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我正在从 quandl.com 下载财务数据集的元数据。quandl.com 的数据已经是字典格式。我想从 quandl.com 获取这些数据并将其组织到 DataFrame 中，然后将其导入 Excel。

这是文本文件（'Indicator_list.txt'），其中包含我从 quandl.com 下载的金融数据集列表。我希望将这些符号中的每一个的元数据组织成一个 DataFrame。

COM/OIL_WTI
BOE/XUDLADS
BOE/XUDLADD
BOE/XUDLB8KL
BOE/XUDLCDS
BOE/XUDLCDD

这是我正在运行的代码

import quandl
import pandas as pd

#This adjusts the layout in the command
#promt to have columns displayed side by side
pd.set_option('expand_frame_repr', False)

#This "with open" statment opens a text file that 
#has the symbols I want to get the metadata on 
with open ('Indicator_list.txt') as file_object:
    Current_indicators = file_object.read()
    tickers = Current_indicators.split('\n')

#quandlmetadata is a blank dictionary that I am
#appending the meatadata to
quandlmetadata={}

#this loops through all the values in 
#Indicator_list.txt"
for i in tickers:

    #metadata represents one set of metadata
    metadata = quandl.Dataset(i).data().meta

这是来自 quandl.com 的元数据的输出

{'start_date': datetime.date(1975, 1, 2), 'column_names': ['Date', 'Value'], 'limit': None, 'collapse': None, 'order': 'asc', 'end_date': datetime.date(2016, 11, 3), 'transform': None, 'column_index': None, 'frequency': 'daily'}

接下来，我将其添加到 quandlmetadata 字典中，并使用 indicator_list.txt " i " 中的当前符号来命名字典的键。

quandlmetadata[i]=(metadata)

这是 quandlmetadata 的输出

{'BOE/XUDLADS': {'column_names': ['Date', 'Value'], 'end_date': datetime.date(2016, 11, 3), 'transform': None, 'collapse': None, 'order': 'asc', 'start_date': datetime.date(1975, 1, 2), 'limit': None, 'column_index': None, 'frequency': 'daily'}, 'BOE/XUDLCDD': {'column_names': ['Date', 'Value'], 'end_date': datetime.date(2016, 11, 3), 'transform': None, 'collapse': None, 'order': 'asc', 'start_date': datetime.date(1975, 1, 2), 'limit': None, 'column_index': None, 'frequency': 'daily'}, 'BOE/XUDLB8KL': {'column_names': ['Date', 'Value'], 'end_date': datetime.date(2016, 11, 3), 'transform': None, 'collapse': None, 'order': 'asc', 'start_date': datetime.date(2011, 8, 1), 'limit': None, 'column_index': None, 'frequency': 'daily'}, 'COM/OIL_WTI': {'column_names': ['date', 'value'], 'end_date': datetime.date(2016, 11, 4), 'transform': None, 'collapse': None, 'order': 'asc', 'start_date': datetime.date(1983, 3, 30), 'limit': None, 'column_index': None, 'frequency': 'daily'}, 'BOE/XUDLADD': {'column_names': ['Date', 'Value'], 'end_date': datetime.date(2016, 11, 3), 'transform': None, 'collapse': None, 'order': 'asc', 'start_date': datetime.date(1975, 1, 2), 'limit': None, 'column_index': None, 'frequency': 'daily'}, 'BOE/XUDLCDS': {'column_names': ['Date', 'Value'], 'end_date': datetime.date(2016, 11, 3), 'transform': None, 'collapse': None, 'order': 'asc', 'start_date': datetime.date(1975, 1, 2), 'limit': None, 'column_index': None, 'frequency': 'daily'}}

最后我想让 quandlmetadata 字典变成一个数据框（或其他更好的方式）

这是代码的最后一部分

df = pd.DataFrame(index = quandlmetadata.keys(),columns =['transform', 'frequency', 'limit', 'end_date', 'collapse', 'column_names','start_date', 'order', 'column_index']  )

df 的输出

             transform frequency limit end_date collapse column_names start_date order column_index
BOE/XUDLB8KL       NaN       NaN   NaN      NaN      NaN          NaN        NaN   NaN          NaN
BOE/XUDLADS        NaN       NaN   NaN      NaN      NaN          NaN        NaN   NaN          NaN
BOE/XUDLADD        NaN       NaN   NaN      NaN      NaN          NaN        NaN   NaN          NaN
BOE/XUDLCDS        NaN       NaN   NaN      NaN      NaN          NaN        NaN   NaN          NaN
COM/OIL_WTI        NaN       NaN   NaN      NaN      NaN          NaN        NaN   NaN          NaN
BOE/XUDLCDD        NaN       NaN   NaN      NaN      NaN          NaN        NaN   NaN          NaN

df 的输出正是我想要的；Indicator_list.txt 中的代码是我的索引，列是 metadata.keys()。我唯一不能开始工作的是用 quandlmetadata 字典值填充 DataFrame 的行。最终目标是能够将此列表导入到 excel 中，因此如果有办法在不使用数据框的情况下执行此操作，我将对此持开放态度。

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1 回答 1

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也许你可以使用DataFrame.from_dict？

In [15]: pd.DataFrame.from_dict(quandlmetadata, orient='index')
Out[15]: 
             column_index    end_date order   column_names  start_date collapse transform limit frequency
BOE/XUDLADD          None  2016-11-03   asc  [Date, Value]  1975-01-02     None      None  None     daily
BOE/XUDLADS          None  2016-11-03   asc  [Date, Value]  1975-01-02     None      None  None     daily
BOE/XUDLB8KL         None  2016-11-03   asc  [Date, Value]  2011-08-01     None      None  None     daily
BOE/XUDLCDD          None  2016-11-03   asc  [Date, Value]  1975-01-02     None      None  None     daily
BOE/XUDLCDS          None  2016-11-03   asc  [Date, Value]  1975-01-02     None      None  None     daily
COM/OIL_WTI          None  2016-11-04   asc  [date, value]  1983-03-30     None      None  None     daily

不过，我认为该column_names专栏不会很有用。您还希望手动调用pd.to_datetime日期列，以便它们是 datetime64 列而不是字符串列。

于 2016-11-06T17:15:50.310 回答