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如何在 pandas 中格式化日期格式

[英]how to format date format in pandas

I use python and pandas to get yahoo stock market date and save to a local csv file.我使用 python 和 pandas 获取雅虎股票市场日期并保存到本地 csv 文件。

DailyPrice = pd.read_csv(file, index_col=0)
print(DailyPrice.tail())

Date
2020-05-27           86.480003  84.370003  86.300003  86.180000  1917600.0 
2020-05-28           87.849998  86.059998  86.870003  86.690002  1908700.0

then I update the date.然后我更新日期。

History = pdr.DataReader(ticker, start=Before_yesterday, end=Today, data_source='yahoo')
print(History.tail())

Date
2020-06-29  87.360001  86.110001  86.559998  87.290001  1302500.0  87.290001
2020-06-30  88.379997  87.235001  87.330002  88.269997   236377.0  88.269997

then I append date然后我 append 日期

DailyPrice = DailyPrice.append(History)
print(DailyPrice.tail())

Date
2020-05-27           86.480003  84.370003  86.300003  86.180000  1917600.0 
2020-05-28           87.849998  86.059998  86.870003  86.690002  1908700.0
2020-06-29 00:00:00  87.360001  86.110001  86.559998  87.290001  1302500.0
2020-06-30 00:00:00  88.379997  87.235001  87.330002  88.269997   236377.0

so, my question is: how coul I format the column Date just like %Y-%m-%d, without time hh:mm:ss?所以,我的问题是:我如何格式化列 Date 就像 %Y-%m-%d 一样,没有时间 hh:mm:ss?

I guess it is the same question as this one我想这和这个问题一样

df['Date'] = df['Date'].dt.date

It should work它应该工作

Looks like you have a DatetimeIndex , you could try to use strftime看起来你有一个DatetimeIndex ,你可以尝试使用strftime

DailyPrice.index = DailyPrice.index.strftime('%Y-%m-%d')

I think I find the problem.我想我找到了问题所在。

Date is not a name of column.日期不是列的名称。

DailyPrice.columns.values.tolist()
['High', 'Low', 'Open', 'Close', 'Volume', 'Adj Close']

so, the first column, Date, what's it?那么,第一列,日期,它是什么?

Date is the index.日期是索引。

at last, issue is resolved.终于,问题解决了。

DailyPrice.index = pd.to_datetime(DailyPrice.index, format = '%Y-%m-%d')

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