Pandas 日期时间自定义错误：“系列对象不可调用”
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Pandas Datetime Customization Error: 'Series Object is not Callable'
提问by Cole Starbuck
I have a dataframe, Df originally from a CSV file:
我有一个数据框 Df 最初来自 CSV 文件：
Ticker Date Open High Low Close \
0 ES H7 10/18/2016 1:44:59 PM 2128.25 2128.50 2128.00 2128.00
1 ES H7 10/18/2016 1:59:59 PM 2127.75 2129.25 2127.75 2128.75
2 ES H7 10/18/2016 2:14:59 PM 2127.25 2127.25 2124.50 2125.75
3 ES H7 10/18/2016 2:29:59 PM 2126.50 2126.50 2126.50 2126.50
4 ES H7 10/18/2016 2:44:59 PM 2125.75 2126.75 2125.75 2126.50
5 ES H7 10/18/2016 4:14:59 PM 2126.25 2126.25 2126.00 2126.00
6 ES H7 10/18/2016 4:44:59 PM 2126.50 2126.50 2126.25 2126.25
7 ES H7 10/18/2016 5:59:59 PM 2126.50 2126.50 2126.50 2126.50
8 ES H7 10/18/2016 6:14:59 PM 2127.00 2127.00 2127.00 2127.00
9 ES H7 10/18/2016 7:14:59 PM 2126.50 2127.75 2126.50 2127.75 I am trying to make sure that the Date column is set to properly account for the date/time:
我试图确保日期列设置为正确说明日期/时间：
Df = pd.read_csv(file location)
Df = pd.DataFrame(Df)
pd.to_datetime(Df.Date('%m%d%y %H:%M:%S'))
That looks correct to me based on other posts, however I get the error for the datetime line:
根据其他帖子，这对我来说是正确的，但是我收到了日期时间行的错误：
Type Error: 'Series' object is not callable
Maybe I'm missing the AM/PM indication here and that's causing the error?
也许我在这里错过了 AM/PM 指示，这是导致错误的原因？
回答by languitar
Df.Datereturns a Seriescontaining the dates from your data frame. You cannot call this with a format string. I suspect you want to ensure that the data type of the column is datetime. This will convert it appropriately:
Df.Date返回Series包含数据框中日期的 。您不能使用格式字符串调用它。我怀疑您想确保列的数据类型是日期时间。这将适当地转换它：
In [4]: Df
Out[4]:
Date foo
0 9:40 42
1 13:30 13
In [5]: Df.Date = pd.to_datetime(Df.Date)
In [6]: Df
Out[6]:
Date foo
0 2017-02-23 09:40:00 42
1 2017-02-23 13:30:00 13
回答by Alexey K.
languitar's answer is right here, pandas can guess many types of formats automatically:
languitar 的答案就在这里，pandas 可以自动猜测多种格式：
pd.to_datetime(Df.Date)
if you need to specify the format, then you need to precisely formulate the full line; your case:
如果你需要指定格式，那么你需要精确地制定完整的行；你的情况：
pd.to_datetime(Df.Date, format='%m/%d/%Y %I:%M:%S %p')
pd.to_datetime('10/18/2016 2:29:59 PM', format='%m/%d/%Y %I:%M:%S %p')
(big Y, I, p and all separators) https://docs.python.org/3.4/library/datetime.html
（大 Y、I、p 和所有分隔符） https://docs.python.org/3.4/library/datetime.html
p.s. as a courtesy use a shorter example to pd.read_clipboard(sep='\s\s+')
ps 作为礼貌使用更短的例子 pd.read_clipboard(sep='\s\s+')
Ticker Date Open
0 ES H7 10/18/2016 1:44:59 PM 2128.25
1 ES H7 10/18/2016 1:59:59 PM 2127.75
pd.read_csv()reads your file to DataFrame (no need pd.DataFrame(Df))
pd.read_csv()将您的文件读取到 DataFrame（不需要pd.DataFrame(Df)）
