Volcano map test

volcanoes2010.py

# -*- coding: utf-8 -*-
"""
Created on Sun May  6 20:29:19 2018

@author: astro 1
"""

#Volcano eruption map from 2010 to present
#data downloaded from 
#https://www.ngdc.noaa.gov/nndc/servlet/ShowDatasets?dataset=102557&search_look=50&display_look=50
#script extracts relavent properties of volcanoes and places colored markers
#with popup info about each one 

import pandas as pd
import folium

#download filename is "results" tab delimited
df1 = pd.read_csv("results", sep = '\t')

#look at the shape of the df and get column names
#print(df1.shape)
#print(df1.columns)

#subset df1 to only get all rows and only columns we need


df2 = df1.loc[:, ("Year", "Name", "Country", 
                 "Latitude", "Longitude", "Type")]


#since this data is from the web check to see if there are any Nan
#df2.isnull().sum().sum()

#can also pass to check if true to run an if statement
#df2.isnull().any().any()

if df2.isnull().any().any() is True:
    print("Sorry there is at least 1 NaN value")
else:
    pass


#check the first and last 5 rows
#df2.head(n = 5)
#df2.tail(n = 5)

#established by now that it's clean data we need to first subset the lat long
df_ll = df2.loc[:, ("Latitude", "Longitude")]

#subset desired properties to display in popup
df_year = df2.loc[:, ("Year")]
df_name = df2.loc[:, ("Name")]
df_country = df2.loc[:, ("Country")]
df_type = df2.loc[:, ("Type")]

#take the dataframe values for lat long and make a list of lists
df_ll_list = df_ll.values.tolist()

#center map at some location if desired
#latlong = [30.2672, -97.7431]


#build the base map centered on latlong with zoom
#
#map = folium.Map(location = [*latlong], 
#                 zoom_start = 2, tiles = "Mapbox Bright")

#build the map based on no location, just default center of map, no zoom
#map = folium.Map(location = None, tiles = "Mapbox Bright")

#use terrain map layer to actually see volcano terrain
map = folium.Map(location = None, tiles = "Stamen Terrain")

#insert multiple markers, iterate through list
#each marker popup will display the lat lon coordinates from the list
#

#possibly add a different color marker for the type and look for
#trends where certain types are prevalent


i = 0
for coordinates in df_ll_list:
    
    #assign a color marker for the type of volcano, Strato being the most common
    if df_type[i] == "Stratovolcano":
        type_color = "green"
    elif df_type[i] == "Complex volcano":
        type_color = "blue"
    elif df_type[i] == "Shield volcano":
        type_color = "orange"
    else:
        type_color = "black"
        
        
    #now place the markers with the popup labels and data
    map.add_child(folium.Marker(location = coordinates, 
                            popup = 
                            "Year: " + str(df_year[i]) + '<br>' +
                            "Name: " + str(df_name[i]) + '<br>' + 
                            "Country: " + str(df_country[i]) + '<br>' 
                            "Type: " + str(df_type[i]) + '<br>'
                            "Coordinates: " + str(df_ll_list[i]), 
                            icon = folium.Icon(color = "%s" % type_color)))
    i = i + 1

#title the map
fg = folium.FeatureGroup(name = "Volcano eruptions since 2010")

#add title
map.add_child(fg)

#save map
map.save("volcanoes2010.html")