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load_pop_growth¶
In [ ]:
load_pop_growth(
schema: str = 'public',
name: str = 'pop_growth')
Ingests the population growth dataset into the Vertica database. This dataset is ideal for time series and geospatial models. If a table with the same name and schema already exists, this function will create a vDataFrame from the input relation.
Parameters¶
Name | Type | Optional | Description |
---|---|---|---|
schema | str | ✓ | Schema of the new relation. The default schema is public. |
name | str | ✓ | Name of the new relation. |
Returns¶
vDataFrame : the pop growth vDataFrame.
Example¶
In [35]:
from verticapy.datasets import load_pop_growth
load_pop_growth()
Out[35]:
123 yearInt | Abc continentVarchar(100) | Abc countryVarchar(100) | Abc cityVarchar(100) | 123 populationFloat | 🌎 latFloat | 🌎 lonFloat | |
1 | 1500 | Asia | China | Beijing | 672.0 | 39.9075 | 116.39723 |
2 | 1500 | Asia | China | Guangzhou | 150.0 | 23.11667 | 113.25 |
3 | 1500 | Asia | China | Hangzhou | 250.0 | 30.25 | 120.16 |
4 | 1500 | Asia | China | Nanjing | 147.0 | 32.05 | 118.766667 |
5 | 1500 | Asia | India | Cuttack | 140.0 | 20.46497 | 85.87927 |
6 | 1500 | Asia | India | Gauda | 200.0 | 24.866667 | 88.133333 |
7 | 1500 | Asia | India | Vijayanagar | 500.0 | 15.335 | 76.462 |
8 | 1500 | Europe | France | Paris | 185.0 | 48.85341 | 2.3488 |
9 | 1500 | Europe | Turkey | Istanbul | 200.0 | 41.005275 | 28.9497 |
10 | 1500 | Middle East | Egypt | Cairo | 400.0 | 30.04 | 31.24 |
11 | 1500 | Middle East | Iran | Tabriz | 250.0 | 38.08 | 46.2919 |
12 | 1500 | Middle East | Morocco | Fez | 130.0 | 34.033333 | -5.01 |
13 | 1501 | Asia | China | Beijing | 672.36 | 39.9075 | 116.39723 |
14 | 1501 | Asia | China | Guangzhou | 150.2 | 23.11667 | 113.25 |
15 | 1501 | Asia | China | Hangzhou | 250.2 | 30.25 | 120.16 |
16 | 1501 | Asia | China | Nanjing | 147.000866666667 | 32.05 | 118.766667 |
17 | 1501 | Asia | India | Cuttack | 139.0 | 20.46497 | 85.87927 |
18 | 1501 | Asia | India | Gauda | 200.0 | 24.866667 | 88.133333 |
19 | 1501 | Asia | India | Vijayanagar | 499.6 | 15.335 | 76.462 |
20 | 1501 | Europe | France | Paris | 185.5 | 48.85341 | 2.3488 |
21 | 1501 | Europe | Turkey | Istanbul | 205.0 | 41.005275 | 28.9497 |
22 | 1501 | Middle East | Egypt | Cairo | 399.2 | 30.04 | 31.24 |
23 | 1501 | Middle East | Iran | Tabriz | 248.0 | 38.08 | 46.2919 |
24 | 1501 | Middle East | Morocco | Fez | 130.076923076923 | 34.033333 | -5.01 |
25 | 1502 | Asia | China | Beijing | 672.72 | 39.9075 | 116.39723 |
26 | 1502 | Asia | China | Guangzhou | 150.4 | 23.11667 | 113.25 |
27 | 1502 | Asia | China | Hangzhou | 250.4 | 30.25 | 120.16 |
28 | 1502 | Asia | China | Nanjing | 147.001733333333 | 32.05 | 118.766667 |
29 | 1502 | Asia | India | Cuttack | 138.0 | 20.46497 | 85.87927 |
30 | 1502 | Asia | India | Gauda | 200.0 | 24.866667 | 88.133333 |
31 | 1502 | Asia | India | Vijayanagar | 499.2 | 15.335 | 76.462 |
32 | 1502 | Europe | France | Paris | 186.0 | 48.85341 | 2.3488 |
33 | 1502 | Europe | Turkey | Istanbul | 210.0 | 41.005275 | 28.9497 |
34 | 1502 | Middle East | Egypt | Cairo | 398.4 | 30.04 | 31.24 |
35 | 1502 | Middle East | Iran | Tabriz | 246.0 | 38.08 | 46.2919 |
36 | 1502 | Middle East | Morocco | Fez | 130.153846153846 | 34.033333 | -5.01 |
37 | 1503 | Asia | China | Beijing | 673.08 | 39.9075 | 116.39723 |
38 | 1503 | Asia | China | Guangzhou | 150.6 | 23.11667 | 113.25 |
39 | 1503 | Asia | China | Hangzhou | 250.6 | 30.25 | 120.16 |
40 | 1503 | Asia | China | Nanjing | 147.0026 | 32.05 | 118.766667 |
41 | 1503 | Asia | India | Cuttack | 137.0 | 20.46497 | 85.87927 |
42 | 1503 | Asia | India | Gauda | 200.0 | 24.866667 | 88.133333 |
43 | 1503 | Asia | India | Vijayanagar | 498.8 | 15.335 | 76.462 |
44 | 1503 | Europe | France | Paris | 186.5 | 48.85341 | 2.3488 |
45 | 1503 | Europe | Turkey | Istanbul | 215.0 | 41.005275 | 28.9497 |
46 | 1503 | Middle East | Egypt | Cairo | 397.6 | 30.04 | 31.24 |
47 | 1503 | Middle East | Iran | Tabriz | 244.0 | 38.08 | 46.2919 |
48 | 1503 | Middle East | Morocco | Fez | 130.230769230769 | 34.033333 | -5.01 |
49 | 1504 | Asia | China | Beijing | 673.44 | 39.9075 | 116.39723 |
50 | 1504 | Asia | China | Guangzhou | 150.8 | 23.11667 | 113.25 |
51 | 1504 | Asia | China | Hangzhou | 250.8 | 30.25 | 120.16 |
52 | 1504 | Asia | China | Nanjing | 147.003466666667 | 32.05 | 118.766667 |
53 | 1504 | Asia | India | Cuttack | 136.0 | 20.46497 | 85.87927 |
54 | 1504 | Asia | India | Gauda | 200.0 | 24.866667 | 88.133333 |
55 | 1504 | Asia | India | Vijayanagar | 498.4 | 15.335 | 76.462 |
56 | 1504 | Europe | France | Paris | 187.0 | 48.85341 | 2.3488 |
57 | 1504 | Europe | Turkey | Istanbul | 220.0 | 41.005275 | 28.9497 |
58 | 1504 | Middle East | Egypt | Cairo | 396.8 | 30.04 | 31.24 |
59 | 1504 | Middle East | Iran | Tabriz | 242.0 | 38.08 | 46.2919 |
60 | 1504 | Middle East | Morocco | Fez | 130.307692307692 | 34.033333 | -5.01 |
61 | 1505 | Asia | China | Beijing | 673.8 | 39.9075 | 116.39723 |
62 | 1505 | Asia | China | Guangzhou | 151.0 | 23.11667 | 113.25 |
63 | 1505 | Asia | China | Hangzhou | 251.0 | 30.25 | 120.16 |
64 | 1505 | Asia | China | Nanjing | 147.004333333333 | 32.05 | 118.766667 |
65 | 1505 | Asia | India | Cuttack | 135.0 | 20.46497 | 85.87927 |
66 | 1505 | Asia | India | Gauda | 200.0 | 24.866667 | 88.133333 |
67 | 1505 | Asia | India | Vijayanagar | 498.0 | 15.335 | 76.462 |
68 | 1505 | Europe | France | Paris | 187.5 | 48.85341 | 2.3488 |
69 | 1505 | Europe | Turkey | Istanbul | 225.0 | 41.005275 | 28.9497 |
70 | 1505 | Middle East | Egypt | Cairo | 396.0 | 30.04 | 31.24 |
71 | 1505 | Middle East | Iran | Tabriz | 240.0 | 38.08 | 46.2919 |
72 | 1505 | Middle East | Morocco | Fez | 130.384615384615 | 34.033333 | -5.01 |
73 | 1506 | Asia | China | Beijing | 674.16 | 39.9075 | 116.39723 |
74 | 1506 | Asia | China | Guangzhou | 151.2 | 23.11667 | 113.25 |
75 | 1506 | Asia | China | Hangzhou | 251.2 | 30.25 | 120.16 |
76 | 1506 | Asia | China | Nanjing | 147.0052 | 32.05 | 118.766667 |
77 | 1506 | Asia | India | Cuttack | 134.0 | 20.46497 | 85.87927 |
78 | 1506 | Asia | India | Gauda | 200.0 | 24.866667 | 88.133333 |
79 | 1506 | Asia | India | Vijayanagar | 497.6 | 15.335 | 76.462 |
80 | 1506 | Europe | France | Paris | 188.0 | 48.85341 | 2.3488 |
81 | 1506 | Europe | Turkey | Istanbul | 230.0 | 41.005275 | 28.9497 |
82 | 1506 | Middle East | Egypt | Cairo | 395.2 | 30.04 | 31.24 |
83 | 1506 | Middle East | Iran | Tabriz | 238.0 | 38.08 | 46.2919 |
84 | 1506 | Middle East | Morocco | Fez | 130.461538461538 | 34.033333 | -5.01 |
85 | 1507 | Asia | China | Beijing | 674.52 | 39.9075 | 116.39723 |
86 | 1507 | Asia | China | Guangzhou | 151.4 | 23.11667 | 113.25 |
87 | 1507 | Asia | China | Hangzhou | 251.4 | 30.25 | 120.16 |
88 | 1507 | Asia | China | Nanjing | 147.006066666667 | 32.05 | 118.766667 |
89 | 1507 | Asia | India | Cuttack | 133.0 | 20.46497 | 85.87927 |
90 | 1507 | Asia | India | Gauda | 200.0 | 24.866667 | 88.133333 |
91 | 1507 | Asia | India | Vijayanagar | 497.2 | 15.335 | 76.462 |
92 | 1507 | Europe | France | Paris | 188.5 | 48.85341 | 2.3488 |
93 | 1507 | Europe | Turkey | Edirne | 130.64 | 41.681808 | 26.562269 |
94 | 1507 | Europe | Turkey | Istanbul | 235.0 | 41.005275 | 28.9497 |
95 | 1507 | Middle East | Egypt | Cairo | 394.4 | 30.04 | 31.24 |
96 | 1507 | Middle East | Iran | Tabriz | 236.0 | 38.08 | 46.2919 |
97 | 1508 | Asia | China | Beijing | 674.88 | 39.9075 | 116.39723 |
98 | 1508 | Asia | China | Guangzhou | 151.6 | 23.11667 | 113.25 |
99 | 1508 | Asia | China | Hangzhou | 251.6 | 30.25 | 120.16 |
100 | 1508 | Asia | China | Nanjing | 147.006933333333 | 32.05 | 118.766667 |
Rows: 1-100 | Columns: 7
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