YichaoOU

YichaoOU

I have a 3d scatter plot, looks like below:

color represent density, so we can see that we basically have one large group, and all the dots jittered around are probably outliers.

The TSNE plot looks like:

YichaoOU

,Base Curb Weight,Drivetrain,Engine Type,Front Tire Size,Front Wheel Size,Fuel Economy Est-Combined,"Fuel Tank Capacity, Approx","Height, Overall","Length, Overall",Min Ground Clearance,Passenger Capacity,SAE Net Torque @ RPM,Steering Type,Suspension Type - Front,Suspension Type - Rear,Trans Description Cont.
nissan-armada-2021,5577 lbs,Rear Wheel Drive,Regular Unleaded V-8,P265/70HR18,18 X 8 in,16 MPG,26 gal,75.8 in,208.9 in,9.1 in,8,413 @ 4000,Rack-Pinion,Double Wishbone,Double Wishbone,Automatic w/OD
nissan-armada-2022,5577 lbs,Rear Wheel Drive,Regular Unleaded V-8,P265/70HR18,18 X 8 in,16 MPG,26 gal,75.8 in,208.9 in,9.1 in,8,413 @ 4000,Rack-Pinion,Double Wishbone,Double Wishbone,Automatic w/OD
chevrolet-traverse-2022,4310 lbs,Front Wheel Drive,Gas V6,P255/65R18,18 x -TBD- in,21 MPG,19.4 gal,70.7 in,205.9 in,7.51 in,8,266 @ 2800,Electric variable-effort Power Rack & Pinion,MacPherson strut independent,Five-link independent,Automatic
toyota-sequoia-2021,5730 lbs,Rear Wheel Drive,Regular Unleaded V-8,P275/65

YichaoOU

from bs4 import BeautifulSoup
import requests
import pandas as pd
def get_info(make,model,year):
    url=f'https://www.cars.com/research/{make}-{model}-{year}/specs/'
    print (url)
    r = requests.get(url)
    soup = BeautifulSoup(r.content, 'html5lib')
    table = soup.find_all("table")
    df_list = []

YichaoOU

import regex
# exec(open("test.py").read())

def get_aligned_sequence2(q,chosen_alignment):
	m = chosen_alignment.group()
	substitutions, insertions, deletions = chosen_alignment.fuzzy_changes
	
	start = chosen_alignment.span()[0]	
	indels = {}
	# deletion index is for q