mrjxtr

Create an empty volume on an existing disk or a separate disk. Create a bootable usb for installing arch Install arch using archinstall script

Things to do after arch install

update everything

sudo pacman -Syu

If boot is too long because of dev-tpmrm0

mrjxtr

{
	// Misc
	"Create code block header": {
		"prefix": "#",
		"scope":"python",
		"body": [
			"#$1 ------------------------------------------------------",
			"#$1 $2",
			"#$1 ------------------------------------------------------"
		],

mrjxtr

"""
Module for configuring plot aesthetics using Matplotlib and Seaborn.

This module provides functions to set a custom color palette and apply
consistent theming across plots created with Matplotlib and Seaborn.
"""

import matplotlib as mpl
import seaborn as sns
from cycler import cycler

mrjxtr

/** Cursor Custom Settings **/

/** Removing buttons on the start screen **/
.cursor-button.cursor-button-primary.cursor-button-primary-clickable {
  display: none !important;
}

.cursor-button.cursor-button-secondary.cursor-button-secondary-clickable {
  display: none !important;
}

mrjxtr

// Place your key bindings in this file to override the defaults
[
  // Vim Navigation keybindings
  {
    "key": "ctrl-h",
    "command": "workbench.action.navigateLeft"
  },
  {
    "key": "ctrl-l",
    "command": "workbench.action.navigateRight",

mrjxtr

{
  // Update Settings
  "update.mode": "manual",
  "security.workspace.trust.untrustedFiles": "open",

  // Editor Settings
  "editor.defaultFormatter": "charliermarsh.ruff",
  "[javascript]": {
    "editor.defaultFormatter": "esbenp.prettier-vscode"
  },

mrjxtr

from math import sqrt
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error, r2_error
from sklearn.model_selection import train_test_split

df = 
target = 

X = df.drop(target, axis=1)
y = df[target]

mrjxtr

def export_figs(export_dir: str, fig: str, fig_number: int, filename: str) -> None:
    """function to export figures generated with matplotlib/seaborn.

    Converts figures to png format and saves them to a specified directory.

    Args:
        export_dir (str): the directory to export the figure to.
        fig (str): the figure generated to export.
        fig_number (str): the number of the figure based on it's position in the list.
        filename (str): the name you want to give the figure.

mrjxtr

import os

import numpy as np
import pandas as pd

# Load data
script_dir = os.path.dirname(__file__)
data_path = os.path.abspath(os.path.join(script_dir, '../data/$1/$2'))

# Read data into a DataFrame