Caye Castillo PAD 6833 Research Paper Data Selection
Caye Castillo
2024-09-26
library(readxl)
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This is data represented in the Annual Enforcement Report, pursuant to Texas Water Code Section 5.126, and published each December following the end of the fiscal year. Supplemental Environmental Projects (SEPs) are environmentally beneficial projects that a respondent agrees to undertake in settlement of an enforcement action. Dollars directed to TCEQ-approved environmental projects may be used to offset assessed penalties in enforcement actions.
The data is available through the Texas Open Data Portal (https://data.texas.gov/dataset/Texas-Commission-on-Environmental-Quality-Suppleme/8j6x-idf8/about_data)
The analysis includes basic observations, missingness, measures of central tendency, normality checks, and correlation analysis.
Hope this works, Caye
data <- read.csv("Texas_Commission_on_Environmental_Quality_-_Supplemental_Environmental_Projects_20240925.csv")#Basic information on the dataset.
str(data)## 'data.frame': 1283 obs. of 29 variables:
## $ Program : chr "AIR QUALITY" "AIR QUALITY" "INDUSTRIAL AND HAZARDOUS WASTE" "WATER QUALITY" ...
## $ Case.No. : int 49255 49681 48085 47475 49644 48316 50162 49756 50129 48836 ...
## $ Customer.Name : chr "TOTALENERGIES PETROCHEMICALS & REFINING USA, INC." "THE PREMCOR REFINING GROUP INC." "J. M. HOLM & CO., INC." "CITY OF HEARNE" ...
## $ Order.Date : chr "Sep 15, 2015" "Sep 15, 2015" "Sep 15, 2015" "Sep 15, 2015" ...
## $ Penalty.Assessed: int 55000 35438 35000 40500 9453 68250 1125 4373 5000 72905 ...
## $ Penalty.Deferred: int 0 7087 7000 8100 1890 13650 225 874 1000 14581 ...
## $ Payable.Amount : int 27500 14176 14000 0 3782 0 450 0 2000 29162 ...
## $ SEP.Costs.Total : int 27500 14175 14000 32400 3781 54600 450 3499 2000 29162 ...
## $ SEP.Offset.Total: int 27500 14175 14000 32400 3781 54600 450 3499 2000 29162 ...
## $ Type.1 : chr "POLLUTION PREVENTION" "POLLUTION PREVENTION" "POLLUTION PREVENTION" "POLLUTION PREVENTION" ...
## $ SEP.Project.1 : chr "PERFORMING PARTY SHALL OPERATE, MAINTAIN, AND POTENTIALLY EXPAND THE EXISTING SOUTHEAST TEXAS REGIONAL AIR MONI"| __truncated__ "PERFORMING PARTY SHALL OPERATE, MAINTAIN, AND POTENTIALLY EXPAND THE EXISTING SOUTHEAST TEXAS REGIONAL AIR MONI"| __truncated__ "CONTRIBUTIONS WILL BE USED TO PAY FOR LABOR AND MATERIALS COSTS ASSOCIATED WITH IMPLEMENTING THE MARSH MANIA PR"| __truncated__ "PROJECT SHALL COORDINATE COLLECTION EVENTS FOR LOCAL RESIDENTS TO BRING IN HOUSEHOLD HAZARDOUS WASTE SUCH AS PA"| __truncated__ ...
## $ SEP.Cost.1 : int 27500 14175 7000 10800 1891 18200 450 3499 2000 29162 ...
## $ SEP.Offset.1 : int 27500 14175 7000 10800 1891 18200 450 3499 2000 29162 ...
## $ Type.2 : chr "" "" "POLLUTION PREVENTION" "POLLUTION PREVENTION" ...
## $ SEP.Project.2 : chr "" "" "CONTRIBUTIONS WILL BE USED IN ACCORDANCE WITH THE SUPPLEMENTAL ENVIRONMENTAL PROJECT AGREEMENT BETWEEN THE ARMA"| __truncated__ "PROJECT WILL REPAIR OR REPLACE FAILING WATER SYSTMES OR ON-SITE WASTEWATER SYSTEMS FOR LOW-INCOME HOMEOWNERS. "| __truncated__ ...
## $ SEP.Cost.2 : int NA NA 7000 10800 1890 18200 NA NA NA NA ...
## $ SEP.Offset.2 : int NA NA 7000 10800 1890 18200 NA NA NA NA ...
## $ Type.3 : chr "" "" "" "POLLUTION PREVENTION" ...
## $ SEP.Project.3 : chr "" "" "" "RC&D WILL COORDINATE WITH LOCAL CITY AND COUNTY GOVERNMENT OFFICIALS TO CLEAN-UP SITES WHERE TIRES HAVE BEEN DI"| __truncated__ ...
