carleen

# Change some of the variables in room type, prevents errors
df.room_type = df.room_type.map({'Private room': 'private_room',
                                'Entire home/apt': 'entire_property',
                                'Shared room': 'shared_room'})

# Adjusts variables for host response times
df.host_response_time = df.host_response_time.map({'within an hour': 'lt_hour',
                                                 'within a few hours': 'lt_few_hours',
                                                 'within a day': 'lt_day',
                                                 'a few days or more': 'gt_day'})

carleen

import sqlite3

# Connect to the SQLite database
conn = sqlite3.connect(db_path)

# Create a cursor object
cur = conn.cursor()

# Execute the query
query = '''SELECT host_response_time, COUNT(*) AS cnt

carleen

-- Table: order
DROP TABLE IF EXISTS orders;
CREATE TABLE orders(
    id int PRIMARY KEY,
    paymentID int NOT NULL,
    chargeID int NOT NULL
);

-- Table: item
DROP TABLE IF EXISTS item;

carleen

from tabulate import tabulate
import sqlite3
import json
from datetime import datetime

con = sqlite3.connect('reids.db')
reid_json = json.load(open('reids.json'))
cur=con.cursor()

order_id = 1

carleen

'''
We'll need three variables to solve this Eigenvalue Problem (based on a Lesile model):
A = the "Leslie matrix"
p_i = the initial population breakdown of healthy, sick, and deceased individuals
percentage = stop value (percentage of healthy + sick people)
'''

import numpy as np

# Our initial Leslie matrix for the system