Clean junk "scratchpad" files and outdated CSVs

1 files changed, 0 insertions, 368 deletions

diff --git a/ZestySalesman.py b/ZestySalesman.py
deleted file mode 100644
index de07449..0000000
--- a/ZestySalesman.py
+++ /dev/null
@@ -1,368 +0,0 @@
-#!/usr/bin/env python
-# coding: utf-8
-
-# In[1]:
-
-
-import folium
-import pandas as pd
-
-import utils
-
-# In[2]:
-
-
-# Load the data
-ListA = pd.read_csv('List A.csv')
-ListB = pd.read_csv('List B.csv')
-ListC = pd.read_csv('List C.csv')
-ListD = pd.read_csv('List D.csv')
-
-
-# In[3]:
-
-
-# Create two centroids, one in the North End and one in the Seaport District
-centroids = [[42.365, -71.054], [42.351, -71.045]]
-
-northeastern_coordinate = "-71.09033,42.33976"
-
-
-# In[4]:
-
-
-# Combine the two lists and add a column to indicate the list
-ListA['list'] = 'A'
-ListB['list'] = 'B'
-ListC['list'] = 'C'
-ListD['list'] = 'D'
-
-TotalList = pd.concat([ListA, ListB, ListC, ListD])
-
-
-# In[5]:
-
-
-# Remove all columns but name and gps
-TotalList = TotalList[['name', 'gps', 'list']]
-
-
-# In[6]:
-
-
-# Convert the gps column to a list of lists for k-means
-TotalList['gps'] = TotalList['gps'].apply(lambda x: x.strip('[]').split(','))
-TotalList['gps'] = TotalList['gps'].apply(lambda x: [float(i) for i in x])
-
-
-# In[7]:
-
-
-display(TotalList)
-
-
-# # 2 Routes
-
-# ## Cluster and Minimize
-
-# In[8]:
-
-
-# Cluster and minimize the data
-_, routes = utils.cluster_and_optimize(TotalList, centroids, northeastern_coordinate,
-                                       time_diff=0.25, max_time=24)
-
-route_1_coordinates = routes[0]
-route_2_coordinates = routes[1]
-
-
-# ## Create JSON
-
-# In[9]:
-
-
-# Create a JSON request for the API
-# This is the data we want to get from the API
-route_1 = utils.list_to_string(route_1_coordinates)
-route_2 = utils.list_to_string(route_2_coordinates)
-
-
-# In[10]:
-
-
-# Create a dataframe from the JSON
-df1 = utils.create_json_df(route_1, utils.list_to_string([centroids[0]]), northeastern_coordinate)
-df2 = utils.create_json_df(route_2, utils.list_to_string([centroids[1]]), northeastern_coordinate)
-
-
-# In[11]:
-
-
-# Add columns for the route number
-df1['route'] = 1
-df2['route'] = 2
-
-# Concatenate the two dataframes
-df = pd.concat([df1, df2], ignore_index=True)
-
-
-# In[12]:
-
-
-display(df)
-
-
-# ## Map
-
-# In[13]:
-
-
-# Create a map
-m = folium.Map(location=[df['lon'].mean(), df['lat'].mean()], zoom_start=11)
-
-# Add the points and lines for the two routes with different colors
-colors = ['red', 'blue']
-
-for route in df['route'].unique():
-    df_route = df[df['route'] == route]
-    folium.PolyLine(df_route[['lon', 'lat']].values.tolist(), color=colors[route - 1]).add_to(m)
-    for i in range(len(df_route)):
-        folium.CircleMarker(df_route[['lon', 'lat']].iloc[i].values.tolist(), radius=3, color=colors[route - 1]).add_to(
-            m)
-
-# Display the map
-m
-
-
-# ## Results
-
-# In[14]:
-
-
-# Get the number of waypoints for each route
-route_1_waypoints = len(route_1_coordinates)
-route_2_waypoints = len(route_2_coordinates)
-print("Route 1 has {} waypoints".format(route_1_waypoints))
-print("Route 2 has {} waypoints".format(route_2_waypoints))
-
-
-# In[15]:
-
-
-trip_hrs_1 = utils.get_trip_time(route_1, route_1_waypoints, utils.list_to_string([centroids[0]]),
-                                 northeastern_coordinate)
-print("The trip will take {} hours".format(trip_hrs_1))
-trip_hrs_2 = utils.get_trip_time(route_2, route_2_waypoints, utils.list_to_string([centroids[1]]),
-                                 northeastern_coordinate)
-print("The trip will take {} hours".format(trip_hrs_2))
-
-
-# # 3 Routes
-
-# In[16]:
-
-
-# Cluster and minimize the data
-# Add a third centroid in the Financial District
-centroids.append([42.356, -71.055])
-_, routes = utils.cluster_and_optimize(TotalList, centroids, northeastern_coordinate, time_diff=0.3, max_time=24)
-
-route_1_coordinates = routes[0]
-route_2_coordinates = routes[1]
-route_3_coordinates = routes[2]
-
-
-# ## Create JSON
-
-# In[17]:
-
-
-# Create a JSON request for the API
-# This is the data we want to get from the API
-route_1 = utils.list_to_string(route_1_coordinates)
-route_2 = utils.list_to_string(route_2_coordinates)
-route_3 = utils.list_to_string(route_3_coordinates)
-
-
-# In[18]:
-
-
-# Create a dataframe from the JSON
-df1 = utils.create_json_df(route_1, utils.list_to_string([centroids[0]]), northeastern_coordinate)
-df2 = utils.create_json_df(route_2, utils.list_to_string([centroids[1]]), northeastern_coordinate)
