CODEWITHSUNDEEP
pythonpandas
Pedro Lobito
Pedro Lobito

Reputation: 98881

Pandas insert multi-dictionary into a dataframe

I've a dictionary containing multiple dictionaries that I'd like to insert on a dataframe, i.e.:

{{u'USDT_REP': {'quoteVolume60m': 0, 'last': u'28.21000141', 'close60m': 0, 'close5m': u'28.21000141', 'close30m': u'28.71000004', 'close8h': u'30.17823249', 'quoteVolume30m': u'9.98429023', 'close24h': u'34.5', 'quoteVolume': u'8667.24172620', 'quoteVolume5m': u'6.745619', 'quoteVolume24h': u'21.43307455', 'quoteVolume8h': u'2.03708838'}, {u'USDT_XMP': {'quoteVolume60m': 0, 'last': u'27.5453345', 'close60m': 0, 'close5m': u'28.21000141', 'close30m': u'28.71000004', 'close8h': u'30.17823249', 'quoteVolume30m': u'9.98429023', 'close24h': u'34.5', 'quoteVolume': u'8667.24172620', 'quoteVolume5m': u'6.745619', 'quoteVolume24h': u'21.43307455', 'quoteVolume8h': u'2.03708838'}}

I'd like to get something like:

Index    quoteVolume60m     last ...
USDT_REP       0          28.21000141
USDT_XMP       0          27.5453345

I've tried:

df = pd.DataFrame.from_dict(my_dict)

But I get :

                     USDT_REP
close24h          34.10010003
close30m          28.99999805
close5m                 28.21
close60m                    0
close8h           30.17823237

Any idea how to achieve this?

Upvotes: 0

Views: 146

Answers (1)

Carles Mitjans
Carles Mitjans

Reputation: 4866

The solution should be using orient parameter in from_dict function call.

As stated by the documentation:

orient : {‘columns’, ‘index’}, default ‘columns’

The “orientation” of the data. If the keys of the passed dict should be the columns of the resulting DataFrame, pass ‘columns’ (default). Otherwise if the keys should be rows, pass ‘index’.

So, try using:

from_dict(my_dict, orient='index')

Upvotes: 1

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