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Three lists zipped into list of dicts

Consider the following:
>>> # list of length n
>>> idx = ['a', 'b', 'c', 'd']
>>> # list of length n
>>> l_1 = [1, 2, 3, 4]
>>> # list of length n
>>> l_2 = [5, 6, 7, 8]
>>> # first key
>>> key_1 = 'mkt_o'
>>> # second key
>>> key_2 = 'mkt_c'
How do I zip this mess to look like this?
{
'a': {'mkt_o': 1, 'mkt_c': 5},
'b': {'mkt_o': 2, 'mkt_c': 6},
'c': {'mkt_o': 3, 'mkt_c': 6},
'd': {'mkt_o': 4, 'mkt_c': 7},
...
}
The closest I've got is something like this:
>>> dict(zip(idx, zip(l_1, l_2)))
{'a': (1, 5), 'b': (2, 6), 'c': (3, 7), 'd': (4, 8)}
Which of course has tuples as values instead of dictionaries, and
>>> dict(zip(('mkt_o', 'mkt_c'), (1,2)))
{'mkt_o': 1, 'mkt_c': 2}
Which seems like it might be promising, but again, fails to meet requirements.

{k : {key_1 : v1, key_2 : v2} for k,v1,v2 in zip(idx, l_1, l_2)}

Solution 1: You may use zip twice (actually thrice) with dictionary comprehension to achieve this as:
idx = ['a', 'b', 'c', 'd']
l_1 = [1, 2, 3, 4]
l_2 = [5, 6, 7, 8]
keys = ['mkt_o', 'mkt_c'] # yours keys in another list
new_dict = {k: dict(zip(keys, v)) for k, v in zip(idx, zip(l_1, l_2))}
Solution 2: You may also use zip with nested list comprehension as:
new_dict = dict(zip(idx, [{key_1: i, key_2: j} for i, j in zip(l_1, l_2)]))
Solution 3: using dictionary comprehension on top of zip as shared in DYZ's answer:
new_dict = {k : {key_1 : v1, key_2 : v2} for k,v1,v2 in zip(idx, l_1, l_2)}
All the above solutions will return new_dict as:
{
'a': {'mkt_o': 1, 'mkt_c': 5},
'b': {'mkt_o': 2, 'mkt_c': 6},
'c': {'mkt_o': 3, 'mkt_c': 7},
'd': {'mkt_o': 4, 'mkt_c': 8}
}

You're working with dicts, lists, indices, keys and would like to transpose the data. It might make sense to work with pandas (DataFrame, .T and .to_dict):
>>> import pandas as pd
>>> idx = ['a', 'b', 'c', 'd']
>>> l_1 = [1, 2, 3, 4]
>>> l_2 = [5, 6, 7, 8]
>>> key_1 = 'mkt_o'
>>> key_2 = 'mkt_c'
>>> pd.DataFrame([l_1, l_2], index=[key_1, key_2], columns = idx)
a b c d
mkt_o 1 2 3 4
mkt_c 5 6 7 8
>>> pd.DataFrame([l_1, l_2], index=[key_1, key_2], columns = idx).T
mkt_o mkt_c
a 1 5
b 2 6
c 3 7
d 4 8
>>> pd.DataFrame([l_1, l_2], index=[key_1, key_2], columns = idx).to_dict()
{'a': {'mkt_o': 1, 'mkt_c': 5},
'b': {'mkt_o': 2, 'mkt_c': 6},
'c': {'mkt_o': 3, 'mkt_c': 7},
'd': {'mkt_o': 4, 'mkt_c': 8}
}

It can also be done with dict, zip, map and repeat from itertools:
>>> from itertools import repeat
>>> dict(zip(idx, map(dict, zip(zip(repeat(key_1), l_1), zip(repeat(key_2), l_2)))))
{'a': {'mkt_c': 5, 'mkt_o': 1}, 'c': {'mkt_c': 7, 'mkt_o': 3}, 'b': {'mkt_c': 6, 'mkt_o': 2}, 'd': {'mkt_c': 8, 'mkt_o': 4}}

How to sum all the values that belong to the same key?

I'm pulling data from the database and assuming i have something like this:
Product Name Quantity
a 3
a 5
b 2
c 7
I want to sum the Quantity based on Product name, so this is what i want:
product = {'a':8, 'b':2, 'c':7 }
Here's what I'm trying to do after fetching the data from the database:
for row in result:
product[row['product_name']] += row['quantity']
but this will give me: 'a'=5 only, not 8.

Option 1: pandas
This is one way, assuming you begin with a pandas dataframe df. This solution has O(n log n) complexity.
product = df.groupby('Product Name')['Quantity'].sum().to_dict()
# {'a': 8, 'b': 2, 'c': 7}
The idea is you can perform a groupby operation, which produces a series indexed by "Product Name". Then use the to_dict() method to convert to a dictionary.
Option 2: collections.Counter
If you begin with a list or iterator of results, and wish to use a for loop, you can use collections.Counter for O(n) complexity.
from collections import Counter
result = [['a', 3],
['a', 5],
['b', 2],
['c', 7]]
product = Counter()
for row in result:
product[row[0]] += row[1]
print(product)
# Counter({'a': 8, 'c': 7, 'b': 2})
Option 3: itertools.groupby
You can also use a dictionary comprehension with itertools.groupby. This requires sorting beforehand.
from itertools import groupby
res = {i: sum(list(zip(*j))[1]) for i, j in groupby(sorted(result), key=lambda x: x[0])}
# {'a': 8, 'b': 2, 'c': 7}

If you insist on using loops, you can do this:
# fake data to make the script runnable
result = [
{'product_name': 'a', 'quantity': 3},
{'product_name': 'a', 'quantity': 5},
{'product_name': 'b', 'quantity': 2},
{'product_name': 'c', 'quantity': 7}
]
# solution with defaultdict and loops
from collections import defaultdict
d = defaultdict(int)
for row in result:
d[row['product_name']] += row['quantity']
print(dict(d))
The output:
{'a': 8, 'b': 2, 'c': 7}

Since you mention pandas
df.set_index('ProductName').Quantity.sum(level=0).to_dict()
Out[20]: {'a': 8, 'b': 2, 'c': 7}

Use tuple to store the result.
Edit:
Not clear if the data mentioned is really a dataframe.
If yes then li = [tuple(x) for x in df.to_records(index=False)]
li = [('a', 3), ('a', 5), ('b', 2), ('c', 7)]
d = dict()
for key, val in li:
val_old = 0
if key in d:
val_old = d[key]
d[key] = val + val_old
print(d)
Output
{'a': 8, 'b': 2, 'c': 7}

How can i add the terms of one dict to another?

Let's assume i start with this dictionary:
mydict = {
'a': [[2,4], [5,6]],
'b': [[1,1], [1,7,9], [6,2,3]],
'c': [['a'], [4,5]],
}
How can i append values to 'a' yet be able to add a new key if i needed to let's say 'd' what i tried is
plus_min_dict = {}
plus_min_dict[key] = reference_dataset[key][line_number]
but it only gave one value per key apparently = destroyed the previous value, i want to update or append yet still be able to create a new key if it doesn't exist
Edit: To clarify let's assume this is my initial dictionary:
mydict = {
'a': [[2,4]],}
i do other calculations with another dictionary let's assume it's :
second_dict = {
'a': [ [5,6]],
'b': [[1,1], [1,7,9]],
'c': [['a'], [4,5]],
}
these calculations showed me that i have interest in [5,6] of 'a' and [1,7,9] of 'b' so i want mydict to become:
mydict = {
'a': [[2,4], [5,6]],
'b': [[1,7,9]],
}

If I understand well your question, you want to append a new value to your dictionary if the key already exists. If so, I would use a defaultdict for a simple reason. With a defaultdict you can use the method += to create (if does not exist) or add (if exist) an element :
from collections import defaultdict
# Your dictionaries
mydict = {
'a': [[2,4], [5,6]],
'b': [[1,1], [1,7,9], [6,2,3]],
'c': [['a'], [4,5]],
}
plus_min_dict = {'a': [[3,3]]}
# d is a DefaultDict containing mydict values
d=defaultdict(list,mydict)
# d_new is a DefaultDict containing plus_min_dict dict
d_new = defaultdict(list, plus_min_dict)
# Add all key,values of d in d_new
for k, v in d.items():
d_new[k] += d[k]
print(d_new)
Results :
defaultdict(<class 'list'>, {'c': [['a'], [4, 5]], 'a': [[3, 3], [2, 4], [5, 6]], 'b': [[1, 1], [1, 7, 9], [6, 2, 3]]})

Use an if else loop
mydict = {'a': [[2,4]],}
second_dict = {
'a': [ [5,6]],
'b': [[1,1], [1,7,9]],
'c': [['a'], [4,5]]}
missing_values = {
'a': [5,6],
'b': [1,7,9]}
for key, value in missing_values.items():
if key in mydict:
mydict[key ].append(value)
else:
mydict[key ] = [value]
print(mydict)
Result:
{'a': [[2, 4], [5, 6]], 'b': [[1, 7, 9]]}

To append an item into 'a', you can do this:
mydict['a'] += ['test_item']
Or:
mydict['a'].append('test_item')

