Pandas Dataframe to List of Dictionaries

Pandas DataFrame to List of Dictionaries

Use df.to_dict('records') -- gives the output without having to transpose externally.

In [2]: df.to_dict('records')
Out[2]:
[{'customer': 1L, 'item1': 'apple', 'item2': 'milk', 'item3': 'tomato'},
 {'customer': 2L, 'item1': 'water', 'item2': 'orange', 'item3': 'potato'},
 {'customer': 3L, 'item1': 'juice', 'item2': 'mango', 'item3': 'chips'}]

Convert list of dictionaries to a pandas DataFrame

If ds is a list of dicts:

df = pd.DataFrame(ds)

Note: this does not work with nested data.

how to convert a pandas dataframe to a list of dictionaries in python?

You can groupby and then use to_dict to convert it to a dictionary.

>>> df.groupby(df['id'], as_index=False).agg(list).to_dict(orient="records")
[{'id': 1, 'value': ['a', 'b']}, {'id': 2, 'value': ['c', 'd', 'e']}, {'id': 3, 'value': ['f']}]

Extract value from list of dictionaries in dataframe using pandas

df['ID'] = df['Resources'].apply(lambda x: ','.join([i['resourceName'] for i in eval(x)]))

         Date  ...                                   ID
0  28-02-2022  ...                            i-05fbb7a
1  28-02-2022  ...  i-08bd2475,i-0fd69dc1,i-0174dd38aea

Create a pandas DataFrame from a list of dictionaries with dictionary keys set as row labels

Try this¹

# build a nested dict from list_example and build df
df = pd.DataFrame.from_dict({k: {'time': v} for d in list_example for k,v in d.items()}, orient='index')
print(df)
                                time
companies_info_5000_5100  121.201472
companies_info_5100_5200  116.492211

¹: This method doesn't build a dataframe for each row. Reformatting the dictionary will be much more efficient than the method in the OP. For example, for a dataframe with 10000 rows, this solution takes 24.3 ms while the one in the OP take 4s (this one is 164 times faster).

How to make pandas DataFrame from list of dictionaries

You can do:

dict_list = [{0: 0.05, 0.5: 0.15, 1: 0.1}, {0: 0.06, 0.5: 0.14, 1: 0.2}, {0: 0.09, 0.5: 0.25, 1: 0.17}]
df = pd.DataFrame(dict_list).T
df.columns = (df.columns + 1).map('Dict{}'.format)

print(df):

     Dict1  Dict2  Dict3
0.0   0.05   0.06   0.09
0.5   0.15   0.14   0.25
1.0   0.10   0.20   0.17

If you want index to be a separate column you can do:

df = df.reset_index().rename(columns={'index':'Index'})

Convert pandas.DataFrame to list of dictionaries in Python

pandas.DataFrame.to_json returns a string (JSON string), not a dictionary. Try to_dict instead:

>>> df
   col1  col2
0     1     3
1     2     4
>>> [df.to_dict(orient='index')]
[{0: {'col1': 1, 'col2': 3}, 1: {'col1': 2, 'col2': 4}}]
>>> df.to_dict(orient='records')
[{'col1': 1, 'col2': 3}, {'col1': 2, 'col2': 4}]

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