## $ SEP.Cost.3 : int NA NA NA 10800 NA 18200 NA NA NA NA ...
## $ SEP.Offset.3 : int NA NA NA 10800 NA 18200 NA NA NA NA ...
## $ Type.4 : logi NA NA NA NA NA NA ...
## $ SEP.Project.4 : logi NA NA NA NA NA NA ...
## $ SEP.Cost.4 : logi NA NA NA NA NA NA ...
## $ SEP.Offset.4 : logi NA NA NA NA NA NA ...
## $ Type.5 : logi NA NA NA NA NA NA ...
## $ SEP.Project.5 : logi NA NA NA NA NA NA ...
## $ SEP.Cost.5 : logi NA NA NA NA NA NA ...
## $ SEP.Offset.5 : logi NA NA NA NA NA NA ...#Checking for missing data.
sapply(data, function(x) sum(is.na(x)))## Program Case.No. Customer.Name Order.Date
## 0 0 0 0
## Penalty.Assessed Penalty.Deferred Payable.Amount SEP.Costs.Total
## 0 0 0 0
## SEP.Offset.Total Type.1 SEP.Project.1 SEP.Cost.1
## 0 0 0 0
## SEP.Offset.1 Type.2 SEP.Project.2 SEP.Cost.2
## 0 0 0 1221
## SEP.Offset.2 Type.3 SEP.Project.3 SEP.Cost.3
## 1221 0 0 1262
## SEP.Offset.3 Type.4 SEP.Project.4 SEP.Cost.4
## 1262 1283 1283 1283
## SEP.Offset.4 Type.5 SEP.Project.5 SEP.Cost.5
## 1283 1283 1283 1283
## SEP.Offset.5
## 1283#Summary of data
summary(data)## Program Case.No. Customer.Name Order.Date
## Length:1283 Min. :35088 Length:1283 Length:1283
## Class :character 1st Qu.:52372 Class :character Class :character
## Mode :character Median :55810 Mode :character Mode :character
## Mean :55611
## 3rd Qu.:58806
## Max. :63459
##
## Penalty.Assessed Penalty.Deferred Payable.Amount SEP.Costs.Total
## Min. : 157 Min. : 0 Min. : 0 Min. : 126
## 1st Qu.: 7500 1st Qu.: 0 1st Qu.: 0 1st Qu.: 4240
## Median : 16302 Median : 1635 Median : 2881 Median : 9540
## Mean : 39054 Mean : 4492 Mean : 13076 Mean : 21491
## 3rd Qu.: 38694 3rd Qu.: 4236 3rd Qu.: 10501 3rd Qu.: 22372
## Max. :2020216 Max. :211820 Max. :1010108 Max. :1010108
##
## SEP.Offset.Total Type.1 SEP.Project.1 SEP.Cost.1
## Min. : 126 Length:1283 Length:1283 Min. : 126
## 1st Qu.: 4240 Class :character Class :character 1st Qu.: 4118
## Median : 9540 Mode :character Mode :character Median : 9151
## Mean : 21499 Mean : 19431
## 3rd Qu.: 22372 3rd Qu.: 21364
## Max. :1010108 Max. :1010108
##
## SEP.Offset.1 Type.2 SEP.Project.2 SEP.Cost.2
## Min. : 126 Length:1283 Length:1283 Min. : 500
## 1st Qu.: 4118 Class :character Class :character 1st Qu.: 3960
## Median : 9225 Mode :character Mode :character Median : 10196
## Mean : 19434 Mean : 36570
## 3rd Qu.: 21364 3rd Qu.: 27469
## Max. :1010108 Max. :282519
## NA's :1221
## SEP.Offset.2 Type.3 SEP.Project.3 SEP.Cost.3
## Min. : 500 Length:1283 Length:1283 Min. : 350
## 1st Qu.: 4360 Class :character Class :character 1st Qu.: 1625
## Median : 10196 Mode :character Mode :character Median : 8000
## Mean : 36663 Mean : 17920
## 3rd Qu.: 27469 3rd Qu.: 20781
## Max. :282519 Max. :105673
## NA's :1221 NA's :1262
## SEP.Offset.3 Type.4 SEP.Project.4 SEP.Cost.4 SEP.Offset.4
## Min. : 350 Mode:logical Mode:logical Mode:logical Mode:logical
## 1st Qu.: 1625 NA's:1283 NA's:1283 NA's:1283 NA's:1283
## Median : 8000
## Mean : 17920
## 3rd Qu.: 20781
## Max. :105673
## NA's :1262
## Type.5 SEP.Project.5 SEP.Cost.5 SEP.Offset.5
## Mode:logical Mode:logical Mode:logical Mode:logical
## NA's:1283 NA's:1283 NA's:1283 NA's:1283
##
##
##
##
## #Trying to measure the normality with Histograms
hist(data$SEP.Costs.Total, main = "SEP Costs Total", xlab = "SEP Total Cost")
Something is definitely wrong with the above graph, not sure why the
Totals are coming out this way. (This has happened with multiple
datasets)
#Comparing two columns (SEPs cost 1 and 2)
cor(data$SEP.Cost.1, data$SEP.Cost.2)## [1] NA