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Construction Spending Python Library

From the CORGIS Dataset Project

By Austin Cory Bart acbart@vt.edu
Version 2.0.0, created 3/20/2016
Tags: construction, spending, us, united states, america, government, buildings, residential, non-residential, private, public

Overview

The Value of Construction Put in Place Survey (VIP) provides monthly estimates of the total dollar value of construction work done in the U.S. The United States Code, Title 13, authorizes this program. The survey covers construction work done each month on new structures or improvements to existing structures for private and public sectors. Data estimates include the cost of labor and materials, cost of architectural and engineering work, overhead costs, interest and taxes paid during construction, and contractor’s profits. Data collection and estimation activities begin on the first day after the reference month and continue for about three weeks. Reported data and estimates are for activity taking place during the previous calendar month. The survey has been conducted monthly since 1964.

Why isn’t the ‘total construction’ the sum of the other categories? It is! the trick is that the ‘residential’ and “nonresidential” categories are supposed to be below the ‘total construction’ level, and the other categories are below those two categories. This example of the data should make it more clear: http://www.census.gov/construction/c30/pdf/tot.pdf.

More information about the nature of the construction projects is also available.

http://www.census.gov/construction/c30/c30index.html

Explore Structure

Each row represents $MISSING_FIELD.

Index Type Example Value
0 dict { }
1 dict (same structure)
2 dict (same structure)
... ... ...
Key Type Example Value Description
"time" dict { }
"annual" dict { }
"current" dict { }
Key Type Example Value Description
"index" int 1 $MISSING_FIELD
"month" int 1 $MISSING_FIELD
"month name" str "Jan" $MISSING_FIELD
"period" str "Jan2002" $MISSING_FIELD
"year" int 2002 $MISSING_FIELD
Key Type Example Value Description
"combined" dict { }
"private" dict { }
"public" dict { }
Key Type Example Value Description
"amusement and recreation" int 17866 $MISSING_FIELD
"commercial" int 68254 $MISSING_FIELD
"communication" int 18873 $MISSING_FIELD
"conservation and development" int 3603 $MISSING_FIELD
"educational" int 72357 $MISSING_FIELD
"health care" int 25746 $MISSING_FIELD
"highway and street" int 62723 $MISSING_FIELD
"lodging" int 11862 $MISSING_FIELD
"manufacturing" int 28318 $MISSING_FIELD
"nonresidential" int 475704 $MISSING_FIELD
"office" int 49140 $MISSING_FIELD
"power" int 46050 $MISSING_FIELD
"public safety" int 8468 $MISSING_FIELD
"religious" int 8745 $MISSING_FIELD
"residential" int 382979 $MISSING_FIELD
"sewage and waste disposal" int 16392 $MISSING_FIELD
"total construction" int 858654 $MISSING_FIELD
"transportation" int 25547 $MISSING_FIELD
"water supply" int 11760 $MISSING_FIELD
Key Type Example Value Description
"amusement and recreation" int 7822 $MISSING_FIELD
"commercial" int 63972 $MISSING_FIELD
"communication" int 18843 $MISSING_FIELD
"conservation and development" int 0 $MISSING_FIELD
"educational" int 13616 $MISSING_FIELD
"health care" int 20888 $MISSING_FIELD
"highway and street" int 0 $MISSING_FIELD
"lodging" int 11669 $MISSING_FIELD
"manufacturing" int 28116 $MISSING_FIELD
"nonresidential" int 263731 $MISSING_FIELD
"office" int 40176 $MISSING_FIELD
"power" int 42407 $MISSING_FIELD
"public safety" int 0 $MISSING_FIELD
"religious" int 8742 $MISSING_FIELD
"residential" int 377631 $MISSING_FIELD
"sewage and waste disposal" int 0 $MISSING_FIELD
