I have a python pandas dataframe, which should be converted to a nested JSON (based on the entry found in the column 'laterality'). My dataframe looks like this: import pandas as pd df1 = pd.DataFrame({'id': [1, 1, 1, 2], 'laterality':…
I need some help on using json_normalizer to create multiple subcolumns from main columns ? The below code is able to generate an output file but its puts everything in one column however i need something seperate columns with heading…
I have a CSV with thousands of hundreds of thousands of rows but basically looks like this personal_id location_type location_number 1 'company' 123 2 'branch 321 1 'branch 456 1 'branch 567 The goal is to group everything by personal_id…
I'm trying to get to the bottom of what I thought would be a simple problem: exporting a dataframe in Pandas into a mysql database. There is a scraper that collates data in pandas to save the csv format **title,…
UPDATE: Json Files: LINK I have a multitude of Json files that have the same individual structure: 0: Title Location Price Net area Gross area ... 1: Title Location ... 2: ... One Json file may run from index 0:…
So I have this fine code: import pandas as pd import requests from datetime import datetime now = datetime.now() dt_string = now.strftime("%Y-%m-%dT%H:00:00") url = 'https://api.energidataservice.dk/dataset/Elspotprices?filter={%22PriceArea%22:[%22DK1%22]}&limit=50' r = requests.get(url) json = r.json() # HourUTC HourDK SpotPriceDKK SpotPriceEUR df = pd.DataFrame(json['records']) df2…
I am relatively new to JSON and after going through several tutorials I have decided to reach out here for additional advice. I am trying to convert the following JSON dictionary via Jupyternotebook/Pandas into a dataframe and later into a…
I've been using pandas' json_normalize for a bit but ran into a problem with specific json file, similar to the one seen here: https://github.com/pandas-dev/pandas/issues/37783#issuecomment-1148052109 I'm trying to find a way to retrieve the data within the Ats -> Ats dict…
I am attempting to make an API call. For this specific API, one of the keys in the JSON file needs to have a nested dictionary inside of it. here is the input data in dataframe format: ID Date Total_Transactions…
import io import pandas as pd csv_data = '''App_name,pre-prod,prod,stage matching-image,nginx,nginx,nginx mismatching-image,nginx,nginx,nginx:1.23.3-alpine''' df = pd.read_csv(io.StringIO(csv_data), sep=",") html_table = df.tohtml() Is there a way to compare the values of columns in dataframe and use it in conditional formatting ? I want compare…