Python Dataframe：根据特定条件删除重复项

Question

具有重复商店 ID 的数据框，其中一些商店 ID 出现两次，一些出现三次：
我只想根据分配给其区域的最短商店距离保留唯一的商店 ID。

    Area  Shop Name  Shop Distance  Shop ID   

0   AAA   Ly         86             5d87790c46a77300
1   AAA   Hi         230            5ce5522012138400
2   BBB   Hi         780            5ce5522012138400
3   CCC   Ly         450            5d87790c46a77300
...
91  MMM   Ju         43             4f76d0c0e4b01af7
92  MMM   Hi         1150           5ce5522012138400
...

使用 pandas drop_duplicates 删除重复行，但条件是基于第一个/最后一个出现的商店 ID，这不允许我按距离排序：

shops_df = shops_df.drop_duplicates(subset='Shop ID', keep= 'first')

我也试过按Shop ID分组然后排序，但是排序returns错误：Duplicates

bbtshops_new['C'] = bbtshops_new.groupby('Shop ID')['Shop ID'].cumcount()
bbtshops_new.sort_values(by=['C'], axis=1)

到目前为止，我尝试做到这个阶段：

# filter all the duplicates into a new df
df_toclean = shops_df[shops_df['Shop ID'].duplicated(keep= False)]

# create a mask for all unique Shop ID
mask = df_toclean['Shop ID'].value_counts()

# create a mask for the Shop ID that occurred 2 times
shop_2 = mask[mask==2].index

# create a mask for the Shop ID that occurred 3 times
shop_3 = mask[mask==3].index

# create a mask for the Shops that are under radius 750 
dist_1 = df_toclean['Shop Distance']<=750

# returns results for all the Shop IDs that appeared twice and under radius 750
bbtshops_2 = df_toclean[dist_1 & df_toclean['Shop ID'].isin(shop_2)]

* if i use df_toclean['Shop Distance'].min() instead of dist_1 it returns 0 results

我想我做了很长的路，但仍然没有弄清楚删除重复项，有人知道如何以更短的方式解决这个问题吗？我是 python 的新手，感谢您的帮助！

Answer 1

尝试先根据距离对数据框进行排序，然后删除重复的商店。

df = shops_df.sort_values('Distance')
df = df[~df['Shop ID'].duplicated()]  # The tilda (~) inverts the boolean mask.

或者就像一个链式表达式（根据@chmielcode 的评论）。

df = (
    shops_df
    .sort_values('Distance')
    .drop_duplicates(subset='Shop ID', keep= 'first')
    .reset_index(drop=True)  # Optional.
)

Answer 2

您可以使用 idxmin:

df.loc[df.groupby('Area')['Shop Distance'].idxmin()]

  Area Shop Name  Shop  Distance              Shop ID
0  AAA        Ly              86     5d87790c46a77300
2  BBB        Hi             780     5ce5522012138400
3  CCC        Ly             450     5d87790c46a77300
4  MMM        Ju              43     4f76d0c0e4b01af7

Python Dataframe：根据特定条件删除重复项

Python Dataframe: Dropping duplicates base on certain conditions

python

dataframe

pandas

drop-duplicates