I have a column in pandas dataframe that has the following structure (see example). I think I have a nested dictionary in a single column, and I want each key to have it’s own column. I want all the matching keys to be the same column. Run the examples for more details I want to explode the dataframe so that
Tag: key-value
Python – Generate permutations by key from key value pair list
Problem: I am generating a search query from key=value pairs. The system being queried does not support searching by the same field twice. I need to generate all unique permutations (assuming that is the correct word) of the pairs so I can generate multiple queries. Example query: python test.py –search field_1=”books” and (field_2=”paper” or (field_2=”abcd” and field_4=”test”)) and field_20=80 and
How to create a dictionnary whose key:value pairs are the values of two different lists of dictionnaries?
I have 2 lists of dictionnaries that result from a pymongo extraction. A list of dicts containing id’s (string) and lemmas (strings): lemmas = [{‘id’: ‘id1’, ‘lemma’: ‘lemma1’}, {‘id’: ‘id2’, ‘lemma’: ‘lemma2’}, {‘id’: ‘id3’, ‘lemma’: ‘lemma3’}, …] A list of dicts containing id’s and multiple words per id: words = [{‘id’: ‘id1’, ‘word’: ‘word1.1’}, {‘id’: ‘id1’, ‘word’: ‘word1.2’}, {‘id’: ‘id2’,
How can I handle only the first part of my value list of a dictionary in Python?
I have a dictionary which has a list of values and I want to use only the first value of each pair before the first comma. Is that possible? If you came across anything similar please write it down Answer The output you expect is unclear. If you want a dictionary in which you only keep the first item of
How do we get an optimum key value pair from a list of dictionaries in a dataframe column based on certain rules?
I have the following dataframe: Different ‘type’ can occur at the same ‘time’, but the need is to only get the ‘type’ and ‘value’ based on the following conditions: priority 1: the type importance is so as t>o>f priority 2: highest value to be considered from value column I have tried using groupby and dictionary with: grp = merged_df.groupby([‘name’,’time’],as_index=False)[[‘type’,’value’]].apply(lambda x:
How do I shuffle the words that are connected to a key in a dictionary?
I have a dictionary I want to shuffle the values in this dictionary to different keys. I tried splitting the dictionary into two like this… And shuffling the values with But I keep getting a type error:’dict_values’ object is not subscriptable I want to recreate the dictionary but with shuffled values. Is this the correct way to get there? Any
How can I update a list of dictionaries with a second list of dictionaries?
So I have been working on this for hours and have scoured many similar questions on Stackoverflow for a response, but no dice. It seems simple enough, but I just can’t seem to get the desired result. I have one list of dictionaries, A, that I would like to merge with another list of dictionaries, B. A and B are
How to access first n characters of a key value in Python
I need to access the first 10 characters of a key-value in dictionary. My dictionary looks like this: I have tried: The desired output is: Answer Why are you using a loop? You can do this directly:- Output:-
is there a faster way to get multiple keys from dictionary?
I have a dictionary: Then I have a list of keys: My desired result is: What I’m doing so far is: Is there a faster way? Perhaps without for? Answer You could use: It has two advantages: It performs the d.get lookup only once – not each iteration Only CPython: Because dict.get is implemented in C and map is implemented