Given the following data:
d = {"a": {1.0: "this", 2.0: "that"}, "b": {1.0: "here", 2.0: "there"}}
How would one create dataframe:
var code name
0 a 1.0 this
1 a 2.0 that
2 b 1.0 here
3 b 2.0 there
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2 Answers
I suggest use nested list comprehension for list of tuples and pass to DataFrame constructor:
L = [(k, k1, v1) for k, v in d.items() for k1, v1 in v.items()]
df = pd.DataFrame(L, columns=['var', 'code', 'name'])
print (df)
var code name
0 a 1.0 this
1 a 2.0 that
2 b 1.0 here
3 b 2.0 there
Alternative solution with DataFrame constructor, DataFrame.rename_axis, reshape by DataFrame.unstack and Series.reset_index:
df = (pd.DataFrame(d)
.rename_axis(index='code', columns='var')
.unstack()
.reset_index(name='name'))
print (df)
var code name
0 a 1.0 this
1 a 2.0 that
2 b 1.0 here
3 b 2.0 there
1 Comment
yatu
Yess... A little trickier to generate a more representative input being a dict
We can construct a dataframe from the dictionary, stack and reset_index:
df = pd.DataFrame(d).stack()
df.index = df.index.set_names(['var', 'code'])
df.reset_index(name='name')
print(df)
var code name
0 1.0 a this
1 1.0 b here
2 2.0 a that
3 2.0 b there
