How can I set index while converting dictionary to dataframe?

Question

I have a dictionary that looks like the below

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.

I can do this job by the below commands

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.

Is there any way to set index while converting dictionary to dataframe, without having overlapping columns like the below?

     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! :)

Answer 1

Use 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:

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 dict by Date key and then set index by dictionary['Date']:

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