There are around 60.000 dictionaries stored in a list. There is also a dataframe with the same amount of rows of which I want to take one column and insert into the dictionaries as a key value pair. I have created a for loop which is supposed to update dictionary values, which however seems to take forever. I am looking
Tag: dictionary
Convert nested dict to dataframe, syntax error?
Problem I am converting multiple nested dicts to dataframes. I have a slightly different dict that I haven’t been able to convert to a dataframe using my attempted solution. I am providing a shortened copy of my dict with dummy values as the reprex. Reprex dict: My attempted solution Code is based on similar dict wrangling problems that I had,
Compare two lists and write for each item corresponding X column value
Let’s say I have a list of users then I have a table What I want is: to have a list of Date for each Resource A, B, C So desired output could be a dictionary: Answer You can use explode then use groupby and agg(list) at the end get the result as dict with to_dict. Output:
I want to convert file data into 3d dictionary using python
Like I want this type of dictionary by reading file: or this will be enough. I have a file lets name file.txt which has data like I am trying but i dint get the result this following is my try: it gives me output {‘A’: ‘7’, ‘B’: ‘8’, ‘C’: ‘9’} I know its obvious it will not give me 3d
count number of missing items required comparing dictionaries in python
Given a list: a dictionary with ingredients I currently have: and a more complex dictionary with the recipes and items per ingredients: I want to output a dictionary that adds to the elements of the list list_essentials the number of items I need if I wanted to be able to make all the recipes. The expected output I am looking
Nested dictionary incorrectly populating all top level key-value pairs with same values
I am having a strange issue where indexing a nested dictionary correctly results in the same value being assigned for all top level keys (k’s). Below is the whole chunk of code. Below is the output of this block: You can see by the print statements that after the first iteration of the middle loop, all top level keys have
Looping through Python Dict and Normalising
I have multiple dict in a list and I want loop through each dict and flatten the file. When I run this code its giving me the ‘NoneType’ object is not subscriptable error. And the custom fields in the below json will be having many other fields as well Project_details list will be consisting of info like this And My
How can I replace a string value with its corresponding Boolean value in a nested dictionary in Python?
I was recently given a project to do for my Python college course. Basically, you save a dictionary in a csv file with csv.DictWriter, and then you load it back into another dictionary with csv.DictReader. However, for some reason, one of the automated unittests fails my function because the final dictionary contains values “True” or “False” instead of Bool values
Python Trying to assign 100 values to 100keys with some conditions
I’m new at python so please go easy on me. The users is a dict [str,list[str].The keys are just user1, user2 etc until 100. The list of strings contains 10 songs each. The premade_playlist also has keys premade1, premade2 etc until 100.The values are also a dict [str,list[str] and contains about 50 songs in the list[str]. I am trying to
How would I pull out similar value pairs from a dictionary and put them in a new dictionary?
I have a dictionary filled with 3 keys: “Ticker”, “Title” and “Value”. The ticker key contains 100 stock tickers that corresponds to the value of the purchase and title that are in the same position. So here is an example of the dictionary: So “AKUS” corresponds with the 10% and +$374,908,350. I am only showing 4 items in the dictionary