CODEWITHSUNDEEP
pythonpython-3.xpandasdataframedictionary
Rahul Sharma
Rahul Sharma

Reputation: 2495

Convert dataframe into dictionary

I have a dataframe and i want it to select a few columns and convert it into Dictionary in the a certain manner

Dataframe:

Dataframe :

and here's the output I want

{20: [4.6, 4.3, 4.3, 20],
21: [4.6, 4.3, 4.3, 21],
 22: [6.0, 5.6, 9.0, 22],
 23: [8.75, 5.6, 6.6, 23]}

I have tried this

items_dic = data[["Length","Width","Height","Pid" ]].set_index('Pid').T.to_dict('list')

items_dic = {20: [4.6, 4.3, 4.3],
 21: [4.6, 4.3, 4.3],
 22: [6.0, 5.6, 9.0],
 23: [8.75, 5.6, 6.6]}

but this does not include Pid in the list of values Can someone explain why ?

Upvotes: 12

Views: 1246

Answers (2)

U13-Forward
U13-Forward

Reputation: 71560

Or use dict(zip(...)):

>>> cols = ["Length","Width","Height","Pid"]
>>> items_dic = dict(zip(df['Pid'],df[cols].values.tolist()))
>>> items_dic
{20: [4.8, 4.3, 4.3, 20.0], 21: [4.8, 4.3, 4.3, 21.0], 22: [6.0, 5.6, 9.0, 22.0], 23: [8.75, 5.6, 6.6, 23.0], 24: [6.0, 5.16, 6.6, 24.0]}
>>>

Upvotes: 7

jezrael
jezrael

Reputation: 862481

Set parameter drop=False in DataFrame.set_index, because default parameter drop=False move column to index:

cols = ["Length","Width","Height","Pid"]
items_dic = data[cols].set_index('Pid', drop=False).T.to_dict('list')

print (items_dic)

{20: [4.6, 4.3, 4.3, 20.0], 
 21: [4.6, 4.3, 4.3, 21.0], 
 22: [6.0, 5.6, 9.0, 22.0], 
 23: [8.75, 5.6, 6.6, 23.0]}

Upvotes: 13

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