Python 元组到数据帧转换的列表
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List of Tuples to DataFrame Conversion
提问by molivizzy
I have a list of tuples similar to the below:
我有一个类似于以下的元组列表：
[(date1, ticker1, value1),(date1, ticker1, value2),(date1, ticker1, value3)]
I want to convert this to a DataFrame with index=date1, columns=ticker1, and values = values. What is the best way to do this?
我想将其转换为一个数据帧index=date1，columns=ticker1和values = values。做这个的最好方式是什么？
EDIT:
编辑：
My end goal is to create a DataFrame with a datetimeindex equal to date1 with values in a column labeled 'ticker':
我的最终目标是创建一个日期时间索引等于 date1 的 DataFrame，其值位于标记为“ticker”的列中：
df = pd.DataFrame(tuples, index=date1)
Right now the tuple is generated with the following:
现在元组是用以下内容生成的：
tuples=list(zip(*prc_path))
where prc_path is a numpy.ndarray with shape (1000,1)
其中 prc_path 是一个形状为 (1000,1) 的 numpy.ndarray
回答by elyase
I think this is what you want:
我认为这就是你想要的：
>>> data = [('2013-01-16', 'AAPL', 1),
('2013-01-16', 'GOOG', 1.5),
('2013-01-17', 'GOOG', 2),
('2013-01-17', 'MSFT', 4),
('2013-01-18', 'GOOG', 3),
('2013-01-18', 'MSFT', 3)]
>>> df = pd.DataFrame(data, columns=['date', 'ticker', 'value'])
>>> df
date ticker value
0 2013-01-16 AAPL 1.0
1 2013-01-16 GOOG 1.5
2 2013-01-17 GOOG 2.0
3 2013-01-17 MSFT 4.0
4 2013-01-18 GOOG 3.0
5 2013-01-18 MSFT 3.0
>>> df.pivot('date', 'ticker', 'value')
ticker AAPL GOOG MSFT
date
2013-01-16 1 1.5 NaN
2013-01-17 NaN 2.0 4
2013-01-18 NaN 3.0 3
