Python函数仅返回第一个值，而不返回数据框 [英] Python function returns only the first value instead of a dataframe

问题描述

我建立了一个函数，将5个投资组合的返回值附加到要返回到变量的数据框上.当我在函数中逐行运行命令(进行调试的种类)时，我最终得到的变量'folioReturn'(我希望脚本返回的变量)具有正确的值(例如5).但是，如果我调用该函数，则仅返回数据帧的第一个值.有谁知道我如何获得整个数据框?

I have build a function where I append the returns of 5 portfolios to a dataframe which I want to return to a variable . When I run the commands within the function row by row(kind of debugging) I end upwith the variable 'folioReturn'(which is the one I want my script to return) having the right amount of values (e.x 5). But if I call the function, only the first value of the dataframe is returned. Does anyone know how I can get the whole dataframe ?

def portfolioReturns (securities, quintilesNo, perReturns):
    '''
    this function receives 
    1)securities: array with the security names and values ** for the purpose of our work the names
    should already be sorted
    2)quintilesNo: the number of portfolios we want to create 
    3)perReturns: an array with the returns that will be used for performance measuremnt

    It returns an array with the returns for each portfolio

    '''

    # we calculate the number of securities per portfolio 
    stdFolioSize = np.divmod(securities.size, quintilesNo)[0] # we take the floor division
    folioReturn = [] # pd.DataFrame()
    # we create portfolios with equal number of securities except of the last one where we use all the remaining securities
    for k in range(0, quintilesNo, 1): # in folio list we store the name of the securities we must include in each portfolio
        if k < (quintilesNo - 1):           
            folioList = securities.index.get_level_values(1)[k * stdFolioSize : (k + 1) * stdFolioSize]

        else: # the last portfolio will also include the remainder securities 
            folioList = securities.index.get_level_values(1)[k * stdFolioSize : securities.size]

        # now that we have the list of the securities to be included in the folio, we use the table
        # with the periodical returns to check the performance. The portfolio we construct is equally weighted

        # first we drop one index(the first index of the country) and then we store all the periodical returns in one-array 
        perRetFinalTable = pd.DataFrame(perReturns.reset_index(level = 0, drop = True)).T  

        # using the list of the bonds we want to include in our portfolio we pick the bond returns and
        # we store them in one array. Then we calculate the folio return
        folio = perRetFinalTable[folioList]
        folioReturn = np.append(folioReturn, folio.sum(axis = 1) * (1 / folio.size))
        folioReturn = pd.DataFrame(folioReturn).T
        # folioReturn = pd.Series(folioReturn).T

        return (folioReturn)

推荐答案

return语句必须在for循环之后，如果您希望在第一个循环中使用整个列表，则只返回该值.只需删除for循环的返回值即可.

return statement must be after the for loop if you want whole list in your case during the first loop only the value is returned. just remove the return from for loop it will work fine.

def portfolioReturns (securities, quintilesNo, perReturns):
    '''
    this function receives 
    1)securities: array with the security names and values ** for the purpose of our work the names
    should already be sorted
    2)quintilesNo: the number of portfolios we want to create 
    3)perReturns: an array with the returns that will be used for performance measuremnt

    It returns an array with the returns for each portfolio

    '''

    # we calculate the number of securities per portfolio 
    stdFolioSize = np.divmod(securities.size, quintilesNo)[0] # we take the floor division
    folioReturn = [] # pd.DataFrame()
    # we create portfolios with equal number of securities except of the last one where we use all the remaining securities
    for k in range(0, quintilesNo, 1): # in folio list we store the name of the securities we must include in each portfolio
        if k < (quintilesNo - 1):           
            folioList = securities.index.get_level_values(1)[k * stdFolioSize : (k + 1) * stdFolioSize]

        else: # the last portfolio will also include the remainder securities 
            folioList = securities.index.get_level_values(1)[k * stdFolioSize : securities.size]

        # now that we have the list of the securities to be included in the folio, we use the table
        # with the periodical returns to check the performance. The portfolio we construct is equally weighted

        # first we drop one index(the first index of the country) and then we store all the periodical returns in one-array 
        perRetFinalTable = pd.DataFrame(perReturns.reset_index(level = 0, drop = True)).T  

        # using the list of the bonds we want to include in our portfolio we pick the bond returns and
        # we store them in one array. Then we calculate the folio return
        folio = perRetFinalTable[folioList]
        folioReturn = np.append(folioReturn, folio.sum(axis = 1) * (1 / folio.size))
        folioReturn = pd.DataFrame(folioReturn).T
        # folioReturn = pd.Series(folioReturn).T

    return (folioReturn)

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