python - Pandas dataframe to JSON format manipulation -


i have pandas dataframe one

user  category    rating 1     [1,2,3]     [5,1,3] 2     [3,2,1]     [3,1,1] 3     [1,3,1]     [2,1,4]

i want write endpoint takes user , returns list of categories , ratings particular user.

www.endpoint.com/user/1

should return

[{category: 1, rating: 5}, {category: 2, rating: 1}, {category: 3, rating: 3}]

is there simple way in pandas?

i use the following generic function explodes lists in columns rows:

def explode(df, lst_cols, fill_value=''):     # make sure `lst_cols` list     if lst_cols , not isinstance(lst_cols, list):         lst_cols = [lst_cols]     # columns except `lst_cols`     idx_cols = df.columns.difference(lst_cols)      # calculate lengths of lists     lens = df[lst_cols[0]].str.len()      if (lens > 0).all():         # lists in cells aren't empty         return pd.dataframe({             col:np.repeat(df[col].values, df[lst_cols[0]].str.len())             col in idx_cols         }).assign(**{col:np.concatenate(df[col].values) col in lst_cols}) \           .loc[:, df.columns]     else:         # @ least 1 list in cells empty         return pd.dataframe({             col:np.repeat(df[col].values, df[lst_cols[0]].str.len())             col in idx_cols         }).assign(**{col:np.concatenate(df[col].values) col in lst_cols}) \           .append(df.loc[lens==0, idx_cols]).fillna(fill_value) \           .loc[:, df.columns]

demo:

in [88]: df out[88]:    user   category     rating 0     1  [1, 2, 3]  [5, 1, 3] 1     2  [3, 2, 1]  [3, 1, 1] 2     3  [1, 3, 1]  [2, 1, 4]  in [89]: cols = ['category','rating']  in [90]: x = explode(df, cols)  in [91]: x out[91]:    user category rating 0     1        1      5 1     1        2      1 2     1        3      3 3     2        3      3 4     2        2      1 5     2        1      1 6     3        1      2 7     3        3      1 8     3        1      4

now can need:

in [92]: x.loc[x.user == 1, cols].to_dict('r') out[92]: [{'category': '1', 'rating': '5'},  {'category': '2', 'rating': '1'},  {'category': '3', 'rating': '3'}]

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