可以使用 read_csv 并指定 header = None 名称作为列表：

You can use read_csv and specify header=None and pass the column names as a list:

In [124]:

t="""time1,stockA,bid,1
 time2,stockA,ask,1.1
 time3,stockB,ask,2.1
 time4,stockB,bid,2.0"""
​
df = pd.read_csv(io.StringIO(t), header=None, names=['time', 'stock', 'bid', 'ask'])
df
Out[124]:
     time   stock  bid  ask
0   time1  stockA  bid  1.0
1   time2  stockA  ask  1.1
2   time3  stockB  ask  2.1
3   time4  stockB  bid  2.0

您必须将出价栏重新编码为1或2：

You'll have to re-encode the bid column to 1 or 2:

In [126]:

df['bid'] = df['bid'].replace('bid', 1)
df['bid'] = df['bid'].replace('ask', 2)
df
Out[126]:
     time   stock  bid  ask
0   time1  stockA    1  1.0
1   time2  stockA    2  1.1
2   time3  stockB    2  2.1
3   time4  stockB    1  2.0

编辑

根据您更新的样本数据和所需输出，

Based on your updated sample data and desired output the following works:

In [29]:

t="""time1,stockA,bid,1
 time2,stockA,ask,1.1
 time3,stockB,ask,2.1
 time4,stockB,bid,2.0
 time5,stockA,bid,1.1
 time6,stockA,ask,1.2"""
​
df = pd.read_csv(io.StringIO(t), header=None, names=['time', 'stock', 'bid', 'ask'])
df
Out[29]:
     time   stock  bid  ask
0   time1  stockA  bid  1.0
1   time2  stockA  ask  1.1
2   time3  stockB  ask  2.1
3   time4  stockB  bid  2.0
4   time5  stockA  bid  1.1
5   time6  stockA  ask  1.2
In [30]:

df.loc[df['bid'] == 'bid', 'bid'] = df['ask']
df.loc[df['bid'] != 'ask', 'ask'] = ''
df.loc[df['bid'] == 'ask','bid'] = ''
df
Out[30]:
     time   stock  bid  ask
0   time1  stockA    1     
1   time2  stockA       1.1
2   time3  stockB       2.1
3   time4  stockB    2     
4   time5  stockA  1.1     
5   time6  stockA       1.2