Question

我有一个具有以下键的数据框：

tourist_spot,
nearest landmark,
longitute(landmark),
latitude(landmark),
nearest police station,
longitute(PS),
latitude(PS),
nearest bus stop,
longitute(BS),
latitude(BS),
nearest taxi stand,
longitute(TS),
latitude(TS)

以及其他类似的列。我想要实现的是这样的：

name,
type,
latitude,
longitude,
nearest_to

name将具有地标的名称或PS或BS等。 Type将指示地点的类型。例如，警察局的PS等。 latitude和longitude将是每个地点的位置，而nearest_to将是tourist_spot的名称。

样本数据：

tourist_spot                ts1
nearest landmark            nl1
longitute(landmark)         4
latitude(landmark)          5
nearest police station      ps1
longitute(PS)               7
latitude(PS)                8
nearest bus stop            bs1
longitute(BS)               9
latitude(BS)                10
nearest taxi stand          ts1
longitute(TS)               11 
latitude(TS)                12

请转换为类似结构的表格。在这里很难做成一张大桌子。

所需的输出：

 name   type   longitude   latitude   nearest_to
    nl1    landmark   4         5           ts1
    ps1    PS         7         8           ts1

到目前为止，我的代码：

import pandas as pd
df = pd.read_excel("C:\\Users\\NCOG1\\Desktop\\Meghalaya\\Daribokgre.xlsx")
df1 = pd.DataFrame(columns=['name','type_id','longitude','latitude', 'nearby_to'])
df1['name'] = df['Nearest Landmark Name'] 
df1['type_id'] = df['Nearest Landmark Name']
df1['longitude'] = df['Longitude (of Nearest Landmark)']
df1['latitude'] = df['Latitude (of Nearest Landmark)']
df1['nearby_to'] = df['Name of Tourist Spot']

Answer 1

首先需要对包含Latitude和Longitude以及前一列的列进行解析：

df = pd.read_excel('Daribokgre.xlsx', sheet_name='Sheet2', index_col=0)
c = df.columns[df.columns.str.startswith('Latitude')]
idx = df.columns.get_indexer(c)
df1 = df.iloc[:, np.sort(np.r_[idx-1, idx, idx + 1])[1:]].reset_index()
#print (df1)

然后将数据提取到助手DataFrame中的新列：

df2 = df1.columns.to_frame(index=False)
m = df2[0].str.contains('Latitude|Longitude')
df2['type'] = df2[0].mask(m).ffill()
df2['b'] = np.where(m, df2[0].str.split(r'\s+\(', n=1).str[0], 'name')

最后创建MultiIndex并通过stack重塑形状：

df1.columns = [df2['type'], df2['b']]
df1 = (df1.stack(0)
         .reset_index(level=0, drop=True)
         .reset_index().rename(columns={1:'type'})
         .rename_axis(None, axis=1))
print (df1)
                                                type     Latitude  \
0                                           Bus Stop  25⁰33'05" N   
1                                           Landmark  25⁰33'05" N   
2                               Name of Tourist Spot  25⁰29'24" N   
3                              Nearest Hospital Name  25⁰36'01" N   
4                            Nearest Taxi Stand Name  25⁰30'45" N   
5                                     Police Station  25⁰35'53" N   
6          Restaurants or other eating joints nearby   2529'22' N   
7  Staying Options nearby (Hotels, Resorts, Homes...  25⁰29'22" N   

     Longitude                                               name  
0  90⁰19'42" E           Oragitok Jnc. Old Williamnagar-Tura road  
1  90⁰19'42" E               Oragitok Williamnagar-Tura  old road  
2  90⁰19'22" E                                         Daribokgre  
3  90⁰16'25" E                                        Asanang PHC  
4  90⁰13'01" E                                  Tura Bazaar, Tura  
5  90⁰15'14" E  Rongram Beat House whoever Daribokgre falls un...  
6   9019'21" E                                Daribokgre Homestay  
7  90⁰19'21" E                            1. Daribokgre Homestay,

如何从熊猫df中挑选多列并将其存储在另一个df中？

1 个答案: