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l = [{'a': 0}, {'b': 1}, {'c': 2}, {'d': 3}, {'e': 4, 'a': 4}]
d = {k: v for x in l for k, v in x.items()}
print(d)
# {'a': 4, 'b': 1, 'c': 2, 'd': 3, 'e': 4}
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>>> keys = ['a', 'b', 'c']
>>> values = [1, 2, 3]
>>> dictionary = dict(zip(keys, values))
>>> print(dictionary)
{'a': 1, 'b': 2, 'c': 3}
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keys = ['a', 'b', 'c']
values = [1, 2, 3]
dictionary = dict(zip(keys, values))
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>>> from collections import ChainMap
>>> a = [{'a':1},{'b':2},{'c':1},{'d':2}]
>>> dict(ChainMap(*a))
{'b': 2, 'c': 1, 'a': 1, 'd': 2}
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column_names = ['id', 'color', 'style']
column_values = [1, 'red', 'bold']
# Convert two lists into a dictionary with zip and the dict constructor
name_to_value_dict = dict(zip(column_names, column_values))
# Convert two lists into a dictionary with a dictionary comprehension
name_to_value_dict = {key:value for key, value in zip(column_names, column_values)}
# Convert two lists into a dictionary with a loop
name_value_tuples = zip(column_names, column_values)
name_to_value_dict = {}
for key, value in name_value_tuples:
if key in name_to_value_dict:
pass # Insert logic for handling duplicate keys
else:
name_to_value_dict[key] = value
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from collections import defaultdict
d1 = {1: 2, 3: 4}
d2 = {1: 6, 3: 7}
dd = defaultdict(list)
for d in (d1, d2): # you can list as many input dicts as you want here
for key, value in d.items():
dd[key].append(value)
print(dd)
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keys = ['Ten', 'Twenty', 'Thirty']
values = [10, 20, 30]
res_dict = dict(zip(keys, values))
print(res_dict)
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keys = ['a', 'b', 'c']
values = [1, 2, 3]
dictionary = dict(zip(keys, values))
print(dictionary) # {'a': 1, 'b': 2, 'c': 3}
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import pandas as pd
l1 = [{'id': 9, 'av': 4}, {'id': 10, 'av': 0}, {'id': 8, 'av': 0}]
l2 = [{'id': 9, 'nv': 45}, {'id': 10, 'nv': 0}, {'id': 8, 'nv': 30}]
df1 = pd.DataFrame(l1).set_index('id')
df2 = pd.DataFrame(l2).set_index('id')
df = df1.merge(df2, left_index=True, right_index=True)
df.T.to_dict()
# {9: {'av': 4, 'nv': 45}, 10: {'av': 0, 'nv': 0}, 8: {'av': 0, 'nv': 30}}