Ais
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from sqlalchemy import create_engine
engine = create_engine('postgresql://postgres:postgres@postgres:5432/postgres', echo=False)
from sqlalchemy import create_engine engine = create_engine('postgresql://postgres:postgres@postgres:5432/postgres', echo=False)
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import pandas as pd
with engine.connect() as connection:
df = pd.read_sql('ais', connection)
df
import pandas as pd with engine.connect() as connection: df = pd.read_sql('ais', connection) df
Out[4]:
mmsi | basedatetime | lat | lon | sog | cog | heading | vesselname | imo | callsign | vesseltype | status | length | width | draft | cargo | transceiverclass | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 367702220 | 2022-03-31 | 29.78763 | -95.08070 | 0.1 | 226.5 | 340.0 | JOE B WARD | None | WDI4808 | 31 | 12.0 | 21.0 | 8.0 | NaN | 57.0 | A |
1 | 671226100 | 2022-03-31 | 25.77626 | -80.20320 | 3.2 | 143.7 | 511.0 | RELIANCE II | IMO9221322 | 5VHS7 | 79 | 0.0 | 52.0 | 12.0 | 2.5 | 70.0 | A |
2 | 367767250 | 2022-03-31 | 29.31623 | -94.78829 | 4.5 | 228.1 | 511.0 | GLEN K | None | WDJ3358 | 52 | 0.0 | 0.0 | 0.0 | 0.0 | 52.0 | A |
3 | 338327436 | 2022-03-31 | 47.29634 | -122.42233 | 0.0 | 360.0 | 511.0 | COOL KAT | IMO0000000 | None | 36 | NaN | 15.0 | 3.0 | NaN | NaN | B |
4 | 367452810 | 2022-03-31 | 29.32824 | -94.77391 | 2.6 | 319.2 | 511.0 | JOHN W JOHNSON | IMO9602344 | WDF4516 | 60 | 0.0 | 80.0 | 19.0 | 3.0 | 60.0 | A |
5 | 367616350 | 2022-03-31 | 31.15502 | -81.49931 | 0.0 | 13.0 | 511.0 | THE NORM | IMO0000000 | WDH4306 | 36 | NaN | 13.0 | 8.0 | NaN | NaN | B |
6 | 367402540 | 2022-03-31 | 38.39598 | -85.62818 | 4.1 | 22.8 | 511.0 | GINGER MOLLER | None | WDE8186 | 31 | 15.0 | 34.0 | 10.0 | NaN | 31.0 | A |
7 | 366919770 | 2022-03-31 | 48.74428 | -122.49504 | 0.0 | 210.3 | 46.0 | LYNN MARIE | IMO9253583 | WDB6192 | 31 | 5.0 | 29.0 | 12.0 | 3.8 | 52.0 | A |
8 | 538006349 | 2022-03-31 | 48.48308 | -125.05758 | 11.9 | 89.1 | 90.0 | ALPHA ETHOS | IMO9723617 | V7ME7 | 70 | 0.0 | NaN | NaN | NaN | 70.0 | A |
9 | 367315790 | 2022-03-31 | 45.57350 | -122.46526 | 9.7 | 308.5 | 308.0 | LORI B | None | WDD9745 | 31 | 0.0 | 17.0 | 9.0 | NaN | 31.0 | A |
10 | 366918650 | 2022-03-31 | 32.08183 | -81.06540 | 0.1 | 177.2 | 511.0 | POINT CLEAR | IMO8972948 | WDB6128 | 31 | 0.0 | 30.0 | 10.0 | NaN | 52.0 | A |
11 | 311000966 | 2022-03-31 | 18.55833 | -66.47910 | 17.5 | 274.5 | 274.0 | KYDON | IMO8916607 | C6EP8 | 60 | 0.0 | 192.0 | 27.0 | 6.4 | 60.0 | A |
12 | 368040430 | 2022-03-31 | 27.50168 | -82.57269 | 0.6 | 251.2 | 511.0 | SEA SEEKER | IMO0000000 | WDK2948 | 36 | NaN | 13.0 | 6.0 | NaN | NaN | B |
13 | 367375730 | 2022-03-31 | 29.36345 | -94.90856 | 0.0 | 301.3 | 271.0 | VICKIE GATES | None | WDE6092 | 31 | 12.0 | 22.0 | 9.0 | 0.0 | 31.0 | A |
14 | 338410861 | 2022-03-31 | 47.80646 | -122.39279 | 0.0 | 31.7 | 511.0 | LILY B. | IMO0000000 | None | 37 | NaN | 8.0 | 2.0 | NaN | NaN | B |
15 | 316007566 | 2022-03-31 | 49.19279 | -122.92069 | 0.1 | 239.6 | 511.0 | PORT FRASER | None | CZ3230 | 37 | 15.0 | 11.0 | 3.0 | 1.5 | 57.0 | A |
