Pandas dataframe from nested dictionary

Question

My dictionary looks like this:

{\'x\': {\'b\': 10, \'c\': 20}, \'y\': {\'b\': \'33\', \'c\': 44}}

I want to get a dataframe that looks like

Answer 1

You can use a list comprehension to reorder your dict into a list of tuples where each tuple is a row and then you can sort your dataframe

import pandas as pd

d = {'x': {'b': 10, 'c': 20}, 'y': {'b': '33', 'c': 44}}

df = pd.DataFrame([(k,k1,v1) for k,v in d.items() for k1,v1 in v.items()], columns = ['Col1','Col2','Val'])
print df.sort(['Col1','Col2','Val'], ascending=[1,1,1])

  Col1 Col2 Val
3    x    b  10
2    x    c  20
1    y    b  33
0    y    c  44

Answer 2

first create the df using from_dict, then call stack and reset_index to get the shape you desire, you then need to rename the cols, sort and reset the index:

In [83]:
d={'x': {'b': 10, 'c': 20}, 'y': {'b': '33', 'c': 44}}
df = pd.DataFrame.from_dict(d, orient='index').stack().reset_index()
df.columns = ['col1', 'col2', 'val']
df.sort_values(['col1', 'col2'], inplace=True)
df.reset_index(drop=True, inplace=True)
df

Out[83]:
  col1 col2 val
0    x    b  10
1    x    c  20
2    y    b  33
3    y    c  44