pythonpandasdataframedictionarycolumn-types

Convert dictionary of dictionaries to dataframe with data types

What is the preferred way to convert dictionary of dictionaries into a data frame with data types?

I have the following kind of dictionary r which contains fact sets behind each key

import pandas as pd

r = { 1:{'a':1,'b':2,'c':'b'},
      2:{'d':1,'b':1,'c':'b'},
      3:{'e':0} }

Converting this dictionary of dictionaries into a dataframe can be done in a quite straightforward way

x = pd.DataFrame(r)
x
x.dtypes

which yields the following version on the original dictionary of dictionaries

     1    2    3
a    1  NaN  NaN
b    2    1  NaN
c    b    e  NaN
d  NaN    1  NaN
e  NaN  NaN  0.0

and the following datatypes for columns

1     object
2     object
3    float64
dtype: object

However, I would like to have transposed version on x. After doing so

y = x.transpose()
y
y.dtypes

it seems like the expected representation on the data is shown in matrix form

     a    b    c    d    e
1    1    2    b  NaN  NaN
2  NaN    1    e    1  NaN
3  NaN  NaN  NaN  NaN    0

but the data types are all object

a    object
b    object
c    object
d    object
e    object
dtype: object

What is the preferred way to do such conversion from r to y so that y.dtypes would yield directly data types

a    float64
b    float64
c    object
d    float64
e    float64
dtype: object

similar to converting r to x?

Solution

  • Just set the right orientation (default is columns, you want index).

    df = pd.DataFrame.from_dict(r, orient='index')

    a    float64
b    float64
c     object
d    float64
e    float64
dtype: object