Convert Python dict into a dataframe

Question

I have a Python dictionary like the following: {u'2012-06-08': 388, u'2012-06-09': 388, u'2012-06-10': 388, u'2012-06-11': 389, u'2012-06-12': 389, u'2012-06-13': 389, u'2012-06-14': 389} The keys are Unicode dates and the values are integers. I would like to convert this into a pandas data frame by having the dates and their corresponding values as two separate columns. Example: col1: Dates col2: DateValue (the dates are still Unicode and date values are still integers) Date Date Value 0 2012-07-01 391 1 2012-07-02 392 2 2012-07-03 392 3 2012-07-04 392 . … ... Any help in this direction would be much appreciated. I am unable to find resources on the pandas docs to help me with this. I know one solution might be to convert each key-value pair in this dict, into a dict so the entire structure becomes a dict of dicts, and then we can add each row individually to the data frame. But I want to know if there is an easier way and a more direct way to do this. So far I have tried converting the dict into a series object but this doesn't seem to maintain the relationship between the columns: s = Series(my_dict,index=my_dict.keys()) Select the correct answer from above options

Answer 1

You can simply use: pandas.DataFrame.from_dict This function takes a dictionary as input to convert into a data frame. For Example: >>> data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']} >>> pd.DataFrame.from_dict(data) col_1 col_2 0 3 a 1 2 b 2 1 c 3 0 d Hope this answer helps.