Current weather on NE coast

In [5]:

    

import urllib.request
import json


    

In [6]:

    

cities = {'Washington':'38.9,77.0',
            'Atlantic City':'39.4,74.4',
            'Philadelphia':'40.0,75.1',
            'New York':'40.7,73.9',
            'Nantucket':'41.3,70.1',
            'New Haven':'41.3,72.9',
            'New Bedford':'41.7,70.9',
            'Cape Cod':'41.8,70.5',
            'Boston': '42.4,71.1',
         }


    

In [7]:

    

api_str = 'https://api.darksky.net/forecast/817a1054cf8cf001633f17ede8d4ea77/'


    

In [8]:

    

weather = {}
for city in cities:
    weather[city] = json.loads(urllib.request.urlopen(api_str+cities[city]).read())


    

In [9]:

    

for city in weather:
    print("{:<15s}: {:7.4f} ({}), {} m/s, {}°F ({}°F)".format(city, 
                               weather[city]['currently']['precipIntensity'],
                               weather[city]['currently']['precipType'],
                               weather[city]['currently']['windSpeed'],
                               weather[city]['currently']['temperature'],
                               weather[city]['currently']['apparentTemperature'],
                              
                              ))


    

    




Washington     :  0.0001 (rain), 5.31 m/s, 45.91°F (43.21°F)
Atlantic City  :  0.0018 (snow), 3.78 m/s, 12.75°F (6.19°F)
Philadelphia   :  0.0006 (snow), 6.16 m/s, 20.67°F (12.59°F)
New York       :  0.0001 (snow), 4.45 m/s, 24.93°F (19.37°F)
Nantucket      :  0.0001 (snow), 5.95 m/s, 35.02°F (29.86°F)
New Haven      :  0.0008 (rain), 5.42 m/s, 35.66°F (31.02°F)
New Bedford    :  0.0004 (snow), 3.51 m/s, 33.5°F (30.37°F)
Cape Cod       :  0.0001 (snow), 5.01 m/s, 19.99°F (12.96°F)
Boston         :  0.0001 (snow), 4.27 m/s, 31.68°F (27.42°F)

In [10]:

    

import pandas as pd
df_weather = pd.DataFrame({"city":[city for city in cities], 
                           "lat":[ float(loc.split(',')[0]) for loc in cities.values() ],
                           "long":[ float(loc.split(',')[1]) for loc in cities.values() ],
                           "intensity":[weather[city]['currently']['precipIntensity'] for city in cities],
                           "type":[weather[city]['currently']['precipType'] for city in cities],
                           "wind":[weather[city]['currently']['windSpeed'] for city in cities],
                           "temp":[weather[city]['currently']['temperature'] for city in cities],
                           "feelslike":[weather[city]['currently']['apparentTemperature'] for city in cities],
                          })


    

In [11]:

    

df_weather


    

    
Out[11]:







  

    

      

      
city
      
feelslike
      
intensity
      
lat
      
long
      
temp
      
type
      
wind
    
  
  

    

      
0
      
Washington
      
43.21
      
0.0001
      
38.9
      
77.0
      
45.91
      
rain
      
5.31
    
    

      
1
      
Atlantic City
      
6.19
      
0.0018
      
39.4
      
74.4
      
12.75
      
snow
      
3.78
    
    

      
2
      
Philadelphia
      
12.59
      
0.0006
      
40.0
      
75.1
      
20.67
      
snow
      
6.16
    
    

      
3
      
New York
      
19.37
      
0.0001
      
40.7
      
73.9
      
24.93
      
snow
      
4.45
    
    

      
4
      
Nantucket
      
29.86
      
0.0001
      
41.3
      
70.1
      
35.02
      
snow
      
5.95
    
    

      
5
      
New Haven
      
31.02
      
0.0008
      
41.3
      
72.9
      
35.66
      
rain
      
5.42
    
    

      
6
      
New Bedford
      
30.37
      
0.0004
      
41.7
      
70.9
      
33.50
      
snow
      
3.51
    
    

      
7
      
Cape Cod
      
12.96
      
0.0001
      
41.8
      
70.5
      
19.99
      
snow
      
5.01
    
    

      
8
      
Boston
      
27.42
      
0.0001
      
42.4
      
71.1
      
31.68
      
snow
      
4.27
    
  

In [12]:

    

import cartopy
import cartopy.crs as ccrs
import cartopy.io.shapereader as shpreader

import seaborn as sns
import matplotlib.pyplot as plt


    

In [13]:

    

cmap = sns.cubehelix_palette(start=2.8, rot=0.1, as_cmap=True)


    

In [14]:

    

fig = plt.figure(figsize=(24, 36))
ax = plt.axes([0, 0, 1, 1],
              projection=ccrs.PlateCarree())

ax.set_extent([-80, -66.5, 35, 45], ccrs.PlateCarree())
#ax.background_patch.set_visible(True)
#ax.outline_patch.set_visible(True)


shapename = 'admin_1_states_provinces_lakes_shp'
states_shp = shpreader.natural_earth(resolution='110m',
                                     category='cultural', name=shapename)

for state in shpreader.Reader(states_shp).geometries():
    facecolor = [0.9375, 0.9375, 0.859375]
    edgecolor = 'black'

    ax.add_geometries([state], ccrs.PlateCarree(),
                      facecolor=facecolor, edgecolor=edgecolor, alpha=0.5
                      )

# plot temperatures
plt.scatter((df_weather.long * -1).values, 
            df_weather.lat.values,
            c=df_weather.temp,
            cmap=cmap,
            s=800, 
            zorder=2,
            transform=ccrs.PlateCarree())
coords = zip((df_weather.long * -1).values, df_weather.lat.values)
for xy,s in zip(coords, df_weather.temp):
    plt.annotate(xy=xy, 
                 s=s,
                 fontsize=36,
                )
plt.savefig("Temperature in North-East states.png")
plt.show()


    

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