You can just append:
mydict = {
'a': [[2,4], [5,6]],
'b': [[1,1], [1,7,9], [6,2,3]],
'c': [['a'], [4,5]],
}
mydict['a'].append([7,8])
mydict['d'] = [0,1]
print(mydict)

python sorting dictionary by length of values

I have found many threads for sorting by values like here but it doesn't seem to be working for me...
I have a dictionary of lists that have tuples. Each list has a different amount of tuples. I want to sort the dictionary by how many tuples each list contain.
>>>to_format
>>>{"one":[(1,3),(1,4)],"two":[(1,2),(1,2),(1,3)],"three":[(1,1)]}
>>>for key in some_sort(to_format):
print key,
>>>two one three
Is this possible?

>>> d = {"one": [(1,3),(1,4)], "two": [(1,2),(1,2),(1,3)], "three": [(1,1)]}
>>> for k in sorted(d, key=lambda k: len(d[k]), reverse=True):
print k,
two one three
Here is a universal solution that works on Python 2 & Python 3:
>>> print(' '.join(sorted(d, key=lambda k: len(d[k]), reverse=True)))
two one three

dict= {'a': [9,2,3,4,5], 'b': [1,2,3,4, 5, 6], 'c': [], 'd': [1,2,3,4], 'e': [1,2]}
dict_temp = {'a': 'hello', 'b': 'bye', 'c': '', 'd': 'aa', 'e': 'zz'}
def sort_by_values_len(dict):
dict_len= {key: len(value) for key, value in dict.items()}
import operator
sorted_key_list = sorted(dict_len.items(), key=operator.itemgetter(1), reverse=True)
sorted_dict = [{item[0]: dict[item [0]]} for item in sorted_key_list]
return sorted_dict
print (sort_by_values_len(dict))
output:
[{'b': [1, 2, 3, 4, 5, 6]}, {'a': [9, 2, 3, 4, 5]}, {'d': [1, 2, 3, 4]}, {'e': [1, 2]}, {'c': []}]

Dynamic Dictionary of dictionaries Python

I wanted to create a dictionary of dictionaries in Python:
Suppose I already have a list which contains the keys:
keys = ['a', 'b', 'c', 'd', 'e']
value = [1, 2, 3, 4, 5]
Suppose I have a data field with numeric values (20 of them)
I want to define a dictionary which stores 4 different dictionaries with the given to a corresponding value
for i in range(0, 3)
for j in range(0, 4)
dictionary[i] = { 'keys[j]' : value[j] }
So basically, it should be like:
dictionary[0] = {'a' : 1, 'b' : 2, 'c' : 3, 'd': 4, 'e':5}
dictionary[1] = {'a' : 1, 'b' : 2, 'c' : 3, 'd': 4, 'e':5}
dictionary[2] = {'a' : 1, 'b' : 2, 'c' : 3, 'd': 4, 'e':5}
dictionary[3] = {'a' : 1, 'b' : 2, 'c' : 3, 'd': 4, 'e':5}
What is the best way to achieve this?

Use a list comprehension and dict(zip(keys,value)) will return the dict for you.
>>> keys = ['a', 'b', 'c', 'd', 'e']
>>> value = [1, 2, 3, 4, 5]
>>> dictionary = [dict(zip(keys,value)) for _ in xrange(4)]
>>> from pprint import pprint
>>> pprint(dictionary)
[{'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5},
{'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5},
{'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5},
{'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}]
If you want a dict of dicts then use a dict comprehension:
>>> keys = ['a', 'b', 'c', 'd', 'e']
>>> value = [1, 2, 3, 4, 5]
>>> dictionary = {i: dict(zip(keys,value)) for i in xrange(4)}
>>> pprint(dictionary)
{0: {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5},
1: {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5},
2: {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5},
3: {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}}

An alternative that only zips once...:
from itertools import repeat
map(dict, repeat(zip(keys,values), 4))
Or, maybe, just use dict.copyand construct the dict once:
[d.copy() for d in repeat(dict(zip(keys, values)), 4)]

for a list of dictionaries:
dictionary = [dict(zip(keys,value)) for i in xrange(4)]
If you really wanted a dictionary of dictionaries like you said:
dictionary = dict((i,dict(zip(keys,value))) for i in xrange(4))
I suppose you could use pop or other dict calls which you could not from a list
BTW: if this is really a data/number crunching application, I'd suggest moving on to numpy and/or pandas as great modules.
Edit re: OP comments,
if you want indicies for the type of data you are talking about:
# dict keys must be tuples and not lists
[(i,j) for i in xrange(4) for j in range(3)]
# same can come from itertools.product
from itertools import product
list(product(xrange4, xrange 3))