将字典转换为 Dataframe

Question

我试图通过 IEX API 循环代码符号列表，以获得大量代码的市账率。 最终目标是在一个 csv 文件中包含所有的市账率。 对于多个代码，它以我没有很多经验的字典形式返回资产负债表信息。

以下代码仅使用单个代码，其中资产负债表返回位于 dataframe 中。

import pandas as pd
from iexfinance.stocks import Stock
from datetime import datetime
import matplotlib.pyplot as plt
from iexfinance.stocks import get_historical_data
from pathlib import Path
import numpy as np
import csv

output_file = pd.DataFrame()

filename = r'C:\Users########'

Ticker = []
with open(filename, newline='') as inputfile:
    for row in csv.reader(inputfile):
        Ticker.append(row[0])

for i in Ticker:
#Obtain information for ticker company when using a single ticker
#Ticker = ['FRT']

    #Obtaining Balance Sheets
    stock = Stock(Ticker, token='##################', output_format='pandas')
    bs = stock.get_balance_sheet()

    #Obtaining the common stock outstanding on the last filing
    common_stock_outstanding = stock.get_shares_outstanding()

    #Obtaining the current price
    current_price = stock.get_price()

    #Obtaining the Market Cap
    market_cap = common_stock_outstanding * current_price

    #Obtaining the BV per share
    bs['BV'] = bs['shareholderEquity'] / common_stock_outstanding
    bs.drop(bs.iloc[:, 0:38], inplace = True, axis = 1)
    BV = pd.DataFrame(bs)
    BV.columns = ['1']
    BV = BV.reset_index(drop=True)

    #Obtaining the Price to Book
    current_price = pd.DataFrame(current_price)
    current_price = current_price.reset_index(drop=True)
    current_price.columns = ['2']
    current_price

    PtB = pd.merge(BV, current_price, left_index=True, right_index=True)

    PtB['PtB'] = PtB['2'] / PtB['1']
    PtB.drop(PtB.iloc[:, 0:2], inplace = True, axis = 1)
    PtB.columns = [Ticker]

    #Appending the PtB into the Output File
    output_file = pd.DataFrame()
    output_file = output_file.append(PtB)
    output_file

这是两个 Ticker RFP 和 APA 的返回 output：

 {'RFP':             accountsPayable capitalSurplus  commonStock currency  \
 2021-03-01        251000000           None     82200000      USD   

             currentAssets  currentCash  currentLongTermDebt filingType  \
 2021-03-01      900000000    113000000              2000000       10-K   

             fiscalDate  fiscalQuarter  ...  symbol  totalAssets  \
 2021-03-01  2020-12-31              4  ...     RFP   3730000000   

             totalCurrentLiabilities  totalLiabilities  treasuryStock  \
 2021-03-01                380000000        2649000000     -174000000   

                        id  key     subkey           date        updated  
 2021-03-01  BALANCE_SHEET  RFP  quarterly  1609372800000  1614775188000  

 [1 rows x 38 columns],
 'APA':             accountsPayable capitalSurplus  commonStock currency  \
 2020-07-30        459000000           None  12006000000      USD   

             currentAssets  currentCash  currentLongTermDebt filingType  \
 2020-07-30     1658000000    135000000            294000000       10-Q   

             fiscalDate  fiscalQuarter  ...  symbol  totalAssets  \
 2020-07-30  2020-06-30              2  ...     APA  12999000000   

             totalCurrentLiabilities  totalLiabilities  treasuryStock  \
 2020-07-30               1710000000       14634000000    -3189000000   

                        id  key     subkey           date        updated  
 2020-07-30  BALANCE_SHEET  APA  quarterly  1593475200000  1608330865000  

 [1 rows x 38 columns]}

我试图使用 pd.DataFrame.from_dict(bs, orient='index') 将字典的字典放入 dataframe 但收到错误：

KeyError                                  Traceback (most recent call last)
~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
   2896             try:
-> 2897                 return self._engine.get_loc(key)
   2898             except KeyError:

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 0

During handling of the above exception, another exception occurred:

KeyError                                  Traceback (most recent call last)
<ipython-input-17-b29d66f7b6fd> in <module>
----> 1 pd.DataFrame.from_dict(bs, orient='index')

~\Anaconda3\lib\site-packages\pandas\core\frame.py in from_dict(cls, data, orient, dtype, columns)
   1188             raise ValueError("only recognize index or columns for orient")
   1189 
-> 1190         return cls(data, index=index, columns=columns, dtype=dtype)
   1191 
   1192     def to_numpy(self, dtype=None, copy=False):

 ~\Anaconda3\lib\site-packages\pandas\core\frame.py in __init__(self, data, index, columns, dtype, copy)
    462                     mgr = arrays_to_mgr(arrays, columns, index, columns, dtype=dtype)
    463                 else:
--> 464                     mgr = init_ndarray(data, index, columns, dtype=dtype, copy=copy)
    465             else:
    466                 mgr = init_dict({}, index, columns, dtype=dtype)

 ~\Anaconda3\lib\site-packages\pandas\core\internals\construction.py in init_ndarray(values, index, 
 columns, dtype, copy)
    169     # by definition an array here
    170     # the dtypes will be coerced to a single dtype
--> 171     values = prep_ndarray(values, copy=copy)
    172 
    173     if dtype is not None:

~\Anaconda3\lib\site-packages\pandas\core\internals\construction.py in prep_ndarray(values, copy)
    274         try:
    275             if is_list_like(values[0]) or hasattr(values[0], "len"):
--> 276                 values = np.array([convert(v) for v in values])
    277             elif isinstance(values[0], np.ndarray) and values[0].ndim == 0:
    278                 # GH#21861

~\Anaconda3\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
    2978             if self.columns.nlevels > 1:
    2979                 return self._getitem_multilevel(key)
 -> 2980             indexer = self.columns.get_loc(key)
    2981             if is_integer(indexer):
    2982                 indexer = [indexer]

~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
    2897                 return self._engine.get_loc(key)
    2898             except KeyError:
 -> 2899                 return self._engine.get_loc(self._maybe_cast_indexer(key))
    2900         indexer = self.get_indexer([key], method=method, tolerance=tolerance)
    2901         if indexer.ndim > 1 or indexer.size > 1:

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 0

我知道代码的构建效率可能很低，但此时我只想了解如何使用这个字典 output 的字典。 必须有办法做到这一点，但目前这超出了我的技能范围。 谢谢你的帮助。

Answer 1

在您提供您尝试从中创建数据框的确切字典之前，我认为我们无法为您提供帮助。 无论如何，作为示例，请看以下示例：

>>data = {'name': {'first':'hary', 'second':'porter'}, 'address':{'temp': 'USA', 'perm': 'UK'}}
>>data
{'name': {'first': 'hary', 'second': 'porter'}, 'address': {'temp': 'USA', 'perm': 'UK'}}
>>pd.DataFrame(data)
          name address
first     hary     NaN
second  porter     NaN
temp       NaN     USA
perm       NaN      UK

Answer 2

Dataframe 也采用参数字典。

d = {'col1': [1, 2], 'col2': [3, 4]}
df = pd.DataFrame(data=d)

Output：

col1=1,2  col2 = 3,4