Question

我有以下pandas数据帧：

    Category    Symbol              Quantity    Cost Price
1   Stocks      AKAM                200         49.22696796
3   Stocks      APA                 1900        50.607305856
8   Options     AA 30JUN17 27.0 P    17         0.127931
11  Options     AA 30JUN17 28.0 P   -17         0.172045076
14  Options     AABA 21JUL17 60.0 C -7          0.34204137
17  Options     AABA 21JUL17 62.5 C  7          0.217931

我想在符号选项类别中插入列。像这样：

    Category    Symbol  Expiry  Strike  Right       Quantity    Cost Price
1   Stocks      AKAM                                 200        49.22696796
3   Stocks      APA                                 1900        50.607305856
8   Options     AA      30JUN17 27.0    P             17        0.127931
11  Options     AA      30JUN17 28.0    P            -17        0.172045076
14  Options     AABA    21JUL17 60.0    C             -7        0.34204137
17  Options     AABA    21JUL17 62.5    C              7        0.217931

我尝试了以下代码，但它不起作用：

for i, row in s.iterrows():
    if len(s.Symbol[i])>4:
        s = s.set_value(i, "Symbol", s.Symbol[i].split(' ',1).tolist(), columns = ["Symbol", "Expiry", "Strike", "Right" ])

感谢任何帮助。谢谢！

Answer 1

让我们assign和split：

df.assign(**df.Symbol.str.split(' ',expand=True).rename(columns={0:'Symbol',1:'Expiry',2:'Strike',3:'Right'}))

输出：

   Category Symbol  Quantity  Cost Price   Expiry Right Strike
1    Stocks   AKAM       200   49.226968     None  None   None
3    Stocks    APA      1900   50.607306     None  None   None
8   Options     AA        17    0.127931  30JUN17     P   27.0
11  Options     AA       -17    0.172045  30JUN17     P   28.0
14  Options   AABA        -7    0.342041  21JUL17     C   60.0
17  Options   AABA         7    0.217931  21JUL17     C   62.5

Answer 2

使用pd.DataFrame([x.split() for x in df.Symbol])

In [34]: df
Out[34]: 
  Symbol
0      a
1  a b c
2  d e f

In [35]: df[['Symbol','c1','c2']]=pd.DataFrame([x.split() for x in df.Symbol])

In [36]: df
Out[36]: 
  Symbol    c1    c2
0      a  None  None
1      a     b     c
2      d     e     f

在pandas数据框中插入列

2 个答案: