熊猫列中的完全匹配字符串

Question

Set-up

I scrape housing ad data and analyse with pandas. I have computed average statistics and inserted them in a pandas dataframe: district_df .

One of the district_df columns contains district names: district_df['district'] .

Another of the district_df columns contains subdistrict names: district_df['subdistrict']

They look like,

        district           subdistrict      
     Bergen-Enkheim      Bergen-Enkheim    
    Bornheim/Ostend            Bornheim
    Bornheim/Ostend              Ostend
            Harheim             Harheim
       Innenstadt I            Altstadt
       Innenstadt I     Bahnhofsviertel
       Innenstadt I              Gallus
      Innenstadt II          Bockenheim 
      Innenstadt II        Westend-Nord
                  ⋮                   ⋮

---

Problem

I create a district table ( district_table ) from district_df per district. Ie for the above I create five district tables. I do this by the following code,

for district in d_set: # d_set is a set containing all district names 
    district_table = district_df[district_df['district'].str.match(district)]

This code works, that is: a table per district is created.

However, the table for Innenstadt II also contains the subdistricts of Innenstadt I .

It seems to me that .str.match(district) matches not exact, but partly. Ie Innenstadt I will match Innenstadt II .

My actual district_df columns contain more then what I display here – issue occurs for a variety of district names.

How do I get exact matches?

Answer 1

I'd do it this way:

{ dist: df[df.district == dist] for dist in df.district.unique() }

But then again you might be better off using a MultiIndex:

df.set_index(['district', 'subdistrict'], inplace=True)

This is a lot like the dict solution, but downstream processing is likely to be faster.

Answer 2

I think you need boolean indexing in loop:

d_set = district_df['district'].unique()

for district in d_set: 
    district_table = district_df[district_df['district'] == district]
    print (district_table)

         district     subdistrict
0  Bergen-Enkheim  Bergen-Enkheim
          district subdistrict
1  Bornheim/Ostend    Bornheim
2  Bornheim/Ostend      Ostend
  district subdistrict
3  Harheim     Harheim
       district      subdistrict
4  Innenstadt I         Altstadt
5  Innenstadt I  Bahnhofsviertel
6  Innenstadt I           Gallus
        district   subdistrict
7  Innenstadt II    Bockenheim
8  Innenstadt II  Westend-Nord

If need dict of DataFrames better is convert groupby object:

a = dict(tuple(district_df.groupby('district')))

print (a['Innenstadt I'])
       district      subdistrict
4  Innenstadt I         Altstadt
5  Innenstadt I  Bahnhofsviertel
6  Innenstadt I           Gallus