从 csv 读取时如何将数据帧行索引更改为 datetime.date?

How to change dataframe row index to datetime.date while reading from csv?

df.index[0] 我想成为 datetime.date(2006, 8, 27).

从文件读取时,df = pd.read_csv(filePath,index_col="Date")df.index[0] 显示为字符串 '2006-08-27'

我试过了:

dateparser = lambda s: datetime.datetime.strptime(s,"%Y-%m-%d").date()
df = pd.read_csv(filePath,parse_dates=["Date"], date_parser=dateparser,index_col="Date")

现在,df.index[0] 显示为 Timestamp('2006-08-27 00:00:00')

如何让df.index[0]变成datetime.date(2006, 8, 27)

使用样本 csv:

Date,Symbol,Series,Prev Close,Open,High,Low,Last,Close,VWAP,Volume,Turnover,Trades,Deliverable Volume,%Deliverble
2006-08-27,,,,,,,,,,,,,,
2006-08-28,ATFC,EQ,365.0,521.0,569.0,502.0,553.0,554.25,552.0,15166163,837176013020000.0,,3777529,0.24910000000000002
2006-08-29,ATFC,EQ,554.25,555.0,563.9,535.55,536.1,539.3,547.59,3929113,215153038915000.0,,727534,0.1852
2006-08-30,ATFC,EQ,539.3,537.0,542.9,521.5,529.0,528.1,529.55,2034983,107762957620000.0,,345064,0.1696
2006-08-31,ATFC,EQ,528.1,525.0,544.0,515.0,539.35,538.45,532.89,1670990,89044643830000.0,,286440,0.1714
2006-09-01,ATFC,EQ,538.45,539.0,549.0,535.1,541.35,541.85,542.46,1176195,63803856150000.0,,213842,0.1818

已经有一个函数可以将数据更改为日期时间,而不是使用 lambda 函数 pd.to_datetime

所以你可以这样做:

df = pd.read_csv(filePath,index_col="Date")

df['Date'] = pd.to_datetime(df['Date'] ,format = '%Y-%m-%d')

df['Date'] = df['Date'].apply(lambda x : x.date())

print(type(df['Date'][0]))

输出

<class 'datetime.date'>

为了匹配您的数据,函数中还有一个格式参数 Format

我认为你的格式是format = '%Y-%m-%d'

根据 pandas.read_csv,您还可以指定 parse_dates = Trueinfer_datetime_format = True 参数让 pandas 尝试从您设置的索引中解析日期迄今为止。 如:

df = pd.read_csv(filePath,index_col="Date",parse_dates=True,infer_datetime_format=True)

无法获得任何oneliner。

df = pd.read_csv(filePath)   # load dataframe
df["Date"]=df["Date"].apply(lambda s: datetime.datetime.strptime(s,"%Y-%m-%d").date()) # convert Date column items to datetime.date
df.set_index('Date', inplace=True) # set Date as row index