Python3.4：字典中的DataFrame [英] Python3.4 : DataFrame from Dictionary
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问题描述
以下代码旨在填充熊猫DataFrame。
The following code is meant to populate a pandas DataFrame. Unfortunately the output is coming out weird.
output = {'Revenue' : [1456216, 549514, 489461], 'Cost of Revenue' : [1565486, 498464, 156131], 'Gross Profit' : [456465, 565165, 651613] ... ... ... }
years = ['year1', 'year2', 'year3']
df = pd.DataFrame(output.values(), index=output.keys(), columns=years)
print(df)
字典 output 具有列表值。我想使用output.keys（）作为DataFrame索引，使用列的列出年份，并使用output.values（）作为数据框架内的数据。最终，我希望输出如下
The dictionary output has list values. I want to use output.keys() as the DataFrame index, the list years for the columns and output.values() as the data within the data frame. Ultimately I want the ouput to be as follows
Year 1 Year 2 Year 3
Revenue 1456216 549514 489461
Cost of Revenue 1565486 498464 156131
Gross Profit 456465 565165 651613
... ... ... ...
... ... ... ...
我该怎么做？
year1 \
Total Revenue ([2218767, 1528545, 972309], [293797, 202908, ...
Cost of Revenue ([2218767, 1528545, 972309], [293797, 202908, ...
Gross Profit ([2218767, 1528545, 972309], [293797, 202908, ...
Research Development ([2218767, 1528545, 972309], [293797, 202908, ...
Selling General and Administrative ([2218767, 1528545, 972309], [293797, 202908, ...
Non Recurring ([2218767, 1528545, 972309], [293797, 202908, ...
Others ([2218767, 1528545, 972309], [293797, 202908, ...
Total Operating Expenses ([2218767, 1528545, 972309], [293797, 202908, ...
Operating Income or Loss ([2218767, 1528545, 972309], [293797, 202908, ...
Total Other Income/Expenses Net ([2218767, 1528545, 972309], [293797, 202908, ...
Earnings Before Interest And Taxes ([2218767, 1528545, 972309], [293797, 202908, ...
Interest Expense ([2218767, 1528545, 972309], [293797, 202908, ...
Income Before Tax ([2218767, 1528545, 972309], [293797, 202908, ...
Income Tax Expense ([2218767, 1528545, 972309], [293797, 202908, ...
Minority Interest ([2218767, 1528545, 972309], [293797, 202908, ...
Net Income From Continuing Ops ([2218767, 1528545, 972309], [293797, 202908, ...
Discontinued Operations ([2218767, 1528545, 972309], [293797, 202908, ...
Extraordinary Items ([2218767, 1528545, 972309], [293797, 202908, ...
Effect Of Accounting Changes ([2218767, 1528545, 972309], [293797, 202908, ...
Other Items ([2218767, 1528545, 972309], [293797, 202908, ...
Net Income ([2218767, 1528545, 972309], [293797, 202908, ...
Preferred Stock And Other Adjustments ([2218767, 1528545, 972309], [293797, 202908, ...
Net Income Applicable To Common Shares ([2218767, 1528545, 972309], [293797, 202908, ...
year2 \
Total Revenue ([2218767, 1528545, 972309], [293797, 202908, ...
Cost of Revenue ([2218767, 1528545, 972309], [293797, 202908, ...
Gross Profit ([2218767, 1528545, 972309], [293797, 202908, ...
Research Development ([2218767, 1528545, 972309], [293797, 202908, ...
Selling General and Administrative ([2218767, 1528545, 972309], [293797, 202908, ...
Non Recurring ([2218767, 1528545, 972309], [293797, 202908, ...
Others ([2218767, 1528545, 972309], [293797, 202908, ...
Total Operating Expenses ([2218767, 1528545, 972309], [293797, 202908, ...
Operating Income or Loss ([2218767, 1528545, 972309], [293797, 202908, ...
