在pandas中将列元素转换为列名

Question

我有一个大的.csv文件，它不断地被实时更新，几千行显示如下：

 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

将其读入dataframe的最快方法是什么：

^{pr2}$

感谢任何帮助

Answer 1

我想这里有一个更简洁的方法。在

 df = pd.read_csv('prices.csv', header=None, names=['time', 'stock', 'type',   'prices'], 
                  index_col=['time', 'stock', 'type'])

In [1062]:

df
Out[1062]:
                    prices
time    stock   type    
time1   stockA  bid 1.0
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
time7   stockA  high1.5
time8   stockA  low 0.5

我认为数据帧应该是这样的。 那就去吧

^{pr2}$

您可以使用df.fillna将您喜欢的任何内容填充到nan中。一般来说，将列值转换为列标题称为透视。.unstack旋转多索引的一个级别。您也可以检查.pivot。在

Answer 2

您可以使用read_csv并指定header=None，并将列名作为列表传递：

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bid列重新编码为1或2：

^{pr2}$

编辑

根据您更新的样本数据和期望的输出，以下工作：

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