如何对熊猫进行分组、排序,然后取回熊猫中第二高的一行?

sort_values 然后使用 cumcount 用于计数值,然后按筛选 boolean indexing

df = df.sort_values(['ID','Offer'], ascending=False)
df1 = df[df.groupby('ID').cumcount() == 1]
print (df1)
             ID        Vehicle Auction  Offer
4 3580845  2005  Volvo XC90 V8     IAA    270
9 3580789  2003   Lexus ES 300     IAA    270

groupby 和 rank 结合使用。

from io import StringIO
import pandas as pd

data = pd.read_table(StringIO("""ID Vehicle Auction Offer
3580845 2005VolvoXC90V8 Copart 215
3580845 2005VolvoXC90V8 ManheimSalvageAPI 170
3580845 2005VolvoXC90V8 MergedSalvage 195
3580845 2005VolvoXC90V8 ManheimSalvage 390
3580845 2005VolvoXC90V8 IAA 270
3580845 2005VolvoXC90V8 SVP 175
3580789 2003LexusES300 Copart 180
3580789 2003LexusES300 MergedSalvage 190
3580789 2003LexusES300 ManheimSalvage 355
3580789 2003LexusES300 IAA 270
3580789 2003LexusES300 SVP 180"""), sep=' ')

offer_rank_by_id = data.groupby('ID').rank(method = 'min', ascending = False).loc[:,'Offer'] == 2 # using 2 because we want to select the second highest offer for each id

data.loc[offer_rank_by_id,:]

#         ID          Vehicle Auction  Offer
# 4  3580845  2005VolvoXC90V8     IAA    270
# 9  3580789   2003LexusES300     IAA    270