I've tried using both Python and Postgres to convert a table of data into JSON that can be used to render a nested dropdown in a web UI. Here is how the data is structured: group_desc category_desc subcategory_desc item_desc Group…
I am totally a new bee in Django, it's my 2nd day to learn it. I have already connected to the database and use the pandas.read_sql_query to get the df from database (I know there is ORM but since we…
I'm trying to read an excel-file in python 3.6. Using the code below I managed to get HTTP 200 as status code for the request, could somebody help me to read the contents, too. import requests url=url="https://<myOrg>.sharepoint.com/:x:/s/x-taulukot/Ec0R1y3l7sdGsP92csSO-mgBI8WCN153LfEMvzKMSg1Zzg?e=6NS5Qh" session_obj = requests.Session()…
I have a Pandas DataFrame with this column: This is an extraction from a database in Mongo but I don't know how to handle a column containing both [] and {}: How can split this column into two columns? Desired…
My actual question was this Read exel file from url in python 3.6 but having tried the instructions in comments I got the error io.UnsupportedOperation: seek Here's the code: import pandas as pd from urllib.request import Request, urlopen url =…
I have a string dictionary as user input in Python console. The string format looks like "{"Column A": str, "Column B": str}". Eventually, I want to convert this string to dict format like {"Column A": str, "Column B": str} so…
I have trouble in getting values from a Json and storing in a Dataframe. My Json looks like { "issues": [ { "expand": "operations", "id": "1", "fields": { "customfield_100": [ { "self": "https://url1001", "value": "Mobile", "id": "1001", "disabled": "false" }…
I am new to Python and I am having trouble with a CSV file. I have a sample CSV file containing data like this: "123,hahaha,,," "345,hohoho,,," When I use read_csv, the output treats each line as the first column. I…
I have an item dataframe such as: item_dict = { 'index': [18, 24, 25, 26, 30, 31, 37, 38, 61, 62, 63, 67, 68, 69], 'BarCode_x': ['12345678ABCD', '12345678IJKL', '12345678IJKL', '12345678IJKL', '12345678EFGH', '12345678EFGH', '67890123IJKL', '67890123IJKL', '67890123ABCD', '67890123ABCD', '67890123ABCD', '67890123EFGH', '67890123EFGH', '67890123EFGH'],…
I have json files which look like a dictionary of a list of similar dictionaries: {"People":[{"FirstName":"Max","Surname":"Smith"},{"FirstName":"Jane","Surname":"Smart"}], "Animals":[{"Breed":"Cat","Name":"WhiteSocks"},{"Breed":"Dog","Name":"Zeus"}]} I'm using the following code to convert this into a dictionary of pandas dataframes: import pandas as pd import json # Read the…