import tkinter from tkinter import * def printword(event): print("hello") app = Tk() textpane = tkinter.Text(app) textpane.bind('<Control-Key-s>',printword) textpane.pack() printword() app.mainloop() When i run the code it gives me typeerror TypeError: printword() missing 1 required positional argument: 'event' how would I fix this ? Answers: Thank you for visiting the Q&A section on Magenaut. Please note that … Read more
I’ve a dictionary which looks like the example I’ve mentioned below. I need to save it as a json file in the same format without changing the data types to a string value so that it can be imported later on to validate the data type of the parameters used.
I am trying to predict house prices in the Cali housing data set with a random forest. I do not understand why I get a KeyError: 'squared_error' in this simple code:
I am using beautifulsoup to scrape website data. I am getting a handle on how to scrape things that are displayed on the webpage, however, there is a unique identifier embedded in the html that I want to grab that doesn’t have a title. For example:
I’m trying to get the email from the city from http://www.comuni-italiani.it/110/index.html
i need to send a data each every X seconds from a client to a server with SOCKET, so i try this code:
When I try to update conda, I was told to execute conda update -n base conda, does this mean that the conda tool is installed in the base environment? Or the conda tool is installed out of any environment?
I have two columns – one with sentences and the other with single words.
Trying to figure out how to overwrite a variable during unit testing:
#!/usr/bin/env python3 import pandas import numpy example_dataset = { 'Date' : ['01 Mar 2022', '02 Apr 2022', '10 Apr 2022', '15 Apr 2022'], 'Transaction Type' : ['Contactless payment', 'Payment to', 'Contactless payment', 'Contactless payment'], 'Description' : ['Tesco Store', 'Dentist', 'Cinema', 'Sainsburys'], 'Amount' : ['156.00', '55', '21.50', '176.10'] } df = pandas.DataFrame(example_dataset) df ['Date'] = pandas.to_datetime(df['Date'], … Read more