我正在尝试从yfinance下载股票数据。我有一个名为ticker_list_1的股票报价器列表，其中包含一堆符号。其结构如下：

array(['A', 'AAP', 'AAPL', 'ABB', 'ABBV', 'ABC', 'ABEV', 'ABMD', 'ABNB',....

现在我使用下面的代码来下载数据：

i = 0
xrz_data = {}
for i, len in enumerate (ticker_list_1):      
   data = yf.download(ticker_list_1[i], start ="2019-01-01", end="2022-10-20")
   xrz_data[i] = data
   i=i+1

我遇到的问题是，一旦下载了数据，数据就保存为xrz_data。我可以通过代码xrz_data[I]和相应的编号访问特定的数据集。但是，我希望能够通过xrz_data[tickername]访问数据。
我如何才能做到这一点？
我试过使用xrz_data[i].values = data，它给了我错误KeyError：0
下面是for循环的当前输出：

{0:                   Open        High         Low       Close   Adj Close  \
     Date                                                                     
     2018-12-31   66.339996   67.480003   66.339996   67.459999   65.660202   
     2019-01-02   66.500000   66.570000   65.300003   65.690002   63.937435   
     2019-01-03   65.529999   65.779999   62.000000   63.270000   61.582008   
     2019-01-04   64.089996   65.949997   64.089996   65.459999   63.713589   
     2019-01-07   65.639999   67.430000   65.610001   66.849998   65.066483   
     ...                ...         ...         ...         ...         ...   
     2022-10-13  123.000000  128.830002  122.349998  127.900002  127.900002   
     2022-10-14  129.000000  130.220001  125.470001  125.699997  125.699997   
     2022-10-17  127.379997  131.089996  127.379997  130.559998  130.559998   
     2022-10-18  133.919998  134.679993  131.199997  132.300003  132.300003   
     2022-10-19  130.110001  130.270004  127.239998  128.960007  128.960007
[959 rows x 6 columns],

     1:                   Open        High         Low       Close   Adj Close  \
     Date                                                                     
     2018-12-31  156.050003  157.679993  154.990005  157.460007  149.844055   
     2019-01-02  156.160004  159.919998  153.820007  157.919998  150.281815   
    ........

我期望的输出是：

AAP:                   Open        High         Low       Close   Adj Close  \
 Date                                                                     
 2018-12-31  156.050003  157.679993  154.990005  157.460007  149.844055   
 2019-01-02  156.160004  159.919998  153.820007  157.919998  150.281815   
........