Question

我正在尝试以下方法：

PoliceStations_raw=pd.DataFrame(
[['BAYVIEW'   ,37.729732,-122.397981],
 ['CENTRAL'   ,37.798732,-122.409919],
 ['INGLESIDE' ,37.724676,-122.446215],
 ['MISSION'   ,37.762849,-122.422005],
 ['NORTHERN'  ,37.780186,-122.432467],
 ['PARK'      ,37.767797,-122.455287],
 ['RICHMOND'  ,37.779928,-122.464467],
 ['SOUTHERN'  ,37.772380,-122.389412],
 ['TARAVAL'   ,37.743733,-122.481500],
 ['TENDERLOIN',37.783674,-122.412899]],columns=['PdDistrict','XX','YY'])


df1=pd.DataFrame([[0,'CENTRAL'],[1,'TARAVAL'],[3,'CENTRAL'],[2,'BAYVIEW']])
df1.columns = ['Index','PdDistrict']


  Index PdDistrict
0   0   CENTRAL
1   1   TARAVAL
2   3   CENTRAL
3   2   BAYVIEW

尽管输入了sort=False，但返回的对象已经合并了表，但是使用PdDistrict作为索引，并且更改了原始左数据帧的行的顺序。

pd.merge(df1,PoliceStations_raw,sort=False)

返回此值（请注意PdDistrict的顺序已更改）

  Index PdDistrict  XX        YY
0   0   CENTRAL 37.798732   -122.409919
1   3   CENTRAL 37.798732   -122.409919
2   1   TARAVAL 37.743733   -122.481500
3   2   BAYVIEW 37.729732   -122.397981

Answer 1

您需要指定两个数据帧合并的方式。默认情况下，内部联接由merge()模拟。但是，通过指定您想要左连接，将保留df1的排序顺序。因此，您只需添加how='left'：

>>> pd.merge(df1, PoliceStations_raw, how='left')
   Index PdDistrict         XX          YY
0      0    CENTRAL  37.798732 -122.409919
1      1    TARAVAL  37.743733 -122.481500
2      3    CENTRAL  37.798732 -122.409919
3      2    BAYVIEW  37.729732 -122.397981

此外，sort=False是默认行为 - 您无需指定该行为。

Pandas merge并不保留排序顺序

1 个答案: