python - 如何将 pandas 数据框中存在的列中的单词替换为同一列中的另一个单词？

Question

我已将其放入代码中的 df1 数据框中。

我已通过将每个字母转换为小写来修改此行。

df1 = df1.applymap(lambda s:s.lower() if type(s) == str else s) 

然后我使用下划线“_”替换了每个连字符“-”或“-”和空格“”

  list=[]
for x in df1['route']:
    list.append(x.replace(" - ", "_").replace(" ","_").replace("-","_").replace("  ","_"))
df1['route'] = list 

现在，我有不同的缩写，我不希望在输出中出现这些缩写。我想将它们替换为完整形式，例如 _del 到 _delhi、_blr 到 _banglore、_vara 到 _varanasi、_hyd 到 _hyderabad。

还有_del_到_delhi、_blr_到_banglore_、_vara_到_varanasi_、_hyd_到_hyderabad_。

因此，我为此编写了这些代码行，因为我已将路线名称列重命名为路线

   for idx in range(len(df1)):
   df1.loc[idx,'route']  =  df1.loc[idx,'route'].replace('del_','delhi_').replace('blr_','banglore_').replace('vara_','varanasi_').replace('hyd_','hyderabad_').replace('_blr_','_banglore_').replace('_vara_','_varanasi_').replace('_hyd_','_hyderabad_').replace('_del_','_delhi_')      

我现在面临的问题是，有时数据来自delhi_to_vara或_chennai_blr或luckhnow_to_vara等。

我不知道如何在字符串结尾时将字符串转换为完整形式，

_vara、_blr、_hyd、_del 至 _varanasi、_banglore、_海德拉巴、_delhi

现在的数据如下所示[

我为所有此过程编写的将其转换为所需形式的代码是这样的

 df1 = df1.applymap(lambda s:s.lower() if type(s) == str else s)            

        list=[]
        for x in df1['route']:
            list.append(x.replace(" - ", "_").replace(" ","_").replace("-","_").replace("  ","_"))
        df1['route'] = list     

        for idx in range(len(df1)):
           df1.loc[idx,'route']  =  df1.loc[idx,'route'].replace('del_','delhi_').replace('blr_','banglore_').replace('vara_','varanasi_').replace('hyd_','hyderabad_').replace('_blr_','_banglore_').replace('_vara_','_varanasi_').replace('_hyd_','_hyderabad_').replace('_del_','_delhi_')         .
           if df1['route'][idx].endswith('_del'):
                 df1['route'][idx].replace('_del','_delhi')
           if df1['route'][idx].endswith('_vara'):
                 df1['route'][idx].replace('_vara','_varanasi')
           if df1['route'][idx].endswith('_blr'):
                 df1['route'][idx].replace('_blr','_banglore')
           if df1['route'][idx].endswith('_hyd'):
                 df1['route'][idx].replace('_hyd','_hyderabad') 

Route name
Del-Manali
Manali-Del
Del to Katra - 46 Sleeper
Delhi to Manali 8:30 PM
Manali to Delhi 8:00
Delhi to Manali 5:00 PM
DELHI TO KATRA 46 SEATER 8:00 PM
Lucknow to Vara
DELHI_MANALI_05:00PM
Delhi To Manali 10:30pm
MANALI TO DEL 5:00 PM
10:15 Lucknow To Vara
MANALI_DELHI_6:00PM
MANALI_DELhi_4.00PM
Delhi_Manali_6:00PM
BLR_CHENNAI_1:30PM
CHENNAI_BLR_11:00PM
BANGALORE_CHENNAI_11:05PM
CHENNAI_BANGALORE_5:30AM
Hyd_Blr
BANGALORE_HYDERABAD_ 7:45PM
CHENNAI_BANGALORE_5:45AM
DELHI TO DEHRADUN
DEHRADUN TO DELHI
Delhi to Katra UP22T8671
BANGALORE_CHENNAI_10:45PM
Delhi-Lucknow 9:00PM 30 sleeper
CHENNAI_BANGALORE_10:30PM
Lucknow_Vara_10:30PM
VARANASI_LUCKNOW_9:30PM
Delhi to Jalandhar 10:00 PM
JALANDHAR TO DELHI 11:00 AM
BANGALORE_CHENNAI_5:05AM
DELHI_AMRITSAR_23:00PM
AMRITSAR_DELHI_11:00PM
BANGALORE_COIMBATORE_11:30PM
Coimbatore_Bangalore_11:00PM

