Python – How can I move a nested json dictionary up to its own index? Question: I have a json dataset where each item/index can contain 2 nested dictionaries. The problem is that one of these nested dictionaries contains all of the exact key:value pairs as its parent dictionary. To put it in other words, …
Apply outer tag attribute to inner tag – Flattening xml in python Question: I have a xml file like: <plays format="tokens"> <period number="1"> <play/> <play/> <play/> </period> <period number="2"> <play/> <play/> <play/> </period> Each play tag contains a bunch of variables, but I would also like to add the period number as a variable to …
Expanding Nested lists in Python without fully flattening Question: Suppose I have a list with nested lists such of strings such as: items = [‘Hello’, [‘Ben’, ‘Chris’, ‘Linda’], ‘! The things you can buy today are’, [‘Apples’, ‘Oranges’]] I want a list of strings that combine and flatten the nested lists into all possibilities such …
Merge dictionary of tuple items based only on first term of tuple key Question: I am trying to convert a dictionary of tuples to a list of tuples. However, I need to do so based on the first value of the tuple key. I have worked out most of the steps to accomplish this, but …
How to extract non-empty elements from python for number list Question: I currently have a list that looks like this: [ [0], [2], [4], [6], [7], [9], [20], [24], [], [26], [], [27], [], [], [], [], [], [], [], [], [], [], [], [], [], [] ] How can I transform it to look …
Converting dictionary to dataframe with key as column names and value of key as column values of the dataframe Question: Converting the nested dictionary to dataframe with, dictionary keys as column names and values corresponding to those keys as column values of the dataframe. I’m new to python and have tried several approaches but failed …
Python 3: Flattening nested dictionaries and lists within dictionaries Question: I am dealing with a complex nested dictionary and list data structure. I need to flatten the data and bring all nested items to level 0. See below example for more clarity : {a:1,b:2,c:{c1:[{c11:1,c12:2,c13:3},{c21:1,c22:2,c23:3}],d1:[{d11:1,d12:2,d13:3},{d21:1,d22:2,d23:3}]},x:1,y:2} i need to flatten this to: {a:1,b:2,c_c1_c11:1, c_c1_c12:2,c_c1_c13:3,c_c1_c21:1,c_c1_c22:2,c_c1_c23:3, c_d1,d11:1…and so on} …
How to flatten a pandas dataframe with some columns as json? Question: I have a dataframe df that loads data from a database. Most of the columns are json strings while some are even list of jsons. For example: id name columnA columnB 1 John {“dist”: “600”, “time”: “0:12.10”} [{“pos”: “1st”, “value”: “500”},{“pos”: “2nd”, “value”: …
How do I unnest a tuple with mixed types? Question: I’m trying to flatten a tuple with mixed types into a list. The following function does not produce the desired output: a = (1, 2, 3, [‘first’, ‘second’]) def flatten(l): return flatten(l[0]) + (flatten(l[1:]) if len(l) > 1 else []) if type(l) is list else …
What is the difference between flatten and ravel functions in numpy? Question: import numpy as np y = np.array(((1,2,3),(4,5,6),(7,8,9))) OUTPUT: print(y.flatten()) [1 2 3 4 5 6 7 8 9] print(y.ravel()) [1 2 3 4 5 6 7 8 9] Both function return the same list. Then what is the need of two different functions …
