described in https://tidesandcurrents.noaa.gov/publications/techrpt83_Global_and_Regional_SLR_Scenarios_for_the_US_final.pdf
In [1]:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import re
import pandas as pd
In [2]:
df = pd.read_csv('techrpt083.csv', skiprows=15)
In [3]:
df.shape
Out[3]:
(35046, 20)
In [4]:
def df_station(df, station):
df2 = df[df['Site'].str.contains(station)]
df3 = df2[df2['Scenario'].str.contains("1.0 - HIGH")]
df4 = pd.melt(df3, id_vars=df3.columns.values[0:6],
var_name="Date", value_name="Value")
df5 = df4.copy(deep=True)
for scenario in df2['Scenario'].values:
df3 = df2[df2['Scenario'].str.contains(scenario)]
var = scenario.replace(' ','')
df4 = pd.melt(df3, id_vars=df3.columns.values[0:6],
var_name="Date", value_name=var)
df5[var] = df4[var]
return df5
In [5]:
df3 = df[~df['Site'].str.contains('GMSL')]
In [6]:
dfs = [df_station(df3,station) for station in df3['Site'].unique()]
In [7]:
type(dfs)
Out[7]:
list
In [8]:
df6 = pd.concat(dfs)
In [9]:
del df6['Value']
del df6['Scenario']
In [14]:
del df6['PSMSL ID']
In [10]:
df6['Date'] = [int(re.findall(r'\d+', v)[0]) for v in df6['Date'].values]
df6.rename(columns = {'Site':'id'}, inplace = True)
In [15]:
df6.to_csv('all_stations.csv', index=False)
In [12]:
df6
Out[12]:
id
PSMSL ID
Latitude
Longitude
Background RSL rate (mm/yr)
Date
0.3-MED
0.3-LOW
0.3-HIGH
0.5-MED
...
1.0-HIGH
1.5-MED
1.5-LOW
1.5-HIGH
2.0-MED
2.0-LOW
2.0-HIGH
2.5-MED
2.5-LOW
2.5-HIGH
0
SAN FRANCISCO
10
37.81
-122.47
0.02
2000
0.0
0.0
0.0
0.0
...
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1
SAN FRANCISCO
10
37.81
-122.47
0.02
2010
3.0
1.0
4.0
3.0
...
6.0
7.0
4.0
8.0
8.0
7.0
9.0
8.0
3.0
9.0
2
SAN FRANCISCO
10
37.81
-122.47
0.02
2020
6.0
3.0
8.0
8.0
...
12.0
13.0
9.0
15.0
16.0
14.0
18.0
18.0
10.0
20.0
3
SAN FRANCISCO
10
37.81
-122.47
0.02
2030
10.0
6.0
13.0
12.0
...
19.0
22.0
17.0
25.0
28.0
25.0
32.0
32.0
21.0
36.0
4
SAN FRANCISCO
10
37.81
-122.47
0.02
2040
13.0
8.0
18.0
17.0
...
28.0
34.0
27.0
38.0
46.0
41.0
49.0
54.0
37.0
57.0
5
SAN FRANCISCO
10
37.81
-122.47
0.02
2050
17.0
10.0
23.0
22.0
...
40.0
51.0
41.0
57.0
70.0
63.0
73.0
83.0
60.0
88.0
6
SAN FRANCISCO
10
37.81
-122.47
0.02
2060
21.0
13.0
28.0
28.0
...
52.0
69.0
58.0
77.0
97.0
88.0
101.0
118.0
90.0
125.0
7
SAN FRANCISCO
10
37.81
-122.47
0.02
2070
25.0
15.0
33.0
33.0
...
66.0
90.0
76.0
100.0
127.0
117.0
133.0
158.0
124.0
166.0
8
SAN FRANCISCO
10
37.81
-122.47
0.02
2080
28.0
17.0
38.0
38.0
...
81.0
114.0
98.0
127.0
163.0
151.0
170.0
202.0
163.0
215.0
9
SAN FRANCISCO
10
37.81
-122.47
0.02
2090
31.0
19.0
43.0
43.0
...
97.0
141.0
122.0
155.0
204.0
188.0
211.0
252.0
207.0
268.0
10
SAN FRANCISCO
10
37.81
-122.47
0.02
2100
34.0
19.0
49.0
48.0
...
117.0
174.0
147.0
191.0
253.0
232.0
261.0
311.0
257.0
334.0
11
SAN FRANCISCO
10
37.81
-122.47
0.02
2120
40.0
23.0
55.0
56.0
...
141.0
210.0
191.0
247.0
324.0
299.0
361.0
433.0
368.0
471.0
12
SAN FRANCISCO
10
37.81
-122.47
0.02
2150
47.0
25.0
65.0
70.0
...
202.0
318.0
286.0
370.0
500.0
459.0
551.0
669.0
573.0
725.0
13
SAN FRANCISCO
10
37.81
-122.47
0.02
2200
53.0
17.0
83.0
92.0
...
325.0
541.0
476.0
630.0
872.0
804.0
933.0
1130.0
1014.0
1207.0
0
NEW YORK
12
40.70
-74.01
1.38
2000
0.0
0.0
0.0
0.0
...
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1
NEW YORK
12
40.70
-74.01
1.38
2010
5.0
2.0
7.0
6.0
...