Answer 1

首先，我们为您的字符串替换创建一个字典，并在它们之前和之后放置一个单词边界 \b。你可以更容易地构建它，但我已经对其进行了硬编码。

然后我们将其作为替换中的参数传递

repl_dict = {r'\bdel\b' : 'delhi',
            r'\bvara\b' : 'varanasi',
            r'\bblr\b' : 'banglore',
            r'\bhyd\b' : 'hyerabad'}

df['R'] = df['Route name'].str.replace('-|_',' ').str.lower().replace(repl_dict,regex=True)

print(df)

                          Route name                                 R
0                         Del-Manali                      delhi manali
1                         Manali-Del                      manali delhi
2          Del to Katra - 46 Sleeper       delhi to katra   46 sleeper
3            Delhi to Manali 8:30 PM           delhi to manali 8:30 pm
4               Manali to Delhi 8:00              manali to delhi 8:00
5            Delhi to Manali 5:00 PM           delhi to manali 5:00 pm
6   DELHI TO KATRA 46 SEATER 8:00 PM  delhi to katra 46 seater 8:00 pm
7                    Lucknow to Vara               lucknow to varanasi
8               DELHI_MANALI_05:00PM              delhi manali 05:00pm
9            Delhi To Manali 10:30pm           delhi to manali 10:30pm
10             MANALI TO DEL 5:00 PM           manali to delhi 5:00 pm
11             10:15 Lucknow To Vara         10:15 lucknow to varanasi
12               MANALI_DELHI_6:00PM               manali delhi 6:00pm
13               MANALI_DELhi_4.00PM               manali delhi 4.00pm
14               Delhi_Manali_6:00PM               delhi manali 6:00pm
15                BLR_CHENNAI_1:30PM           banglore chennai 1:30pm
16               CHENNAI_BLR_11:00PM          chennai banglore 11:00pm
17         BANGALORE_CHENNAI_11:05PM         bangalore chennai 11:05pm
18          CHENNAI_BANGALORE_5:30AM          chennai bangalore 5:30am
19                           Hyd_Blr                 hyerabad banglore
20       BANGALORE_HYDERABAD_ 7:45PM       bangalore hyderabad  7:45pm
21          CHENNAI_BANGALORE_5:45AM          chennai bangalore 5:45am
22                 DELHI TO DEHRADUN                 delhi to dehradun
23                 DEHRADUN TO DELHI                 dehradun to delhi
24          Delhi to Katra UP22T8671          delhi to katra up22t8671
25         BANGALORE_CHENNAI_10:45PM         bangalore chennai 10:45pm
26   Delhi-Lucknow 9:00PM 30 sleeper   delhi lucknow 9:00pm 30 sleeper
27         CHENNAI_BANGALORE_10:30PM         chennai bangalore 10:30pm
28              Lucknow_Vara_10:30PM          lucknow varanasi 10:30pm
29           VARANASI_LUCKNOW_9:30PM           varanasi lucknow 9:30pm
30       Delhi to Jalandhar 10:00 PM       delhi to jalandhar 10:00 pm
31       JALANDHAR TO DELHI 11:00 AM       jalandhar to delhi 11:00 am
32          BANGALORE_CHENNAI_5:05AM          bangalore chennai 5:05am
33            DELHI_AMRITSAR_23:00PM            delhi amritsar 23:00pm
34            AMRITSAR_DELHI_11:00PM            amritsar delhi 11:00pm
35      BANGALORE_COIMBATORE_11:30PM      bangalore coimbatore 11:30pm
36      Coimbatore_Bangalore_11:00PM      coimbatore bangalore 11:00pm