16 | 338424624 | 2022-03-31 | 29.55824 | -95.02928 | 0.2 | 219.8 | 511.0 | BILLFISHER | IMO0000000 | None | 30 | NaN | 17.0 | 5.0 | NaN | NaN | B |
17 | 367015950 | 2022-03-31 | 29.26563 | -89.35339 | 0.0 | 193.8 | 511.0 | CAPT JACK | None | WDC3898 | 31 | 0.0 | 14.0 | 5.0 | NaN | 52.0 | A |
18 | 367121850 | 2022-03-31 | 32.58144 | -91.12419 | 9.5 | 130.3 | 128.0 | LELAND SPEAKES | None | WDD2945 | 31 | 15.0 | 45.0 | 13.0 | NaN | 32.0 | A |
19 | 338233531 | 2022-03-31 | 47.62901 | -122.39115 | 0.4 | 360.0 | 511.0 | CATALYST | IMO0000000 | None | 36 | NaN | 14.0 | 4.0 | NaN | NaN | B |
20 | 368206360 | 2022-03-31 | 47.60131 | -122.33908 | 0.0 | 105.2 | 58.0 | COMMANDER | None | WDM4430 | 40 | 0.0 | 43.0 | 13.0 | 1.7 | 40.0 | A |
21 | 368004920 | 2022-03-31 | 39.78632 | -91.36278 | 4.7 | 7.2 | 511.0 | SIR RICHARD | None | WDJ7255 | 31 | 0.0 | NaN | NaN | NaN | 31.0 | A |
22 | 219028420 | 2022-03-31 | 28.66703 | -93.59339 | 9.5 | 129.4 | 129.0 | TORM CORRIDO | IMO9411305 | OZNT2 | 89 | 0.0 | 182.0 | 32.0 | 10.8 | 89.0 | A |
23 | 367774150 | 2022-03-31 | 30.06910 | -90.90375 | 3.2 | 328.6 | 335.0 | SCF MARINER | None | WDJ4074 | 31 | 15.0 | NaN | NaN | NaN | 57.0 | A |
24 | 367534010 | 2022-03-31 | 30.15823 | -90.99730 | 0.1 | 56.5 | 347.0 | SOPHIA GOLDING | None | WDG4196 | 31 | 12.0 | 27.0 | NaN | NaN | 57.0 | A |
25 | 354499000 | 2022-03-31 | 29.18968 | -94.63571 | 0.2 | 193.5 | 107.0 | MSC ESTHI | IMO9304411 | 3EFU3 | 70 | 1.0 | 336.0 | 45.0 | 15.0 | 71.0 | A |
26 | 368926035 | 2022-03-31 | 38.58866 | -90.20667 | 0.0 | 360.0 | 511.0 | KIMMSWICK | None | AENA | 33 | 15.0 | NaN | NaN | NaN | 33.0 | A |
27 | 368070780 | 2022-03-31 | 21.31383 | -157.86673 | 0.0 | 287.0 | 511.0 | RAINBOWS | IMO0000000 | WDK6055 | 30 | NaN | 0.0 | 0.0 | NaN | NaN | B |
28 | 368112480 | 2022-03-31 | 48.10715 | -122.77666 | 1.1 | 360.0 | 511.0 | JESTER | IMO0000000 | WDL2486 | 37 | NaN | 12.0 | 6.0 | NaN | NaN | B |
29 | 368044430 | 2022-03-31 | 29.76417 | -95.10827 | 0.0 | 325.4 | 0.0 | CORYELL | None | WDK3354 | 57 | 12.0 | 116.0 | 34.0 | 3.1 | 57.0 | A |
30 | 367696750 | 2022-03-31 | 25.57446 | -79.63322 | 8.5 | 336.7 | 511.0 | LEAP OF FAITH | IMO0000000 | WDL3426 | 36 | NaN | 13.0 | 6.0 | NaN | NaN | B |
31 | 367384780 | 2022-03-31 | 45.58756 | -122.77070 | 0.0 | 311.7 | 137.0 | CAROLYN DOROTHY | IMO9552288 | WDE6786 | 31 | 0.0 | 23.0 | 10.0 | NaN | 52.0 | A |
32 | 367560990 | 2022-03-31 | 27.63564 | -82.56339 | 0.0 | 226.7 | 176.0 | ATLAS | IMO9641754 | WDG6819 | 31 | 0.0 | 28.0 | 12.0 | NaN | 52.0 | A |
33 | 367743710 | 2022-03-31 | 33.00909 | -79.92096 | 0.2 | 253.0 | 158.0 | ISLAND MERCHANT | IMO8971592 | WDI8942 | 31 | 0.0 | 19.0 | NaN | NaN | 52.0 | A |
34 | 368163520 | 2022-03-31 | 37.16540 | -89.08592 | 0.0 | 101.7 | 40.0 | WALLER | None | WDL7792 | 52 | 12.0 | 218.0 | 32.0 | 3.0 | 57.0 | A |
35 | 368157190 | 2022-03-31 | 47.64453 | -122.31387 | 0.0 | 360.0 | 511.0 | OTIS 2 | IMO0000000 | WDL7111 | 37 | NaN | 14.0 | 5.0 | NaN | NaN | B |
36 | 367625810 | 2022-03-31 | 33.76800 | -118.22268 | 1.3 | 171.1 | 170.0 | VETERAN | IMO9765720 | WDH5227 | 31 | 0.0 | 31.0 | 12.0 | NaN | 52.0 | A |
