我有一个数据帧有一个(字符串)列，我想把它分成两个(字符串)列，其中一个列标题为“fips”和另一个“行”
我的数据框架df看起来是这样的:
row
0 00000 UNITED STATES
1 01000 ALABAMA
2 01001 Autauga County, AL
3 01003 Baldwin County, AL
4 01005 Barbour County, AL
我不知道如何使用df.row。Str[:]来实现拆分行单元格的目标。我可以使用df['fips'] = hello添加一个新列，并用hello填充它。什么好主意吗?
fips row
0 00000 UNITED STATES
1 01000 ALABAMA
2 01001 Autauga County, AL
3 01003 Baldwin County, AL
4 01005 Barbour County, AL
当前回答
没想到我还没见过这个。如果你只需要两段，我强烈推荐…
Series.str.partition
分区在分隔符上执行一次分割，通常性能相当好。
df['row'].str.partition(' ')[[0, 2]]
0 2
0 00000 UNITED STATES
1 01000 ALABAMA
2 01001 Autauga County, AL
3 01003 Baldwin County, AL
4 01005 Barbour County, AL
如果需要重命名行，
df['row'].str.partition(' ')[[0, 2]].rename({0: 'fips', 2: 'row'}, axis=1)
fips row
0 00000 UNITED STATES
1 01000 ALABAMA
2 01001 Autauga County, AL
3 01003 Baldwin County, AL
4 01005 Barbour County, AL
如果你需要把它连接回原来的，使用join或concat:
df.join(df['row'].str.partition(' ')[[0, 2]])
pd.concat([df, df['row'].str.partition(' ')[[0, 2]]], axis=1)
row 0 2
0 00000 UNITED STATES 00000 UNITED STATES
1 01000 ALABAMA 01000 ALABAMA
2 01001 Autauga County, AL 01001 Autauga County, AL
3 01003 Baldwin County, AL 01003 Baldwin County, AL
4 01005 Barbour County, AL 01005 Barbour County, AL
其他回答
df[['fips', 'row']] = df['row'].str.split(' ', n=1, expand=True)
我发现没人用切片法，所以我把2美分写在这里。
df["<col_name>"].str.slice(stop=5)
df["<col_name>"].str.slice(start=6)
该方法将创建两个新列。
我更喜欢导出相应的pandas系列(即我需要的列)，使用apply函数将列内容拆分为多个系列，然后将生成的列连接到现有的DataFrame。当然，源列应该被删除。
如。
col1 = df["<col_name>"].apply(<function>)
col2 = ...
df = df.join(col1.to_frame(name="<name1>"))
df = df.join(col2.toframe(name="<name2>"))
df = df.drop(["<col_name>"], axis=1)
分割两个单词的字符串函数应该是这样的:
lambda x: x.split(" ")[0] # for the first element
lambda x: x.split(" ")[-1] # for the last element
你可以使用str.split by空格(默认分隔符)和参数expand=True为DataFrame赋值给新列:
df = pd.DataFrame({'row': ['00000 UNITED STATES', '01000 ALABAMA',
'01001 Autauga County, AL', '01003 Baldwin County, AL',
'01005 Barbour County, AL']})
print (df)
row
0 00000 UNITED STATES
1 01000 ALABAMA
2 01001 Autauga County, AL
3 01003 Baldwin County, AL
4 01005 Barbour County, AL
df[['a','b']] = df['row'].str.split(n=1, expand=True)
print (df)
row a b
0 00000 UNITED STATES 00000 UNITED STATES
1 01000 ALABAMA 01000 ALABAMA
2 01001 Autauga County, AL 01001 Autauga County, AL
3 01003 Baldwin County, AL 01003 Baldwin County, AL
4 01005 Barbour County, AL 01005 Barbour County, AL
修改，如果需要删除原始列datafframe .pop
df[['a','b']] = df.pop('row').str.split(n=1, expand=True)
print (df)
a b
0 00000 UNITED STATES
1 01000 ALABAMA
2 01001 Autauga County, AL
3 01003 Baldwin County, AL
4 01005 Barbour County, AL
什么是一样的:
df[['a','b']] = df['row'].str.split(n=1, expand=True)
df = df.drop('row', axis=1)
print (df)
a b
0 00000 UNITED STATES
1 01000 ALABAMA
2 01001 Autauga County, AL
3 01003 Baldwin County, AL
4 01005 Barbour County, AL
如果get错误:
#remove n=1 for split by all whitespaces
df[['a','b']] = df['row'].str.split(expand=True)
ValueError:列的长度必须与键的长度相同
你可以检查，它返回4列DataFrame，而不是只有2:
print (df['row'].str.split(expand=True))
0 1 2 3
0 00000 UNITED STATES None
1 01000 ALABAMA None None
2 01001 Autauga County, AL
3 01003 Baldwin County, AL
4 01005 Barbour County, AL
那么解决方案是通过join追加新的DataFrame:
df = pd.DataFrame({'row': ['00000 UNITED STATES', '01000 ALABAMA',
'01001 Autauga County, AL', '01003 Baldwin County, AL',
'01005 Barbour County, AL'],
'a':range(5)})
print (df)
a row
0 0 00000 UNITED STATES
1 1 01000 ALABAMA
2 2 01001 Autauga County, AL
3 3 01003 Baldwin County, AL
4 4 01005 Barbour County, AL
df = df.join(df['row'].str.split(expand=True))
print (df)
a row 0 1 2 3
0 0 00000 UNITED STATES 00000 UNITED STATES None
1 1 01000 ALABAMA 01000 ALABAMA None None
2 2 01001 Autauga County, AL 01001 Autauga County, AL
3 3 01003 Baldwin County, AL 01003 Baldwin County, AL
4 4 01005 Barbour County, AL 01005 Barbour County, AL
与删除原始列(如果还有其他列):
df = df.join(df.pop('row').str.split(expand=True))
print (df)
a 0 1 2 3
0 0 00000 UNITED STATES None
1 1 01000 ALABAMA None None
2 2 01001 Autauga County, AL
3 3 01003 Baldwin County, AL
4 4 01005 Barbour County, AL
如果你想根据分隔符将一个字符串分割成两个以上的列，你可以省略'maximum splitting '参数。 你可以使用:
df['column_name'].str.split('/', expand=True)
这将自动创建与任何初始字符串中包含的最大字段数量相同的列。
