转换为熊猫的日期时间

Question

我将数据保存到CSV文件中，如下所示：

Date,Bid,Ask
04/12/19 11:00 AM,1970,2010
05/12/19 11:00 AM,1960,2000
05/12/19 04:00 PM,1900,1925
06/12/19 11:00 AM,1890,1910
06/12/19 04:00 PM,2000,2025

我正在尝试使用 pd.to_datetime（）将“日期”列转换为日期时间，但出现此错误：

ValueError：时间数据'04 / 12/19 11:00 AM'与格式'％d /％m /％y％I：％M％p'（匹配）不匹配 < / p>

这是我的代码：

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("file_1.csv")
df['Date'] = pd.to_datetime(df['Date'], format='%d/%m/%y %I:%M %p')
df = df.set_index(["Date"])
df.plot()
plt.show()

这是整个错误：

Traceback (most recent call last):
  File "/home/zakaria/.local/lib/python3.8/site-packages/pandas/core/tools/datetimes.py", line 450, in _convert_listlike_datetimes
    values, tz = conversion.datetime_to_datetime64(arg)
  File "pandas/_libs/tslibs/conversion.pyx", line 350, in pandas._libs.tslibs.conversion.datetime_to_datetime64
TypeError: Unrecognized value type: <class 'str'>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "file.py", line 6, in <module>
    df['Date'] = pd.to_datetime(df['Date'], format='%d/%m/%y %I:%M %p')
  File "/home/zakaria/.local/lib/python3.8/site-packages/pandas/core/tools/datetimes.py", line 803, in to_datetime
    values = convert_listlike(arg._values, format)
  File "/home/zakaria/.local/lib/python3.8/site-packages/pandas/core/tools/datetimes.py", line 454, in _convert_listlike_datetimes
    raise e
  File "/home/zakaria/.local/lib/python3.8/site-packages/pandas/core/tools/datetimes.py", line 417, in _convert_listlike_datetimes
    result, timezones = array_strptime(
  File "pandas/_libs/tslibs/strptime.pyx", line 144, in pandas._libs.tslibs.strptime.array_strptime
ValueError: time data '04/12/19 11:00 AM' does not match format '%d/%m/%y %I:%M %p' (match)

Answer 1

为什么不pd.to_datetime不使用格式？

df['Date'] = pd.to_datetime(df['Date'])
print(df)

                 Date   Bid   Ask
0 2019-04-12 11:00:00  1970  2010
1 2019-05-12 11:00:00  1960  2000
2 2019-05-12 16:00:00  1900  1925
3 2019-06-12 11:00:00  1890  1910
4 2019-06-12 16:00:00  2000  2025

Answer 2

您可以尝试以下方法：

df['Date'] = pd.to_datetime(df['Date'], format='%d/%m/%y %I:%M %p')
print(df)

Answer 3

已解决

Scaffold(...)

代替

df['Date'] = pd.to_datetime(df['Date'], dayfirst=True)