def plot_flight(lons, lats):
"""plot the igc data to a map"""
data = [Scattergeo(lon=lons, lat=lats)]
my_layout = Layout(title='IGC flight data')
fig = {'data': data, 'layout': my_layout}
offline.plot(fig, filename='IGC_flight_data.html')
#The indent=4 arguement tells dump() to format the data using indent
json.dump(eq_data,outfile,indent=4)
list_of_eqs = eq_data['features']
mags, lons, lats = [], [], []
for eq in list_of_eqs:
mag = eq['properties']['mag']
lon = eq['geometry']['coordinates'][0]
lat = eq['geometry']['coordinates'][1]
mags.append(mag)
lons.append(lon)
lats.append(lat)
print(mags[:10])
print(lons[:10])
print(lats[:10])
from plotly.graph_objs import Scattergeo, Layout
from plotly import offline
data = [Scattergeo(lon=lons, lat=lats)]
my_layout = Layout(title="Global Earthquakes")
fig = {'data': data, 'layout': my_layout}
offline.plot(fig,filename='global_earthquakes.html')
fire_data = json.load(infile)
json.dump(fire_data, outfile, indent=4)
datalons, datalats, databright = [], [], []
for x in fire_data:
lon = x["logitude"]
lat = x["latitude"]
bright = x["brightness"]
if bright > 450:
databright.append(bright)
datalons.append(lon)
datalats.append(lat)
list_of_fire = fire_data['features']
brightness, longitude, latitude = [], [], []
from plotly.graph_objs import Scattergeo, Layout
from plotly import offline
data = [Scattergeo(longitude=lons, latitude=lats)]
my_layout = Layout(title="US Fires from 9-1-2020 to 9-13-2020")
fig = {"data": data, 'layout': my_layout}
offline.plot(fig, filename='US_fires_9_1.html')
print(fires_data['features'][0]['properties']['brightness'])
print(len(all_eq_dicts))
# Extract the mag of the earthquakes.
mags = [eq_dict["properties"]["mag"] for eq_dict in all_eq_dicts]
mags = [mag if mag >= 0 else -1 * mag for mag in mags]
hover_text = [eq_dict["properties"]["title"] for eq_dict in all_eq_dicts]
# Extract the longtitude and latitudes of earthquakes. geodata are in (long, latitude) format
longt = [eq_dict["geometry"]["coordinates"][0] for eq_dict in all_eq_dicts]
latit = [eq_dict["geometry"]["coordinates"][1] for eq_dict in all_eq_dicts]
# Map the earthquakes.
data = [Scattergeo(lon=longt, lat=latit)]
# Another way to represent data
data_2 = [
{
"type": "scattergeo",
"lon": longt,
"lat": latit,
"text" : hover_text,
"marker": {
"size": [4 * mag for mag in mags],
"color": mags,
"colorscale": "Rainbow",
"reversescale": False,
"colorbar": {"title": "Magnitude"},
},
list_of_eqs = eq_data["features"]
mags = []
lons = []
lats = []
for eq in list_of_eqs:
mag = eq["properties"]["mag"]
lon = eq["geometry"]["coordinates"][0]
lat = eq["geometry"]["coordinates"][1]
mags.append(mag)
lons.append(lon)
lats.append(lat)
print(mags[:10]) # from zero to tenth element, 0 to 9, called list slicing
print(lons[:10])
print(lats[:10])
# above basically has eq as the first part of statement, eq_data['features'], for statement adds vars as second part
# graph
from plotly.graph_objs import Scattergeo, Layout # Remeber case sensitive
from plotly import offline
data = [Scattergeo(lon=lons, lat=lats)] # requires list of a and list of b
my_layout = Layout(title="Global Earthquakes")
fig = {"data": data, "layout": my_layout}
offline.plot(fig, filename="global_earthquakes.html")
json.dump(all_eq_data, f, indent=4)
#Make a list of all earthquakes.
all_eq_dicts = all_eq_data['features']
mags, lons, lats = [], [], []
for eq_dict in all_eq_dicts:
mag = eq_dict['properties']['mag']
lon = eq_dict['geometry']['coordinates'][0]
lat = eq_dict['geometry']['coordinates'][1]
mags.append(mag)
lons.append(lon)
lats.append(lat)
print(mags[:10])
print(lons[:5])
print(lats[:5])
#Map the earthquakes.
data = [
Scattergeo(lon=lons, lat=lats)
] #Define a list called data and create Scattergeo module inside the list.
my_layout = Layout(title='Global earthquakes') #Give chart a title.
fig = {
'data': data,
'layout': my_layout
} #Create dictionary called fig that contains data and layout.
offline.plot(fig, filename='global_earthquakes.html'
) #Plot() function with a descriptive name for the output.
