pandas 将字典转换为数据框时如何设置索引？
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How can I set index while converting dictionary to dataframe?
提问by maynull
I have a dictionary that looks like the below
我有一本看起来像下面的字典
defaultdict(list,
{'Open': ['47.47', '47.46', '47.38', ...],
'Close': ['47.48', '47.45', '47.40', ...],
'Date': ['2016/11/22 07:00:00', '2016/11/22 06:59:00','2016/11/22 06:58:00', ...]})
My purpose is to convert this dictionary to a dataframe and to set the 'Date' key values as the index of the dataframe.
我的目的是将此字典转换为数据框并将“日期”键值设置为数据框的索引。
I can do this job by the below commands
我可以通过以下命令完成这项工作
df = pd.DataFrame(dictionary, columns=['Date', 'Open', 'Close'])
0 Date Open Close
1 2016/11/22 07:00:00 47.47 47.48
2 2016/11/22 06:59:00 47.46 47.45
3 2016/11/22 06:58:00 47.38 47.38
df.index = df.Date
Date Date Open Close
2016/11/22 07:00:00 2016/11/22 07:00:00 47.47 47.48
2016/11/22 06:59:00 2016/11/22 06:59:00 47.46 47.45
2016/11/22 06:58:00 2016/11/22 06:58:00 47.38 47.38
but, then I have two 'Date' columns, one of which is the index and the other of which is the original column.
但是，然后我有两个“日期”列，其中一个是索引，另一个是原始列。
Is there any way to set index whileconverting dictionary to dataframe, without having overlapping columns like the below?
有没有办法在将字典转换为数据帧时设置索引，而不会像下面这样重叠列？
Date Close Open
2016/11/22 07:00:00 47.48 47.47
2016/11/22 06:59:00 47.45 47.46
2016/11/22 06:58:00 47.38 47.38
Thank you for reading this! :)
谢谢您阅读此篇！:)
回答by jezrael
Use set_index:
使用set_index：
df = pd.DataFrame(dictionary, columns=['Date', 'Open', 'Close'])
df = df.set_index('Date')
print (df)
Open Close
Date
2016/11/22 07:00:00 47.47 47.48
2016/11/22 06:59:00 47.46 47.45
2016/11/22 06:58:00 47.38 47.40
Or use inplace:
或使用inplace：
df = pd.DataFrame(dictionary, columns=['Date', 'Open', 'Close'])
df.set_index('Date', inplace=True)
print (df)
Open Close
Date
2016/11/22 07:00:00 47.47 47.48
2016/11/22 06:59:00 47.46 47.45
2016/11/22 06:58:00 47.38 47.40
Another possible solution filter out dictby Datekey and then set index by dictionary['Date']:
另一种可能的解决方案dict是Date按键过滤，然后按dictionary['Date']以下方式设置索引：
df = pd.DataFrame({k: v for k, v in dictionary.items() if not k == 'Date'},
index=dictionary['Date'],
columns=['Open','Close'])
df.index.name = 'Date'
print (df)
Open Close
Date
2016/11/22 07:00:00 47.47 47.48
2016/11/22 06:59:00 47.46 47.45
2016/11/22 06:58:00 47.38 47.40
