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Course Project 2 Exploratory Data Analysis

Codebook

  1. Requirements
  2. Scripts
    1. Plot 1
    2. Plot 2
    3. Plot 3
    4. Plot 4
    5. Plot 5
    6. Plot 6
  3. Output and Input Details
    1. Inputs
      1. NEI
      2. SCC
    2. Output

1. Requirements

It is necessary to install the following packages to reproduce this Course Project 2.

  1. ggplot2
  2. tidyverse
  3. magrittr
  4. cowplot

Also, those following scripts will use the standard packages from R.

  1. base
  2. graphic
  3. utils
  4. grDevices

It is mandatory to have access to the internet if you are willing to reproduce it.

2. Scripts

This Course Project 2 required the development of 6 scripts to plot and export six png files.

2.1. Description of functionality of plot1.R

  1. Create the folder data to keep all files downloaded in it;
  2. Download the zipped file (FNEI_data.zip) using download.file();
  3. If the raw data is already downloaded, the script will not download any file;
  4. Unzipping the FNEI_data.zip into the data folder;
  5. Loading the summarySCC_PM25.rds file using base::readRDS and naming it as NEI;
  6. Loading the Source_Classification_Code.rds file using base::readRDS and naming it as SCC;
  7. Summarizing the NEI dataset grouping by year and then calculating the Total emissions of PM2.5;
  8. Plotting a barplot using the base graphic system;
  9. Saving the plot as a png file;

2.2. Description of functionality of plot2.R

  1. Creating the folder data to keep all files downloaded in it;
  2. Downloading the zipped file (FNEI_data.zip) using download.file();
  3. If the raw data is already downloaded, the script will not download any file;
  4. Unzipping the FNEI_data.zip into the data folder;
  5. Loading the summarySCC_PM25.rds file using base::readRDS and naming it as NEI;
  6. Loading the Source_Classification_Code.rds file using base::readRDS and naming it as SCC;
  7. Subsetting the NEI dataset to filter only fips equal to 24510 (Baltimore City);
  8. Summarizing the previous dataset grouping by year and then calculating the Total emissions of PM2.5;
  9. Plotting a line plot using the base graphic system;
  10. Saving the plot as a png file;

2.3. Description of functionality of plot3.R

  1. Creating the folder data to keep all files downloaded in it;
  2. Downloading the zipped file (FNEI_data.zip) using download.file();
  3. If the raw data is already downloaded, the script will not download any file;
  4. Unzipping the FNEI_data.zip into the data folder;
  5. Loading the summarySCC_PM25.rds file using base::readRDS and naming it as NEI;
  6. Loading the Source_Classification_Code.rds file using base::readRDS and naming it as SCC;
  7. Subsetting the NEI dataset to filter only fips equal to 24510 (Baltimore City);
  8. Summarizing the previous dataset grouping by year and then calculating the Total emissions of PM2.5;
  9. Plotting a line plot using the ggplot2 package;
  10. Setting the aesthetic from geom_line as color = type;
  11. Saving the plot as a png file;

2.4. Description of functionality of plot4.R

  1. Creating the folder data to keep all files downloaded in it;
  2. Downloading the zipped file (FNEI_data.zip) using download.file();
  3. If the raw data is already downloaded, the script will not download any file;
  4. Unzipping the FNEI_data.zip into the data folder;
  5. Loading the summarySCC_PM25.rds file using base::readRDS and naming it as NEI;
  6. Loading the Source_Classification_Code.rds file using base::readRDS and naming it as SCC;
  7. Subsetting the SCC dataset to filter the Coal source of PM2.5 found in EI.Sector variable;
  8. Subsetting the NEI dataset to filter only the given SCC from the previous dataset;
  9. Merging both previous datasets to create a new column about EI.Sector;
  10. Summarizing the previous dataset grouping by year and EI.The sector then calculating the Total emissions of PM2.5;
  11. Plotting a stacked bar plot using the ggplot2 package;
  12. Setting the geom_bar to have position = "stack";
  13. Saving the plot as a png file;

2.5. Description of functionality of plot5.R

  1. Creating the folder data to keep all files downloaded in it;
  2. Downloading the zipped file (FNEI_data.zip) using download.file();
  3. If the raw data is already downloaded, the script will not download any file;
  4. Unzipping the FNEI_data.zip into the data folder;
  5. Loading the summarySCC_PM25.rds file using base::readRDS and naming it as NEI;
  6. Loading the Source_Classification_Code.rds file using base::readRDS and naming it as SCC;
  7. Subsetting the NEI dataset to filter only fips equal to 24510 (Baltimore City) and type equal to ON-ROAD;
  8. Summarizing the previous dataset grouping by year and then calculating the Total emissions of PM2.5;
  9. Plotting a bar plot using the ggplot2 package;
  10. Saving the plot as a png file;