-df3 = utils.create_json_df(route_3, utils.list_to_string([centroids[2]]), northeastern_coordinate)
-
-
-# In[19]:
-
-
-# Add columns for the route number
-df1['route'] = 1
-df2['route'] = 2
-df3['route'] = 3
-
-# Concatenate the three dataframes
-df = pd.concat([df1, df2, df3], ignore_index=True)
-
-
-# In[20]:
-
-
-display(df)
-
-
-# ## Map
-
-# In[21]:
-
-
-# Create a map
-m = folium.Map(location=[df['lon'].mean(), df['lat'].mean()], zoom_start=11)
-
-# Add the points and lines for the three routes with different colors
-colors = ['red', 'blue', 'green']
-
-for route in df['route'].unique():
-    df_route = df[df['route'] == route]
-    folium.PolyLine(df_route[['lon', 'lat']].values.tolist(), color=colors[route - 1]).add_to(m)
-    for i in range(len(df_route)):
-        folium.CircleMarker(df_route[['lon', 'lat']].iloc[i].values.tolist(), radius=3, color=colors[route - 1]).add_to(
-            m)
-
-# Display the map
-m
-
-
-# ## Results
-
-# In[22]:
-
-
-# Get the number of waypoints for each route
-route_1_waypoints = len(route_1_coordinates)
-route_2_waypoints = len(route_2_coordinates)
-route_3_waypoints = len(route_3_coordinates)
-print("Route 1 has {} waypoints".format(route_1_waypoints))
-print("Route 2 has {} waypoints".format(route_2_waypoints))
-print("Route 3 has {} waypoints".format(route_3_waypoints))
-
-
-# In[23]:
-
-
-# Get the trip time for each route
-trip_hrs_1 = utils.get_trip_time(route_1, route_1_waypoints, utils.list_to_string([centroids[0]]),
-                                 northeastern_coordinate)
-print("The trip will take {} hours".format(trip_hrs_1))
-trip_hrs_2 = utils.get_trip_time(route_2, route_2_waypoints, utils.list_to_string([centroids[1]]),
-                                 northeastern_coordinate)
-print("The trip will take {} hours".format(trip_hrs_2))
-trip_hrs_3 = utils.get_trip_time(route_3, route_3_waypoints, utils.list_to_string([centroids[2]]),
-                                 northeastern_coordinate)
-print("The trip will take {} hours".format(trip_hrs_3))
-
-
-# # 10 ROUTES (because I can)
-
-# In[24]:
-
-
-# Cluster and minimize the data
-# Add seven more centroids around Boston with different latitudes and longitudes
-for i in range(7):
-    centroids.append([42.365 + i * 0.01, -71.054 + i * 0.01])
-
-_, routes = utils.cluster_and_optimize(TotalList, centroids, northeastern_coordinate, time_diff=0.5, max_time=24)
-
-
-# ## Create JSON
-
-# In[25]:
-
-
-# Create a JSON request for the API
-# This is the data we want to get from the API
-route_strings = []
-for route in routes:
-    route_strings.append(utils.list_to_string(route))
-
-
-# In[26]:
-
-
-# Create a dataframe from the JSON
-dfs = []
-for i in range(len(routes)):
-    dfs.append(utils.create_json_df(route_strings[i], utils.list_to_string([centroids[i]]), northeastern_coordinate))
-    
-# Concatenate the dataframes
-df = pd.concat(dfs, ignore_index=True)
-
-
-# In[30]:
-
-
-# Add columns for the route number
-for i in range(len(routes)):
-    df['route'].iloc[i * len(routes[i]):(i + 1) * len(routes[i])] = i + 1
-
-
-# In[31]:
-
-
-# Display the dataframe
-display(df)
-
-
-# ## Map
-
-# In[37]:
-
-
-# Create a map
-m = folium.Map(location=[df['lon'].mean(), df['lat'].mean()], zoom_start=11)
-
-# Add the points and lines for the three routes with different colors
-colors = ['red', 'blue', 'green', 'orange', 'purple', 'pink', 'black', 'gray', 'brown', 'yellow']
-
-for route in df['route'].unique():
-    df_route = df[df['route'] == route]
-    folium.PolyLine(df_route[['lon', 'lat']].values.tolist(), color=colors[route - 1]).add_to(m)
-    for i in range(len(df_route)):
-        folium.CircleMarker(df_route[['lon', 'lat']].iloc[i].values.tolist(), radius=3, color=colors[route - 1]).add_to(
-            m)
-        
-# Display the map
-m
-
-
-# ## Results
-
-# In[36]:
-
-
-# Get the number of waypoints for each route
-route_waypoints = []
-for route in routes:
-    route_waypoints.append(len(route))
-for i in range(len(route_waypoints)):
-    print("Route {} has {} waypoints".format(i + 1, route_waypoints[i]))
-
-
-# In[34]:
-
-
-# Get the trip time for each route
-trip_hrs = []
-for i in range(len(routes)):
-    trip_hrs.append(utils.get_trip_time(route_strings[i], route_waypoints[i], utils.list_to_string([centroids[i]]),
-                                        northeastern_coordinate))
-for i in range(len(trip_hrs)):
-    print("The trip will take {} hours".format(trip_hrs[i]))
-
-
-# In[ ]:
-
-
-
-