Resolving TypeError in Python code

Question

I'm basically running some code as follows. Basically I'm just retrieving pairs of stocks (laid out as Row 1-Stock 1,2, Row 2-Stock 1,2 and so on, where Stock 1 and 2 are different in each row) from a CSV File. I then take in data from Yahoo associated with these "Pairs" of Stocks. I calculate the returns of the stocks and basically check if the distance (difference in returns) between a pair of stocks breaches some threshold and if so I return 1. However, I'm getting the following error which I am unable to resolve:

PricePort(tickers)
     27     for ticker in tickers:
     28         #print ticker
---> 29         x = pd.read_csv('http://chart.yahoo.com/table.csv?s=ttt'.replace('ttt',ticker),usecols=[0,6],index_col=0)
     30         x.columns=[ticker]
     31         final=pd.merge(final,x,left_index=True,right_index=True)

TypeError: expected a character buffer object

The code is as follows:

from datetime import datetime
import pytz
import csv
import pandas as pd
import pandas.io.data as web
import numpy as np

#Retrieves pairs of stocks (laid out as Row 1-Stock 1,2, Row 2-Stock 1,2 and   so on, where Stock 1 and 2 are different in each row) from CSV File
def Dataretriever():
        Pairs = []
        f1=open('C:\Users\Pythoncode\Pairs.csv') #Enter the location of the file
        csvdata= csv.reader(f1)
        for row in csvdata:          #reading tickers from the csv file
            Pairs.append(row)
        return Pairs

tickers = Dataretriever() #Obtaining the data

#Taking in data from Yahoo associated with these "Pairs" of Stocks
def PricePort(tickers):
    """
        Returns historical adjusted prices of a portfolio of stocks.
        tickers=pairs
    """
    final=pd.read_csv('http://chart.yahoo.com/table.csv?s=^GSPC',usecols=[0,6],index_col=0)
    final.columns=['^GSPC']
    for ticker in tickers:
        #print ticker
        x = pd.read_csv('http://chart.yahoo.com/table.csv?s=ttt'.replace('ttt',ticker),usecols=[0,6],index_col=0)
        x.columns=[ticker]
        final=pd.merge(final,x,left_index=True,right_index=True)
    return final   

#Calculating returns of the stocks
def Returns(tickers):
    l = []
    begdate=(2014,1,1)
    enddate=(2014,6,1)    
    p = PricePort(tickers)
    ret = (p.close[1:] - p.close[:-1])/p.close[1:]
    l.append(ret)
    return l

#Basically a class to see if the distance (difference in returns) between a 
#pair of stocks breaches some threshold
class ThresholdClass():    
    #constructor
    def __init__(self, Pairs):
        self.Pairs = Pairs

    #Calculating the distance (difference in returns) between a pair of stocks
    def Distancefunc(self, tickers):
        k = 0
        l = Returns(tickers)
        summation=[[0 for x in range (k)]for x in range (k)]      #2d matrix for the squared distance
        for i in range (k):
            for j in range (i+1,k):     # it will be a upper triangular matrix
                for p in range (len(self.PricePort(tickers))-1):
                    summation[i][j]= summation[i][j] + (l[i][p] - l[j][p])**2       #calculating distance

        for i in range (k):     #setting the lower half of the matrix 1 (if we see 1 in the answer we will set a higher limit but typically the distance squared is less than 1)
            for j in range (i+1):
                sum[i][j]=1
            return sum

    #This function is used in determining the threshold distance
    def MeanofPairs(self, tickers):
        sum = self.Distancefunc(tickers)
        mean = np.mean(sum)
        return mean

    #This function is used in determining the threshold distance
    def StandardDeviation(self, tickers):
        sum = self.Distancefunc(tickers)
        standard_dev = np.std(sum)
        return standard_dev 


    def ThresholdandnewsChecker(self, tickers):
        threshold = self.MeanofPairs(tickers) + 2*self.StandardDeviation(tickers)
        if (self.Distancefunc(tickers) > threshold):
            return 1 

Threshold_Class  = ThresholdClass(tickers)   
Threshold_Class.ThresholdandnewsChecker(tickers,1)

Alex Riley · Accepted Answer · 2015-04-21 14:47:18Z

1

The trouble is Dataretriever() returns a list, not a string. When you iterate over tickers(), the name ticker is bound to a list.

The str.replace method expects both arguments to be strings. The following code raises the error because the second argument is a list:

'http://chart.yahoo.com/table.csv?s=ttt'.replace('ttt', ticker)

The subsequent line x.columns = [ticker] will cause similar problems. Here, ticker needs to be a hashable object (like a string or integer), but lists are not hashable.

edited Apr 21, 2015 at 14:47

answered Apr 21, 2015 at 13:30

Alex Riley

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7 Comments

user131983 Over a year ago

Thanks. I edited my code as follows, yet I still have the same issue:

tickersasstrings = map(str, tickers)         def PricePort(tickersasstrings):     final=pd.read_csv('http://chart.yahoo.com/table.csv?s=^GSPC',usecols=[0,6],index_col=0)     final.columns=['^GSPC']     for ticker in tickersasstrings:         #print ticker         x = pd.read_csv('http://chart.yahoo.com/table.csv?s=ttt'.replace('ttt',ticker),usecols=[0,6],index_col=0)         x.columns=[ticker]         final=pd.merge(final,x,left_index=True,right_index=True)     return final

Alex Riley Over a year ago

I'd guess it's because of the x.columns=[ticker] bit. x.columns needs to assigned to a list strings or numbers (hashable) not a list of lists (unhashable).

user131983 Over a year ago

Thanks Again. I tried changing it to x.columns = ticker as it would then just be assigned a list of strings, however this does not appear to resolve the issue. Could there be another problem?

Alex Riley Over a year ago

Nothing jumps out - what's the new error message you're getting?

user131983 Over a year ago

Its the same one as before.

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