CODEWITHSUNDEEP
pythonpandas
alechay
alechay

Reputation: 173

How to convert pandas dataframe to hierarchical dictionary

I have the following pandas dataframe:

df1 = pd.DataFrame({'date': [200101,200101,200101,200101,200102,200102,200102,200102],'blockcount': [1,1,2,2,1,1,2,2],'reactiontime': [350,400,200,250,100,300,450,400]})

I am trying to create a hierarchical dictionary, with the values of the embedded dictionary as lists, that looks like this:

{200101: {1:[350, 400], 2:[200, 250]}, 200102: {1:[100, 300], 2:[450, 400]}}

How would I do this? The closest I get is using this code:

df1.set_index('date').groupby(level='date').apply(lambda x: x.set_index('blockcount').squeeze().to_dict()).to_dict()

Which returns:

{200101: {1: 400, 2: 250}, 200102: {1: 300, 2: 400}}

Upvotes: 16

Views: 1626

Answers (3)

BENY
BENY

Reputation: 323266

IIUC

    df1.groupby(['date','blockcount']).reactiontime.agg(list).unstack(0).to_dict()
{200101: {1: [350, 400], 2: [200, 250]}, 200102: {1: [100, 300], 2: [450, 400]}}

Upvotes: 7

anky
anky

Reputation: 75080

Here is another way using pivot_table:

d = df1.pivot_table(index='blockcount',columns='date',
     values='reactiontime',aggfunc=list).to_dict()

print(d)

{200101: {1: [350, 400], 2: [200, 250]},
 200102: {1: [100, 300], 2: [450, 400]}}

Upvotes: 22

thushv89
thushv89

Reputation: 11333

You can do the following,

df2 = df1.groupby(['date', 'blockcount']).agg(lambda x: pd.Series(x).tolist())

# Formatting the result to the correct format
dct = {}
for k, v in df2["reactiontime"].items():
  if k[0] not in dct: 
    dct[k[0]] = {}
  dct[k[0]].update({k[1]: v})

Which produces,

>>> {200101: {1: [350, 400], 2: [200, 250]}, 200102: {1: [100, 300], 2: [450, 400]}}

dct holds the result you need.

Upvotes: 6

Related Questions