简单Python熊猫：将数据转换为熊猫数据帧

我已经生成了 （i） 日期：年月日 （二）价格 （iii）指示器，来自以下功能：

(array([ 20130128.,  20130129.,  20130130.,  20130131.,  20130201.,
         20130204.,  20130205.,  20130206.,  20130207.,  20130208.]),
 array([ 56.02,  55.6 ,  56.  ,  56.12,  56.86,  56.09,  56.2 ,  56.05,
         55.86,  56.37]),
 [-5.4958212306431209,
  -5.4965882164300091,
  -5.5007207046890292,
  -5.5055537754993047,
  -5.5111633791272423,
  -5.5182838425602752,
  -5.5276187056817143,
  -5.5422982532120697,
  -5.5530410183875532,
  -5.5540498754024412])

---

有人能指导我如何将其转换为数据帧吗？

使用字典并将其传递给数据帧对象

pd.DataFrame({'dates':pd.to_datetime([ 20130128,  20130129,  20130130,  20130131,  20130201,
     20130204,  20130205,  20130206,  20130207,  20130208], format='%Y%m%d'),\
'prices':array([ 56.02,  55.6 ,  56.  ,  56.12,  56.86,  56.09,  56.2 ,  56.05,
     55.86,  56.37]),\
'indicators':array([-5.4958212306431209,
 -5.4965882164300091,
 -5.5007207046890292,
 -5.5055537754993047,
 -5.5111633791272423,
 -5.5182838425602752,
 -5.5276187056817143,
 -5.5422982532120697,
 -5.5530410183875532,
 -5.5540498754024412])})

---

非常感谢您回复Giolelm！我找到了一个解决方案：

import datetime

outt = indf   #indf is the function generating the data


dates1 = pd.to_datetime(outt[0], format='%Y%m%d')
type(dates1)
dates1 = dates1.tolist()
type(dates1)

price = outt[1]
type(price)

indicator = numpy.asarray(outt[2])
type(indicator)


s1 = pd.Series(price, index=dates1)
s2 = pd.Series(indicator, index=dates1)

df = pd.concat([s1, s2], axis=1)
df.columns = ['price', 'indicator']
df

#            price  indicator
#2013-01-28  56.02  -5.495821
#2013-01-29  55.60  -5.496588
#2013-01-30  56.00  -5.500721
#2013-01-31  56.12  -5.505554
#2013-02-01  56.86  -5.511163
#2013-02-04  56.09  -5.518284
#2013-02-05  56.20  -5.527619
#2013-02-06  56.05  -5.542298
#2013-02-07  55.86  -5.553041
#2013-02-08  56.37  -5.554050

---

你试过什么吗？。这是文档处理的第一件事情。是的，但没有什么值得一提的——我对python/pandas是新手