with open(filename, 'r') as f:
all_eq_data = json.load(f)
all_eq_dicts = all_eq_data['features']
mags = [mag['properties']['mag'] for mag in all_eq_dicts]
lons = [lon['geometry']['coordinates'][0] for lon in all_eq_dicts]
lats = [lat['geometry']['coordinates'][1] for lat in all_eq_dicts]
hover_texts = [
hover_text['properties']['title'] for hover_text in all_eq_dicts
]
# Map the earthquakes.
data = [
Scattergeo(lon=lons,
lat=lats,
text=hover_texts,
marker={
'size': [5 * mag for mag in mags],
'color': mags,
'colorscale': 'Viridis',
'reversescale': True,
'colorbar': {
'title': 'Magnitude'
}
})
]
my_layout = Layout(title=all_eq_data['metadata']['title'])
fig = {'data': data, 'layout': my_layout}
offline.plot(fig, filename='output-files/global_earthquakes.html')
lats.append(lat)
# print(brights[:10])
# print(lons[:10])
# print(lats[:10])
from plotly.graph_objs import Scattergeo, Layout
from plotly import offline
data = [{
"type": "scattergeo",
"lon": lons,
"lat": lats,
"marker": {
"size": [0.02 * brightness for brightness in brights],
"color": brights,
"colorscale": "Viridis",
"reversescale": True,
"colorbar": {
"title": "Brightness"
},
},
}]
Scattergeo(lon=lons, lat=lats) # taking scatterplots and putting on a map
my_layout = Layout(title="Prominent US Fires") # give layout for ^
fig = {"data": data, "layout": my_layout}
offline.plot(fig, filename="us_fires.html")
with open(filename) as f:
reader = csv.reader(f)
column_header = next(reader)
print(column_header)
for rec in reader:
lons.append(rec[1])
lats.append(rec[0])
bright_ti4.append(rec[2])
hover_texts.append(rec[5])
# Map the earthquakes.
data = [
Scattergeo(
lon=lons,
lat=lats,
text=['Reported on : ' + hover_text for hover_text in hover_texts],
marker={
'size': 2,
'color': 'firebrick',
'colorscale': 'Viridis',
'reversescale': True,
'colorbar': {
'title': 'Magnitude'
}
})
]
my_layout = Layout(title='World Fires!!!')
fig = {'data': data, 'layout': my_layout}
offline.plot(fig, filename='output-files/world_fires.html')
list_of_eqs = []
list_of_eqs = eq_data["features"]
# print(list_of_eqs)
mags, longs, latds = [], [], []
# eq is already the sub 0 index value, so only
# properties and mag need to be indexed to get each eq magnitude
for eq in list_of_eqs:
mag = eq["properties"]["mag"]
long = eq["geometry"]["coordinates"][0]
latd = eq["geometry"]["coordinates"][1]
mags.append(mag)
longs.append(long)
latds.append(latd)
print(mags[:10])
print(longs[:10])
print(latds[:10])
data = [Scattergeo(lon=longs, lat=latds)]
my_layout = Layout(title="Global Earthquakes")
fig = {'data': data, 'layout': my_layout}
offline.plot(fig, filename="global_earth")
import chapter_sixteen.eq_explore_data
import json
from plotly.graph_objs import Scattergeo, Layout
from plotly import offline
from chapter_sixteen import eq_explore_data
my_data = [
Scattergeo(lon=eq_explore_data.lons,
lat=eq_explore_data.lats,
text=eq_explore_data.hover_texts,
marker={
'size': [5 * mag for mag in eq_explore_data.mags],
'color': eq_explore_data.mags,
'colorscale': 'Viridis',
'reversescale': True,
'colorbar': {
'title': 'Magnitude'
},
})
]
my_layout = Layout(title='Global Earthquakes')
fig = {'data': my_data, 'layout': my_layout}
offline.plot(fig, filename='global_earthquakes.html')
#Escribiendo archivo JSON bien identado
output_filename = 'significant_month.geojson'
with open(output_filename, 'w') as f2:
json.dump(load_all, f2, indent=4)
#Revisando cuantos terremotos hay dentro
registros_terremotos = load_all['features']
print(f"cantidad de terremotos {len(registros_terremotos)}")
Magnitudes, longitudes, latitudes, hover_text = [], [], [], []
for Feature in registros_terremotos:
Magnitudes.append(Feature['properties']['mag'])
longitudes.append(Feature['geometry']['coordinates'][0])
latitudes.append(Feature['geometry']['coordinates'][1])
hover_text.append(Feature['properties']['title'])
print(Magnitudes[:10])
print(longitudes[:10])
print(latitudes[:10])
data = [Scattergeo(lon=longitudes, lat=latitudes)]
my_layout = Layout(title='Terremotos globales')
fig = {'data': data, 'layout': my_layout}
offline.plot(fig, filename='terremotos_globales.html')
#Imprimir escalas de colores diponibles
for key in colors.PLOTLY_SCALES.keys():
print(key)
brights.append(int(float(
row[2]))) #for some reason doing just int() didn't work
#Print Values of First 10 in Each List
#print(brights[:10])
#print(lons[:10])
#print(lats[:10])
#Load Data to Create Plot of Fire Data
data = [
Scattergeo(
lon=lons,
lat=lats,
#Customize Markers
marker=dict(
color=brights,
colorscale='Viridis',
reversescale=True,
line=dict(width=1, color='White'),
size=12,
#Customize Colorbar
colorbar=dict(titleside="top", title='Brightness')))
]
#Create/Customize Plot Layout
my_layout = Layout(title="Australian Fires - January 2020",
geo=dict(
fitbounds="locations",
showland=True,
landcolor="rgb(229, 236, 246)",
))