即使在examp之后也无法加入数据帧

Question

导入模块：

import Quandl
import pandas as pd
from pandas.tools.plotting import df_unique

读取api密钥：

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目前该函数读取一个csv文件来获取代码，但我计划将其更改为sqllite。。在

def stock_list():
    #stocks = pd.read_csv('TID.csv'.rstrip())
    stocks = open('TID.csv').readlines()

    return stocks[0:]

从quandl那里得到股票代码这是一种享受。在

def getStockValues():    
    stocks = stock_list()
    main_df = pd.DataFrame()

    for abbrv in stocks:

         query = "LSE/" + str(abbrv).strip()

         df = Quandl.get(query, authtoken=api_key,start_date='2016-04-05', end_date='2016-04-10')
         df = df['Price']
         df.columns = [abbrv]
         print(query)
         print(df)

这一声明由于某种原因导致了问题，同时它不能加入额外的股票价格。在

        #This statement Prints as   
         print(df.tail(5))
        #causes error             
         if main_df.empty:
           main_df = df
         else:
           main_df = main_df.join(df)
#             exit

    print('Task done!')


getStockValues()

这是print语句的输出和join的错误。在

Result:

LSE/VOD
Date
2016-04-14    226.80
2016-04-15    229.75

<ETC for all stocks>

Traceback (most recent call last):
  File "H:\Workarea\DataB\SkyDriveP\OneDrive\PyProjects\Learning\21 myPprojects\stockPrices.py", line 49, in <module>
    getStockValues()
  File "H:\Workarea\DataB\SkyDriveP\OneDrive\PyProjects\Learning\21 myPprojects\stockPrices.py", line 43, in getStockValues
    main_df = main_df.join(df)
  File "H:\APPS\Python35-32\lib\site-packages\pandas\core\generic.py", line 2669, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'Series' object has no attribute 'join'

进一步的测试表明，问题似乎与pandas数据对象的范围有关，这导致和问题：

main_df = pd.DataFrame()

for abbrv in stocks:        
     query = "LSE/" + str(abbrv).strip()       
     df = Quandl.get(query, authtoken=api_key,start_date='2016-03-05', end_date='2016-04-10')
     df = df['Price']
     df.columns = [abbrv]
    #causes error             
     if main_df.empty:
       main_df = df
     else:
       main_df = main_df.join(df)

但是，这不会导致错误，但只返回一个数据集：

for abbrv in stocks: 
    main_df = pd.DataFrame()
    query = "LSE/" + str(abbrv).strip()       
    df = Quandl.get(query, authtoken=api_key,start_date='2016-03-05', end_date='2016-04-10')
    df = df['Price']
    df.columns = [abbrv]

    if main_df.empty:
        main_df = df
    else:
        main_df = main_df.join(df)

Answer 1

在我看来，你的代码问题就在这里：

...
df = df['Price'] ## <- you are turning the DataFrame to a Series here
df.columns = [abbrv] ## <- no effect whatsoever on a Series
print(query)
print(df)

相反，我只需将新行添加到现有的数据帧中。在

^{pr2}$