【Python pandas】去除df某列里面字符串里面的空格

对DataFrame的某一列进行操作，一般都会使用df[“xx”].str下的方法

df[ ].str.strip( )

先创建带有空格的df:

df = pd.DataFrame({'Company':['company A','company B','company C','company A'],
                   'Sales':['Peter    ','   Amy','John   ','Mi   ke']})
df
Out[38]: 
     Company      Sales
0  company A  Peter    
1  company B        Amy
2  company C    John   
3  company A    Mi   ke

.str 先要转成字符串， lstrip()表示去除左边空格

df['Sales'].str.lstrip()
Out[39]: 
0    Peter    
1          Amy
2      John   
3      Mi   ke
Name: Sales, dtype: object

.str 先要转成字符串， rstrip()表示去除左边空格

df['Sales'].str.rstrip()
Out[40]: 
0      Peter
1        Amy
2       John
3    Mi   ke
Name: Sales, dtype: object

.str 先要转成字符串， strip()表示去除左右两边，当中的空格仍在：

df['Sales'].str.strip()
Out[41]: 
0      Peter
1        Amy
2       John
3    Mi   ke
Name: Sales, dtype: object

用replace 可以替换所有的空格：

df['Sales'].str.replace(' ','')
Out[42]: 
0    Peter
1      Amy
2     John
3     Mike
Name: Sales, dtype: object

继续replace:

df['Company'].str.replace('company','')
Out[43]: 
0     A
1     B
2     C
3     A
Name: Company, dtype: object

直接用df.replace()

df.replace('company A','New')
Out[84]: 
     Company      Sales
0        New  Peter    
1  company B        Amy
2  company C    John   
3        New    Mi   ke

series.str.replace() & df.replace()的区别：

df['Sales'].str.replace('Amy','AAA')
Out[87]: 
0    Peter    
1          AAA
2      John   
3      Mi   ke
Name: Sales, dtype: object
df.replace({'Amy':'AAA','company B':'BBB'})
Out[90]: 
     Company      Sales
0  company A  Peter    
1        BBB        Amy
2  company C    John   
3  company A    Mi   ke

df.replace() 当有空格的时候才会替换，并不会替换啊单元格里面的字符串后面的空格：

df.replace(' ' ,'')
Out[91]: 
     Company      Sales
0  company A  Peter    
1  company B        Amy
2  company C    John   
3  company A    Mi   ke