2 回答

TA貢獻(xiàn)1851條經(jīng)驗(yàn) 獲得超3個(gè)贊
您還可以使用:
df.append(df1,ignore_index=True).drop_duplicates(subset=['Pub Date','Forecast Time','Forecast Date','State'])
將兩個(gè)數(shù)據(jù)幀視為:
df :
Pub Date Forecast Time Forecast Date State Temp
0 2018-12-12 23:00:00 2018-12-20 AK 3.0
1 2018-12-12 02:00:00 2018-12-20 AK 3.2
2 2018-12-12 05:00:00 2018-12-20 AK 2.9
df1:
Pub Date Forecast Time Forecast Date State Temp
0 2018-12-12 23:00:00 2018-12-20 AK 3.0
1 2018-12-13 02:00:00 2018-12-20 AK 3.2
2 2018-12-13 05:00:00 2018-12-20 AK 2.9
df.append(df1,ignore_index=True).drop_duplicates(subset=['Pub Date','Forecast Time','Forecast Date','State'])
Pub Date Forecast Time Forecast Date State Temp
0 2018-12-12 23:00:00 2018-12-20 AK 3.0
1 2018-12-12 02:00:00 2018-12-20 AK 3.2
2 2018-12-12 05:00:00 2018-12-20 AK 2.9
4 2018-12-13 02:00:00 2018-12-20 AK 3.2
5 2018-12-13 05:00:00 2018-12-20 AK 2.9
基本上僅基于某些列附加數(shù)據(jù)幀和刪除重復(fù)項(xiàng) ['Pub Date','Forecast Time','Forecast Date','State']
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