Convert pandas dataframe into dictionary with keys one column and values the other

Question

Assuming I have a pandas DF as follows:

mydf=pd.DataFrame([{'sectionId':'f0910b98','xml':'<p/p>'},{'sectionId':'f0345b98','xml':'<a/a>'}])
mydf.set_index('sectionId', inplace=True)

I would like to get a dicctionary out of it as follwos:

{'f0910b98':'<p/p>', 'f0345b98':'<a/a>'}

I tried the following:

mydf.to_dict()
mydf.to_dict('records')

And it is not what I am looking for.

I am looking for the correct way to use to_dict()

Note: I know I can get the two columns into two lists and pack them in a dict like in:

mydict = dict(zip(mydf.sectionId, mydf.xml))

but I am looking for a pandas straight direct method (if there is one)

None of the orient options do what you want to accomplish with your data in its current form. The dict(zip( approach is commonly used to meet your requirements. — Eric Truett
– Eric Truett, Commented May 19, 2021 at 15:29

mids · Accepted Answer · 2021-05-19 15:01:48Z

1

You could transpose your dataframe and then to_dict it and select the first item (the xml now-index).

mydf.T.to_dict(orient='records')[0]

returns

{'f0910b98': '<p/p>', 'f0345b98': '<a/a>'}

answered May 19, 2021 at 15:01

mids

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