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Python函數只返回第一個值而不是數據框 [英] Python function returns only the first value instead of a dataframe

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本文介紹了Python函數只返回第一個值而不是數據框的處理方法,對大家解決問題具有一定的參考價值,需要的朋友們下面隨著小編來一起學習吧!

問題描述

我已經構建了一個函數,我將 5 個投資組合的回報附加到我想要返回到變量的數據框中.當我逐行運行函數中的命令(一種調試)時,我最終得到具有正確數量的值(例如 5)的變量 'folioReturn'(這是我希望我的腳本返回的那個).但是如果我調用該函數,則只返回數據幀的第一個值.有誰知道我怎樣才能得到整個數據框?

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)

推薦答案

return 語句必須在 for 循環之后,如果你想要整個列表在你的情況下在第一個循環中只返回值.只需從 for 循環中刪除 return 它就可以正常工作.

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)

這篇關于Python函數只返回第一個值而不是數據框的文章就介紹到這了,希望我們推薦的答案對大家有所幫助,也希望大家多多支持IT屋!

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