换为openDateTime后，df如下所示:

openDateTime    open    high    low close
1764    19665.875000    34751.8 34764.1 34749.4 34761.5
1765    19665.885417    34761.6 34894.0 34761.5 34858.4
1766    19665.895833    34858.4 34880.9 34812.0 34825.9
1767    19665.906250    34826.0 34826.0 34795.0 34798.3
1768    19665.916667    34798.3 34930.0 34798.3 34894.0

Data columns (total 5 columns):
 #   Column        Non-Null Count  Dtype  
---  ------        --------------  -----  
 0   openDateTime  5 non-null      float64
 1   open          5 non-null      float64
 2   high          5 non-null      float64
 3   low           5 non-null      float64
 4   close         5 non-null      float64

或者，我也可以有unix时间戳在ms为openDateTime，如果这有助于无论如何转换:

         openTimeUnixMs openDateTime    open    high    low close
1764    1699131600000   2023-11-04 21:00:00 34751.8 34764.1 34749.4 34761.5
1765    1699132500000   2023-11-04 21:15:00 34761.6 34894.0 34761.5 34858.4
1766    1699133400000   2023-11-04 21:30:00 34858.4 34880.9 34812.0 34825.9
1767    1699134300000   2023-11-04 21:45:00 34826.0 34826.0 34795.0 34798.3
1768    1699135200000   2023-11-04 22:00:00 34798.3 34930.0 34798.3 34894.0