According to MDN: A Map object can iterate its elements in insertion order – a for..of loop will return an array of [key, value] for each iteration. and Objects are similar to Maps in that both let you set keys to values, retrieve those values, delete keys, and detect whether something is stored at a … Read more
Call dict with no parameters new_dict = dict() or simply write new_dict = {}
By “shallow copying” it means the content of the dictionary is not copied by value, but just creating a new reference. >>> a = {1: [1,2,3]} >>> b = a.copy() >>> a, b ({1: [1, 2, 3]}, {1: [1, 2, 3]}) >>> a[1].append(4) >>> a, b ({1: [1, 2, 3, 4]}, {1: [1, 2, 3, … Read more
You can use .replace. For example: >>> df = pd.DataFrame({‘col2’: {0: ‘a’, 1: 2, 2: np.nan}, ‘col1’: {0: ‘w’, 1: 1, 2: 2}}) >>> di = {1: “A”, 2: “B”} >>> df col1 col2 0 w a 1 1 2 2 2 NaN >>> df.replace({“col1”: di}) col1 col2 0 w a 1 A 2 2 … Read more
Use collections.Counter: >>> from collections import Counter >>> A = Counter({‘a’:1, ‘b’:2, ‘c’:3}) >>> B = Counter({‘b’:3, ‘c’:4, ‘d’:5}) >>> A + B Counter({‘c’: 7, ‘b’: 5, ‘d’: 5, ‘a’: 1}) Counters are basically a subclass of dict, so you can still do everything else with them you’d normally do with that type, such as … Read more
I am assuming you are not using Json.NET (Newtonsoft.Json NuGet package). If this the case, then you should try it. It has the following features: LINQ to JSON The JsonSerializer for quickly converting your .NET objects to JSON and back again Json.NET can optionally produce well formatted, indented JSON for debugging or display Attributes like … Read more
Easily done in 2 steps: dictionary[new_key] = dictionary[old_key] del dictionary[old_key] Or in 1 step: dictionary[new_key] = dictionary.pop(old_key) which will raise KeyError if dictionary[old_key] is undefined. Note that this will delete dictionary[old_key]. >>> dictionary = { 1: ‘one’, 2:’two’, 3:’three’ } >>> dictionary[‘ONE’] = dictionary.pop(1) >>> dictionary {2: ‘two’, 3: ‘three’, ‘ONE’: ‘one’} >>> dictionary[‘ONE’] = … Read more
dict.values returns a view of the dictionary’s values, so you have to wrap it in list: list(d.values())
I suggest a LinkedHashMap or a TreeMap. A LinkedHashMap keeps the keys in the order they were inserted, while a TreeMap is kept sorted via a Comparator or the natural Comparable ordering of the elements. Since it doesn’t have to keep the elements sorted, LinkedHashMap should be faster for most cases; TreeMap has O(log n) … Read more
a.update(b) Latest Python Standard Library Documentation