問題：
How to remove rows with duplicate index values?如何刪除具有重複索引值的行？
In the weather DataFrame below, sometimes a scientist goes back and corrects observations -- not by editing the erroneous rows, but by appending a duplicate row to the end of a file.在下面的天氣數據框中，有時科學家會返回並更正觀察結果——不是通過編輯錯誤的行，而是通過在文件末尾附加重複的行。
I'm reading some automated weather data from the web (observations occur every 5 minutes, and compiled into monthly files for each weather station.) After parsing a file, the DataFrame looks like:我正在從網上讀取一些自動天氣數據（每 5 分鐘進行一次觀測，並編譯成每個氣象站的月度文件。）解析文件後，DataFrame 如下所示：
Sta Precip1hr Precip5min Temp DewPnt WindSpd WindDir AtmPress
Date
2001-01-01 00:00:00 KPDX 0 0 4 3 0 0 30.31
2001-01-01 00:05:00 KPDX 0 0 4 3 0 0 30.30
2001-01-01 00:10:00 KPDX 0 0 4 3 4 80 30.30
2001-01-01 00:15:00 KPDX 0 0 3 2 5 90 30.30
2001-01-01 00:20:00 KPDX 0 0 3 2 10 110 30.28
Example of a duplicate case:重複案例的示例：
import pandas
import datetime
startdate = datetime.datetime(2001, 1, 1, 0, 0)
enddate = datetime.datetime(2001, 1, 1, 5, 0)
index = pandas.DatetimeIndex(start=startdate, end=enddate, freq='H')
data1 = {'A' : range(6), 'B' : range(6)}
data2 = {'A' : [20, -30, 40], 'B' : [-50, 60, -70]}
df1 = pandas.DataFrame(data=data1, index=index)
df2 = pandas.DataFrame(data=data2, index=index[:3])
df3 = df2.append(df1)
df3
A B
2001-01-01 00:00:00 20 -50
2001-01-01 01:00:00 -30 60
2001-01-01 02:00:00 40 -70
2001-01-01 03:00:00 3 3
2001-01-01 04:00:00 4 4
2001-01-01 05:00:00 5 5
2001-01-01 00:00:00 0 0
2001-01-01 01:00:00 1 1
2001-01-01 02:00:00 2 2
And so I need df3 to eventually become:所以我需要df3最終變成：
A B
2001-01-01 00:00:00 0 0
2001-01-01 01:00:00 1 1
2001-01-01 02:00:00 2 2
2001-01-01 03:00:00 3 3
2001-01-01 04:00:00 4 4
2001-01-01 05:00:00 5 5
I thought that adding a column of row numbers ( df3['rownum'] = range(df3.shape[0]) ) would help me select the bottom-most row for any value of the DatetimeIndex , but I am stuck on figuring out the group_by or pivot (or ???) statements to make that work.我認爲添加一列行號（ df3['rownum'] = range(df3.shape[0]) ）將幫助我爲DatetimeIndex任何值選擇最底部的行，但我一直在弄清楚group_by或pivot （或???）語句來完成這項工作。
解決方案：
參考一： https://stackoom.com/question/shCG參考二： Remove pandas rows with duplicate indices