Total Other Income/Expenses Net ([2218767, 1528545, 972309], [293797, 202908, ...
Earnings Before Interest And Taxes ([2218767, 1528545, 972309], [293797, 202908, ...
Interest Expense ([2218767, 1528545, 972309], [293797, 202908, ...
Income Before Tax ([2218767, 1528545, 972309], [293797, 202908, ...
Income Tax Expense ([2218767, 1528545, 972309], [293797, 202908, ...
Minority Interest ([2218767, 1528545, 972309], [293797, 202908, ...
Net Income From Continuing Ops ([2218767, 1528545, 972309], [293797, 202908, ...
Discontinued Operations ([2218767, 1528545, 972309], [293797, 202908, ...
Extraordinary Items ([2218767, 1528545, 972309], [293797, 202908, ...
Effect Of Accounting Changes ([2218767, 1528545, 972309], [293797, 202908, ...
Other Items ([2218767, 1528545, 972309], [293797, 202908, ...
Net Income ([2218767, 1528545, 972309], [293797, 202908, ...
Preferred Stock And Other Adjustments ([2218767, 1528545, 972309], [293797, 202908, ...
Net Income Applicable To Common Shares ([2218767, 1528545, 972309], [293797, 202908, ...
year3
You get the idea
OrderedDict([('Total Revenue', [2218767, 1528545, 972309]), ('Cost of Revenue', [293797, 202908, 125521]), ('Gross Profit', [1924970, 1325637, 846788]), ('Research Development', [536184, 395643, 257179]), ('Selling General and Administrative', [1115705, 747666, 452898]), ('Non Recurring', ['0', '0', '0']), ('Others', [236946, 134516, 79849]), ('Total Operating Expenses', ['0', '0', '0']), ('Operating Income or Loss', [36135, 47812, 56862]), ('Total Other Income/Expenses Net', [-4930, 1416, 252]), ('Earnings Before Interest And Taxes', [31205, 49228, 57114]), ('Interest Expense', ['0', '0', '0']), ('Income Before Tax', [31205, 49228, 57114]), ('Income Tax Expense', [46525, 22459, 35504]), ('Minority Interest', [-427, '0', '0']), ('Net Income From Continuing Ops', [-15747, 26769, 21610]), ('Discontinued Operations', ['0', '0', '0']), ('Extraordinary Items', ['0', '0', '0']), ('Effect Of Accounting Changes', ['0', '0', '0']), ('Other Items', ['0', '0', '0']), ('Net Income', [-15747, 26769, 21610]), ('Preferred Stock And Other Adjustments', ['0', '0', '0']), ('Net Income Applicable To Common Shares', [-15747, 26769, 21610])])
推荐答案
您可以传递 list（output.values（））而不是传递 output.values（）：
Instead of passing output.values(), you could pass list(output.values()):
>>> pd.DataFrame(list(output.values()), index=output.keys(), columns=years)
year1 year2 year3
Cost of Revenue 1565486 498464 156131
Gross Profit 456465 565165 651613
Revenue 1456216 549514 489461
您也可以写
>>> df = pd.DataFrame.from_dict(output, orient='index')
>>> df.columns = years
>>> df
year1 year2 year3
Cost of Revenue 1565486 498464 156131
Gross Profit 456465 565165 651613
Revenue 1456216 549514 489461
要求DataFrame构造函数执行很多操作，有时我认为将其分解更简单。
The DataFrame constructor is asked to do a lot of things, and sometimes I think it's simpler to break it up.
关于为什么发生这种情况，构造函数中有很多特殊的类型，并且该分支如下：
As for why this is happening, there's a lot of special-casing on type in the constructor, and this branch:
elif isinstance(data, (list, types.GeneratorType)):
不会选择 dict_values 对象，因为它既不是列表也不是生成器。
isn't picking up the dict_values object because it's neither a list nor a generator.
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