How to convert OrderedDict with tuples to a Pandas Dataframe-CodePudding

I have the following OrderedDict:

OrderedDict(
[
 ("2021-01-01" , {"name" : "John",    "age" : 25}),
 ("2021-05-05" , {"name" : "Max",     "age" : 15}),
 ("2021-09-09" , {"name" : "Michael", "age" : 35})
]
)

I need to convert it to a Pandas Dataframe where each key in each dict will be the column name, and dates will be the index of the DataFrame. How can I achieve this?

The expected result should like as the following:

where the date column is the index of this DataFrame.

CodePudding user response：

We can get the expected result by using the transpose method from Pandas :

>>> df = pd.DataFrame(data, columns=data.keys()).T
>>> df
            name    age
2021-01-01  John    25
2021-05-05  Max     15
2021-09-09  Michael 35

CodePudding user response：

Try with from_dict

out = pd.DataFrame.from_dict(d, 'index')
Out[484]: 
               name  age
2021-01-01     John   25
2021-05-05      Max   15
2021-09-09  Michael   35

CodePudding user response：

I might have been beaten to the post here but here's the solution:

from collections import OrderedDict
x1 = OrderedDict(
[
 ("2021-01-01" , {"name" : "John",    "age" : 25}),
 ("2021-05-05" , {"name" : "Max",     "age" : 15}),
 ("2021-09-09" , {"name" : "Michael", "age" : 35})
]
)

pd.DataFrame.from_dict(x1).T.rename_axis('date').reset_index()