Code
# Data manipulation libraries
import os
import pandas as pd
import numpy as np
# Visualization
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
# Timer
from tqdm import tqdm, tqdm_notebook
# Regression
from sklearn.linear_model import LinearRegression
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import RandomForestRegressor
from sklearn.ensemble import AdaBoostRegressor
from sklearn.ensemble import GradientBoostingRegressor
from xgboost import XGBRegressor
from sklearn.neural_network import MLPRegressor
from sklearn.neighbors import KNeighborsRegressor
# Model support functions
from sklearn import model_selection
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import PolynomialFeatures
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import GridSearchCV
from scipy.stats import uniform
from sklearn.preprocessing import StandardScaler
from pprint import pprint
from sklearn.inspection import permutation_importance
from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score
# Geo-related libraries
import geopandas as gpd
import folium
from folium.plugins import HeatMap
import geopy
from geopy.geocoders import Nominatim
from geopy.extra.rate_limiter import RateLimiter
import contextily as ctx
import geofeather
from geopandas import GeoDataFrame
from shapely.geometry import Point
from shapely import wkt
from shapely.geometry import Point, MultiPoint
from shapely.ops import nearest_points
from shapely import wkt
import osmnx
