Python dict to pandas df

[waleed3011]

I have a set of data that can come through a stock data API, the amount of data and how stocks is depending on users' requests. The data I receive from the API comes in as a dictionary.

Example:

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{'YAR':              last  date              2020-07-10  336.4  2020-07-13  344.0  2020-07-14  344.3,  'DNB':               last  date               2020-07-10  129.60  2020-07-13  142.45  2020-07-14  145.50,  'NHY':              last  date              2020-07-10  27.35  2020-07-13  28.56  2020-07-14  28.50}

Is it possible to write a for loop in Python where for every key in the dictionary it will create a new pandas data frame row with its value and date as index?

So that the dataframe looks something like this?



I have tried something like this, where I called the dictionary the API provides dataToday:

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tickerlist = ['YAR','DNB','NHY'] df = pd.DataFrame(columns=tickerlist)   for ticker in tickerlist:     df = df.append(pd.DataFrame.from_dict(dataToday[ticker]))

But this gives me a data frame which looks like this:



I know it might be a stupid or a easy question, all help is appreciated. Thanks! :)

[scidam]

The first code block doesn't represent a valid Python dictionary ({'YAR': last
date ...). Could you provide a valid sample of dataToday dictionary; It is hard to answer the question without this knowledge.
Is it looks like the following?:

1	dataToday = {'YAR': {'date': [val1, val2, val3], 'last': [val1, val2, val2]}, 'DNB':...}

[waleed3011]

Is it possible to fix the dict? That is the way the financial data API provides the data... :/

[scidam]

It is likely that the API returns a json string (not a dict). Further, this json string is converted to a dictionary (in Python).The first code block (in your previous post) is not a valid Python dictionary; neither a valid json string?! So, I don't understand how your data is
presented. If dataToday is a dictionary, could you post output of print(dataToday)?