11.0
12.0
7.0
15.0
14.0
13.0
17.0
14.0
6.0
15.0
2
NEW YORK
12
40.70
-74.01
1.38
2020
11.0
6.0
14.0
13.0
...
23.0
25.0
14.0
31.0
31.0
25.0
35.0
29.0
14.0
33.0
3
NEW YORK
12
40.70
-74.01
1.38
2030
15.0
10.0
21.0
19.0
...
34.0
39.0
24.0
45.0
48.0
43.0
53.0
50.0
28.0
55.0
4
NEW YORK
12
40.70
-74.01
1.38
2040
20.0
13.0
28.0
25.0
...
47.0
53.0
36.0
61.0
67.0
63.0
75.0
76.0
45.0
82.0
5
NEW YORK
12
40.70
-74.01
1.38
2050
25.0
15.0
36.0
31.0
...
60.0
71.0
51.0
80.0
92.0
85.0
100.0
105.0
68.0
114.0
6
NEW YORK
12
40.70
-74.01
1.38
2060
31.0
18.0
42.0
39.0
...
76.0
92.0
68.0
104.0
124.0
107.0
130.0
144.0
97.0
150.0
7
NEW YORK
12
40.70
-74.01
1.38
2070
36.0
19.0
49.0
45.0
...
93.0
114.0
87.0
130.0
154.0
134.0
166.0
185.0
130.0
194.0
8
NEW YORK
12
40.70
-74.01
1.38
2080
39.0
21.0
54.0
50.0
...
111.0
139.0
108.0
159.0
189.0
168.0
206.0
230.0
170.0
241.0
9
NEW YORK
12
40.70
-74.01
1.38
2090
44.0
21.0
60.0
56.0
...
130.0
167.0
130.0
191.0
234.0
205.0
250.0
286.0
214.0
296.0
10
NEW YORK
12
40.70
-74.01
1.38
2100
46.0
22.0
65.0
61.0
...
150.0
197.0
154.0
225.0
279.0
248.0
298.0
342.0
262.0
357.0
11
NEW YORK
12
40.70
-74.01
1.38
2120
51.0
27.0
75.0
70.0
...
176.0
247.0
195.0
297.0
368.0
334.0
405.0
459.0
373.0
530.0
12
NEW YORK
12
40.70
-74.01
1.38
2150
58.0
28.0
88.0
85.0
...
238.0
353.0
281.0
420.0
561.0
493.0
586.0
695.0
574.0
772.0
13
NEW YORK
12
40.70
-74.01
1.38
2200
69.0
26.0
110.0
110.0
...
359.0
567.0
442.0
673.0
926.0
826.0
958.0
1139.0
1011.0
1237.0
0
HALIFAX
96
44.67
-63.58
1.46
2000
0.0
0.0
0.0
0.0
...
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1
HALIFAX
96
44.67
-63.58
1.46
2010
5.0
2.0
7.0
6.0
...
10.0
11.0
6.0
13.0
14.0
13.0
15.0
15.0
6.0
16.0
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
12
grid_-28.5_249.5
1011852495
-28.50
-110.50
0.12
2150
42.0
10.0
71.0
67.0
...
214.0
317.0
277.0
359.0
420.0
383.0
473.0
544.0
486.0
636.0
13
grid_-28.5_249.5
1011852495
-28.50
-110.50
0.12
2200
47.0
-6.0
92.0
87.0
...
347.0
534.0
462.0
614.0
742.0
676.0
828.0
1065.0
982.0
1177.0
0
grid_-28.5_250.5
1011852505
-28.50
-109.50
0.06
2000
0.0
0.0
0.0
0.0
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0.0
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0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1
grid_-28.5_250.5
1011852505
-28.50
-109.50
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2010
1.0
-1.0
4.0
3.0
...
7.0
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3.0
9.0
8.0
7.0
11.0
8.0
3.0
11.0
2
grid_-28.5_250.5
1011852505
-28.50
-109.50
0.06
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5.0
1.0
8.0
7.0
...
13.0
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7.0
16.0
16.0
12.0
18.0
15.0
8.0
19.0
3
grid_-28.5_250.5
1011852505
-28.50
-109.50
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2030
8.0
3.0
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...
21.0
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26.0
27.0
23.0
30.0
29.0
20.0
33.0
4
grid_-28.5_250.5
1011852505
-28.50
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11.0
4.0
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30.0
33.0
25.0
39.0
42.0
38.0
47.0
47.0
37.0
52.0
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grid_-28.5_250.5
1011852505
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grid_-28.5_250.5
1011852505
-28.50
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84.0
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104.0
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grid_-28.5_250.5
1011852505
-28.50
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2070
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...
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109.0
99.0
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grid_-28.5_250.5
1011852505
-28.50
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grid_-28.5_250.5
1011852505
-28.50
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2090
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grid_-28.5_250.5
1011852505
-28.50
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2100
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grid_-28.5_250.5
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2120
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grid_-28.5_250.5
1011852505
-28.50
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2150
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grid_-28.5_250.5
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-28.50
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grid_-28.5_251.5
1011852515
-28.50
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2000
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grid_-28.5_251.5
1011852515
-28.50
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2010
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2
grid_-28.5_251.5
1011852515
-28.50
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16.0
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12.0
18.0
16.0
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3
grid_-28.5_251.5
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2030
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...
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grid_-28.5_251.5
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27314 rows × 24 columns
In [ ]:
Content source: rsignell-usgs/sweet_slr
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