"total construction" int 641333 $MISSING_FIELD
"transportation" int 6512 $MISSING_FIELD
"water supply" int 0 $MISSING_FIELD
Key Type Example Value Description
"amusement and recreation" int 10044 $MISSING_FIELD
"commercial" int 4282 $MISSING_FIELD
"communication" int 0 $MISSING_FIELD
"conservation and development" int 3578 $MISSING_FIELD
"educational" int 58742 $MISSING_FIELD
"health care" int 4859 $MISSING_FIELD
"highway and street" int 62553 $MISSING_FIELD
"lodging" int 0 $MISSING_FIELD
"manufacturing" int 0 $MISSING_FIELD
"nonresidential" int 211973 $MISSING_FIELD
"office" int 8964 $MISSING_FIELD
"power" int 3643 $MISSING_FIELD
"public safety" int 8356 $MISSING_FIELD
"religious" int 0 $MISSING_FIELD
"residential" int 5348 $MISSING_FIELD
"sewage and waste disposal" int 16077 $MISSING_FIELD
"total construction" int 217321 $MISSING_FIELD
"transportation" int 19035 $MISSING_FIELD
"water supply" int 11412 $MISSING_FIELD
Key Type Example Value Description
"combined" dict { }
"private" dict { }
"public" dict { }
Key Type Example Value Description
"amusement and recreation" int 1328 $MISSING_FIELD
"commercial" int 4887 $MISSING_FIELD
"communication" int 1416 $MISSING_FIELD
"conservation and development" int 271 $MISSING_FIELD
"educational" int 5125 $MISSING_FIELD
"health care" int 2013 $MISSING_FIELD
"highway and street" int 3180 $MISSING_FIELD
"lodging" int 989 $MISSING_FIELD
"manufacturing" int 2134 $MISSING_FIELD
"nonresidential" int 33545 $MISSING_FIELD
"office" int 3763 $MISSING_FIELD
"power" int 3402 $MISSING_FIELD
"public safety" int 647 $MISSING_FIELD
"religious" int 667 $MISSING_FIELD
"residential" int 25972 $MISSING_FIELD
"sewage and waste disposal" int 1150 $MISSING_FIELD
"total construction" int 59516 $MISSING_FIELD
"transportation" int 1729 $MISSING_FIELD
"water supply" int 846 $MISSING_FIELD
Key Type Example Value Description
"amusement and recreation" int 609 $MISSING_FIELD
"commercial" int 4588 $MISSING_FIELD
"communication" int 1414 $MISSING_FIELD
"conservation and development" int 0 $MISSING_FIELD
"educational" int 1000 $MISSING_FIELD
"health care" int 1629 $MISSING_FIELD
"highway and street" int 0 $MISSING_FIELD
"lodging" int 972 $MISSING_FIELD
"manufacturing" int 2117 $MISSING_FIELD
"nonresidential" int 19701 $MISSING_FIELD
"office" int 3066 $MISSING_FIELD
"power" int 3129 $MISSING_FIELD
"public safety" int 0 $MISSING_FIELD
"religious" int 667 $MISSING_FIELD
"residential" int 25572 $MISSING_FIELD
"sewage and waste disposal" int 0 $MISSING_FIELD
"total construction" int 45273 $MISSING_FIELD
"transportation" int 444 $MISSING_FIELD
"water supply" int 0 $MISSING_FIELD
Key Type Example Value Description
"amusement and recreation" int 719 $MISSING_FIELD
"commercial" int 299 $MISSING_FIELD
"communication" int 0 $MISSING_FIELD
"conservation and development" int 268 $MISSING_FIELD
"educational" int 4126 $MISSING_FIELD
"health care" int 384 $MISSING_FIELD
"highway and street" int 3168 $MISSING_FIELD
"lodging" int 0 $MISSING_FIELD
"manufacturing" int 0 $MISSING_FIELD
"nonresidential" int 13844 $MISSING_FIELD
"office" int 697 $MISSING_FIELD
"power" int 273 $MISSING_FIELD
"public safety" int 637 $MISSING_FIELD
"religious" int 0 $MISSING_FIELD
"residential" int 400 $MISSING_FIELD
"sewage and waste disposal" int 1127 $MISSING_FIELD
"total construction" int 14243 $MISSING_FIELD
"transportation" int 1285 $MISSING_FIELD
"water supply" int 826 $MISSING_FIELD

Downloads

Download all of the following files.

  1. construction_spending.py
  2. construction_spending.data

Usage

import construction_spending
spending = construction_spending.get_spending()

Documentation

get_spending()
Returns a list of dictionaries representing spending.