Question

考虑pandas中的以下数据框

   date     action    price     
  20150101   buy       10
  20150102   buy       9
  20150103   sell      11
  20150104   sell      10
  20150105   buy       8
  20150106   sell      9

如果我想在每次出售＆＃39;时添加行转入“购买”，插入行只是上一行的副本，除了更改＆＃39; sell＆＃39;进入＆＃39;购买＆＃39;如下：

   date     action    price     
  20150101   buy       10
  20150102   buy       9
  20150103   sell      11
  20150104   sell      10
**20150104   buy       10**
  20150105   buy       8
  20150106   sell      9
**20150106   buy       9 **

感谢您的帮助。

Answer 1

您可以使用

标识转换行

mask = (df['action'] == 'sell') & (df['action'].shift(-1) != 'sell')
# In [229]: mask
# Out[229]: 
# 0    False
# 1    False
# 2    False
# 3     True
# 4    False
# 5     True
# Name: action, dtype: bool

然后你可以创建一个新的DataFrame，其中包含mask为True的行：

new = df.loc[mask].copy()

将操作设置为'buy'：

new['action'] = 'buy'
#        date action  price
# 3  20150104    buy     10
# 5  20150106    buy      9

构建一个新的DataFrame，用于连接df和new：

df = pd.concat([df, new])

并按date排序：

df = df.sort(['date'])

例如，

import pandas as pd
df = pd.read_table('data', sep='\s+')
mask = (df['action'] == 'sell') & (df['action'].shift(-1) != 'sell')
new = df.loc[mask].copy()
new['action'] = 'buy'
df = pd.concat([df, new])
df = df.sort(['date'])
df = df.reset_index(drop=True)
print(df)

产量

       date action  price
0  20150101    buy     10
1  20150102    buy      9
2  20150103   sell     11
3  20150104   sell     10
4  20150104    buy     10
5  20150105    buy      8
6  20150106   sell      9
7  20150106    buy      9

根据pandas数据帧中的列值插入行

1 个答案: