Home Data Professional Services Plumbers

US 4,847 Plumbers Data: Phone, Desc, Name, Service

Name	n3_chennan_plumber_rotorooter_com
Data	45.39M (+ 0B)
Tables	11 (+ 0)
Columns	45 (+ 0)
Table Rows	306,620 (+ 0)
Media	0B (+ 0B)
Files	0 (+ 0)
Last Commit	2023-06-19 18:36:38 (+ 169 d)

This plumbers database lists 4,847 records across 50 states in America. Each plumber consists of title, phone number, description and name. In table plumber, there are 4,847 unique phone numbers. In this US plumber data set, it also contains 26 commercial services and 43 residential services.

The whole America plumbers API has 11 tables.

Data Samples

Main List (for Desktop / for Mobile) / JSON / XML / Excel / CSV (Download CSV) / View by Table

Data APIs

http://n3.datasn.io/data/api/v1/n3_chennan/us_plumber_1/ (By Table)

Tables + Columns
Media Files
Updates
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Tables & Columns

Tables	Rows	Columns	Non-empty
commercial_service	26	value	100%
filter_by	12	value	100%
plumber	4,847	title	100%
		phone	100%
		description	99.96%
		name	99.96%
plumber_x_commercial_service	96,262	plumber_id	100%
plumber_x_commercial_service	96,262	commercial_service_id	100%
plumber_x_filter_by	48,919	plumber_id	100%
plumber_x_filter_by	48,919	filter_by_id	100%
plumber_x_residential_service	137,775	plumber_id	100%
plumber_x_residential_service	137,775	residential_service_id	100%
plumber_x_time	13,836	plumber_id	100%
plumber_x_time	13,836	time_id	100%
residential_service	43	value	100%
state	50	title	100%
state_x_plumber	4,847	state_id	100%
state_x_plumber	4,847	plumber_id	100%
time	3	value	100%

Notes:

Meta columns id and ts are not shown here, but included in columns total.
Some statistical or memo columns are not shown here, but included in columns total.
Non-empty percentage indicates the percent of values that are non-empty for that particular column.

Media Sets

No media sets.

Commits / Updates

Time	Data	Tables	Columns	Rows	Media	Files
2023-06-19 (+ 169 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2023-01-01 (+ 95 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2022-09-27 (+ 271 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2021-12-30 (+ 115 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2021-09-05 (+ 150 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2021-04-08 (+ 68 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2021-01-29 (+ 120 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2020-10-01 (+ 38 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2020-08-23 (+ 141 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2020-04-04 (+ 196 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2019-09-21 (+ 197 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2019-03-07 (+ 43 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2019-01-23 (+ 44 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-12-09 (+ 29 d)	45.39M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-11-09 (+ 27 d)	45.39M (+ 9.31M)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-10-13 (+ 29 d)	36.08M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-09-13 (+ 34 d)	36.08M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-08-09 (+ 27 d)	36.08M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-07-12 (+ 31 d)	36.08M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-06-10 (+ 31 d)	36.08M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-05-10 (+ 28 d)	36.08M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-04-11 (+ 38 d)	36.08M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-03-03 (+ 35 d)	36.08M (+ 0B)	11 (+ 0)	45 (+ 0)	306,620 (+ 0)	0B (+ 0B)	0 (+ 0)
2018-01-27	36.08M	11	45	306,620	0B	0

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Why are data size increments not in line with those of number of rows?

The scanning and profiling of data size increments are done separately from those of the number of rows.