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我有一個Python腳本。運行各種命令導入,CSV文件中置和處理數據後,我結束了一個數據幀,看起來像這樣:Python Pandas datetime和multiindex問題
PV PV
Date 30/11/2016 01/12/2016
00:30 4 4
01:00 5 1
01:30 6 7
etc
我現在要的是刪除列30/11/2016,僅留下2016年12月1日的數據。這是我的代碼:
# create MultiIndex.from_arrays from first row of DataFrame first, then remove first row
# by df.iloc
df.columns = pd.MultiIndex.from_arrays([df.columns, pd.to_datetime(df.iloc[0])])
df = df.iloc[1:]
# get today's date minus 60 mins. the minus 60 mins will account for the fact that the
# very last half hourly data slot is produced at the beginning of the next day
date = dt.datetime.today() - dt.timedelta(minutes=60)
# convert to correct format:
date = date.strftime("%d-%m-%Y")
# Use indexslice to remove unwanted date columns i.e. none that are not for today's
# date
idx = pd.IndexSlice
df = df.loc[:,idx[:,[date]]]
# drop the second level of the multiindex, which is the level containing the date, which
# is no longer required
df.columns = df.columns.droplevel(1)
這是整個十一月的做工精細直到今天,12月1日,當它開始嘔吐起來的錯誤。我一直追溯到它的代碼,即第一部分:
# create MultiIndex.from_arrays from first row of DataFrame first, then remove first row
# by df.iloc
df.columns = pd.MultiIndex.from_arrays([df.columns, pd.to_datetime(df.iloc[0])])
的輸出是:
PV
Date 2016-11-30 2016-01-12
Date 30/11/2016 01/12/2016
00:30 4 4
01:00 5 1
01:30 6 7
etc
的問題是在第一盤上面顯示的日期,第一這是2016-11-30,因此YMD,第二個是2016-01-12,因此YDM。爲什麼日期格式不同?我將如何讓他們都成爲Y-M-D?