37 | 368123940 | 2022-03-31 | 33.61557 | -117.90354 | 0.0 | 360.0 | 511.0 | REVE D'O | IMO0000000 | WDL3676 | 36 | NaN | 14.0 | 8.0 | NaN | NaN | B |
38 | 356436000 | 2022-03-31 | 26.06004 | -80.13008 | 0.0 | 46.4 | 261.0 | EVERGLORY | IMO8512889 | 3EPI9 | 70 | 0.0 | 225.0 | 32.0 | 13.2 | 70.0 | A |
39 | 369494415 | 2022-03-31 | 30.17030 | -85.75557 | 0.0 | 279.3 | 1.0 | CG49415 | None | None | 90 | 0.0 | 14.0 | NaN | NaN | 51.0 | A |
40 | 338361065 | 2022-03-31 | 47.66621 | -122.38829 | 0.0 | 360.0 | 511.0 | ESCAPE | IMO0000000 | None | 37 | NaN | 18.0 | 5.0 | NaN | NaN | B |
41 | 366972280 | 2022-03-31 | 29.77964 | -95.09884 | 0.0 | 258.1 | 511.0 | JOEY DEVALL | None | WYB7063 | 31 | 0.0 | 18.0 | 7.0 | NaN | 31.0 | A |
42 | 368220140 | 2022-03-31 | 18.34024 | -64.79517 | 0.1 | 360.0 | 511.0 | LECHOIX | IMO0000000 | 1318668 | 36 | NaN | 0.0 | 0.0 | NaN | NaN | B |
43 | 368132890 | 2022-03-31 | 28.40915 | -80.66608 | 0.0 | 302.3 | 101.0 | BAYOU BANDIT | IMO739103200 | WDL4590 | 0 | 0.0 | 0.0 | 0.0 | 3.0 | 0.0 | A |
44 | 368098250 | 2022-03-31 | 25.75557 | -80.18413 | 6.5 | 351.7 | 511.0 | ABBE OF MY EYE | IMO0000000 | WDK8869 | 37 | NaN | 13.0 | 4.0 | NaN | NaN | B |
45 | 367438530 | 2022-03-31 | 29.71237 | -93.16237 | 9.6 | 111.6 | 511.0 | CAPT PEYTON P | IMO9593050 | WDF3321 | 60 | 0.0 | 44.0 | 9.0 | NaN | 60.0 | A |
46 | 366999521 | 2022-03-31 | 38.58757 | -90.20843 | 0.0 | 212.6 | 511.0 | CG CHENA | None | NAMM | 90 | 0.0 | 22.0 | 6.0 | NaN | 55.0 | A |
47 | 338073736 | 2022-03-31 | 24.55644 | -81.80798 | 0.0 | 360.0 | 511.0 | MISCELLANEOUS | IMO0000000 | None | 37 | NaN | 21.0 | 6.0 | NaN | NaN | B |
48 | 367482310 | 2022-03-31 | 18.00574 | -66.76510 | 0.1 | 232.9 | 511.0 | DON OSCAR P | IMO7621839 | WDF7223 | 31 | 0.0 | 30.0 | 9.0 | 3.0 | 52.0 | A |
49 | 367543860 | 2022-03-31 | 40.49733 | -80.07156 | 0.0 | 308.5 | 41.0 | GEORGETOWN | IMO7202413 | WDG5154 | 31 | 12.0 | 25.0 | 9.0 | NaN | 57.0 | A |
50 | 316029864 | 2022-03-31 | 49.16322 | -122.99342 | 0.0 | 360.0 | 511.0 | MALAHAT II | IMO0000000 | None | 30 | NaN | 13.0 | 5.0 | NaN | NaN | B |
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import seaborn as sns
# Apply the default theme
sns.set_theme()
# Create a visualization
sns.relplot(
data=df,
x="mmsi", y="length", col="width"
)
import seaborn as sns # Apply the default theme sns.set_theme() # Create a visualization sns.relplot( data=df, x="mmsi", y="length", col="width" )
Out[8]:
<seaborn.axisgrid.FacetGrid at 0x7f5ae05f6f80>
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import matplotlib.pyplot as plt
plt.style.use('classic')
%matplotlib inline
import numpy as np
import pandas as pd
data = np.random.multivariate_normal([0, 0], [[5, 2], [2, 2]], size=2000)
data = pd.DataFrame(data, columns=['x', 'y'])
for col in 'xy':
plt.hist(data[col], density=True, alpha=0.5)
import matplotlib.pyplot as plt plt.style.use('classic') %matplotlib inline import numpy as np import pandas as pd data = np.random.multivariate_normal([0, 0], [[5, 2], [2, 2]], size=2000) data = pd.DataFrame(data, columns=['x', 'y']) for col in 'xy': plt.hist(data[col], density=True, alpha=0.5)
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