Unable to join a dataframe even after following an example

Question

Imports modules:

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

read api key:

api_key = open('quandlapikey.txt','r').read()

Currently the function reads a csv file to get the codes however I plan to change this to sqllite..

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

    return stocks[0:]

Get stock codes from quandl this works a treat.

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)

This statement causes the issues for some reason whilst looping it cannot join additional stock prices.

        #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()

This is the output from the print statements and error from the join.

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'

Further tests show that the issue seems to be with the scope of the pandas data object this causes and issue:

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)

However this does not cause an error however only returns one dataset:

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

Seems to me that the issue with your code is somewhere around here:

...
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)

What I would do instead is simply add the new row to your existing DataFrame.

## if main_df.empty: ## <- remove this line
##    main_df = df ## This should be changed to the line below
main_df[abbrv] = df ## This will just add the new column to you df and use the Series as data
## else: ## <- remove this line
##    main_df = main_df.join(df) ## <- remove this line