问题：将DataFrame列类型从字符串转换为日期时间，格式为dd / mm / yyyy
如何将字符串的DataFrame列（以dd / mm / yyyy格式）转换为日期时间？
How can I convert a DataFrame column of strings (in dd/mm/yyyy format) to datetimes?
回答 0
最简单的方法是使用to_datetime：
df['col'] = pd.to_datetime(df['col'])
它还dayfirst为欧洲时代提供了依据（但请注意，这并不严格）。
它在起作用：
In [11]: pd.to_datetime(pd.Series(['05/23/2005']))
Out[11]:
0 2005-05-23 00:00:00
dtype: datetime64[ns]
您可以传递特定格式：
In [12]: pd.to_datetime(pd.Series(['05/23/2005']), format="%m/%d/%Y")
Out[12]:
0 2005-05-23
dtype: datetime64[ns]
The easiest way is to use to_datetime:
df['col'] = pd.to_datetime(df['col'])
It also offers a dayfirst argument for European times (but beware this isn’t strict).
Here it is in action:
In [11]: pd.to_datetime(pd.Series(['05/23/2005']))
Out[11]:
0 2005-05-23 00:00:00
dtype: datetime64[ns]
You can pass a specific format:
In [12]: pd.to_datetime(pd.Series(['05/23/2005']), format="%m/%d/%Y")
Out[12]:
0 2005-05-23
dtype: datetime64[ns]
回答 1
如果您的日期列是格式为’2017-01-01’的字符串，则可以使用pandas astype将其转换为日期时间。
df['date'] = df['date'].astype('datetime64[ns]')
或使用datetime64 [D]（如果您想要“天”精度而不是纳秒）
print(type(df_launath['date'].iloc[0]))
Yield
<class 'pandas._libs.tslib.Timestamp'>
与使用pandas.to_datetime时相同
您可以尝试使用其他格式，然后是’％Y-％m-％d’，但至少可以使用。
If your date column is a string of the format ‘2017-01-01’
you can use pandas astype to convert it to datetime.
df['date'] = df['date'].astype('datetime64[ns]')
or use datetime64[D] if you want Day precision and not nanoseconds
print(type(df_launath['date'].iloc[0]))
yields
<class 'pandas._libs.tslib.Timestamp'>
the same as when you use pandas.to_datetime
You can try it with other formats then ‘%Y-%m-%d’ but at least this works.
回答 2
如果要指定复杂的格式，可以使用以下内容：
df['date_col'] = pd.to_datetime(df['date_col'], format='%d/%m/%Y')
format此处的更多详细信息：
You can use the following if you want to specify tricky formats:
df['date_col'] = pd.to_datetime(df['date_col'], format='%d/%m/%Y')
More details on format here:
回答 3
如果您的约会中有多种格式，别忘了设定infer_datetime_format=True以简化生活
df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True)
资料来源：pd.to_datetime
或者，如果您想要定制的方法：
def autoconvert_datetime(value):
formats = ['%m/%d/%Y', '%m-%d-%y'] # formats to try
result_format = '%d-%m-%Y' # output format
for dt_format in formats:
try:
dt_obj = datetime.strptime(value, dt_format)
return dt_obj.strftime(result_format)
except Exception as e: # throws exception when format doesn't match
pass
return value # let it be if it doesn't match
df['date'] = df['date'].apply(autoconvert_datetime)
If you have a mixture of formats in your date, don’t forget to set infer_datetime_format=True to make life easier
df['date'] = pd.to_datetime(df['date'], infer_datetime_format=True)
Source: pd.to_datetime
or if you want a customized approach:
def autoconvert_datetime(value):
formats = ['%m/%d/%Y', '%m-%d-%y'] # formats to try
result_format = '%d-%m-%Y' # output format
for dt_format in formats:
try:
dt_obj = datetime.strptime(value, dt_format)
return dt_obj.strftime(result_format)
except Exception as e: # throws exception when format doesn't match
pass
return value # let it be if it doesn't match
df['date'] = df['date'].apply(autoconvert_datetime)