2.6. Description of functionality of plot6.R

  1. Creating the folder data to keep all files downloaded in it;
  2. Downloading the zipped file (FNEI_data.zip) using download.file();
  3. If the raw data is already downloaded, the script will not download any file;
  4. Unzipping the FNEI_data.zip into the data folder;
  5. Loading the summarySCC_PM25.rds file using base::readRDS and naming it as NEI;
  6. Loading the Source_Classification_Code.rds file using base::readRDS and naming it as SCC;
  7. Subsetting the NEI dataset to filter only fips equal to 24510 or 06037 (Baltimore City and Los Angeles County) and type equal to ON-ROAD;
  8. Creating an auxiliary dataset to store the fips and city;
  9. Merging both previous datasets to create a new column about the city;
  10. Summarizing the previous dataset grouping by year and then calculating the Total emissions of PM2.5;
  11. Plotting a bar plot using the ggplot2 package;
  12. Saving the plot as a png file;

3. Output and Input Details

Here will be described some aspects of output and inputs.

3.1. Inputs

Course Project 2 will only use one zipped file, the FNEI_data.zip. It has 2 (two) .rds compressed files:

  • summarySCC_PM25.rds, and;
  • Source_Classification_Code.rds.

3.1.1. NEI

The data from summarySCC_PM25.rds is already tidy, and following the assignment instruction, I have named this object NEI.

  • Size: 732,232,328 Bytes (698.3112 Megabytes)
  • Rows: 6,497,651, and;
  • Columns: 6.

I have calculated the object size in Bytes using the object_size() from the pryr package.

The columns variables in the NEI dataset: fips, SCC, Pollutant, Emissions, type, year

Head

fips SCC Pollutant Emissions type year
4 09001 10100401 PM25-PRI 15.714 POINT 1999
8 09001 10100404 PM25-PRI 234.178 POINT 1999
12 09001 10100501 PM25-PRI 0.128 POINT 1999
16 09001 10200401 PM25-PRI 2.036 POINT 1999
20 09001 10200504 PM25-PRI 0.388 POINT 1999
24 09001 10200602 PM25-PRI 1.490 POINT 1999

Strucuture

## 'data.frame':    6497651 obs. of  6 variables:
##  $ fips     : chr  "09001" "09001" "09001" "09001" ...
##  $ SCC      : chr  "10100401" "10100404" "10100501" "10200401" ...
##  $ Pollutant: chr  "PM25-PRI" "PM25-PRI" "PM25-PRI" "PM25-PRI" ...
##  $ Emissions: num  15.714 234.178 0.128 2.036 0.388 ...
##  $ type     : chr  "POINT" "POINT" "POINT" "POINT" ...
##  $ year     : int  1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 ...

3.1.2. SCC

The data from Source_Classification_Code.rds is already tidy. Following the assignment instruction, I have named this object SCC.

  • Size: 3,983,496 Bytes (3.798958 Megabytes)
  • Rows: 11,717, and;
  • Columns: 15.

I have calculated the object size in Bytes using the object_size() from the pryr package.

The columns variables in the SCC dataset: SCC, Data.Category, Short.Name, EI.Sector, Option.Group, Option.Set, SCC.Level.One, SCC.Level.Two, SCC.Level.Three, SCC.Level.Four, Map.To, Last.Inventory.Year, Created_Date, Revised_Date, Usage.Notes

Head

SCC Data.Category Short.Name EI.Sector Option.Group Option.Set SCC.Level.One SCC.Level.Two SCC.Level.Three SCC.Level.Four Map.To Last.Inventory.Year Created_Date Revised_Date Usage.Notes
10100101 Point Ext Comb /Electric Gen /Anthracite Coal /Pulverized Coal Fuel Comb - Electric Generation - Coal External Combustion Boilers Electric Generation Anthracite Coal Pulverized Coal NA NA
10100102 Point Ext Comb /Electric Gen /Anthracite Coal /Traveling Grate (Overfeed) Stoker Fuel Comb - Electric Generation - Coal External Combustion Boilers Electric Generation Anthracite Coal Traveling Grate (Overfeed) Stoker NA NA
10100201 Point Ext Comb /Electric Gen /Bituminous Coal /Pulverized Coal: Wet Bottom Fuel Comb - Electric Generation - Coal External Combustion Boilers Electric Generation Bituminous/Subbituminous Coal Pulverized Coal: Wet Bottom (Bituminous Coal) NA NA
10100202 Point Ext Comb /Electric Gen /Bituminous Coal /Pulverized Coal: Dry Bottom Fuel Comb - Electric Generation - Coal External Combustion Boilers Electric Generation Bituminous/Subbituminous Coal Pulverized Coal: Dry Bottom (Bituminous Coal) NA NA
10100203 Point Ext Comb /Electric Gen /Bituminous Coal /Cyclone Furnace Fuel Comb - Electric Generation - Coal External Combustion Boilers Electric Generation Bituminous/Subbituminous Coal Cyclone Furnace (Bituminous Coal) NA NA
10100204 Point Ext Comb /Electric Gen /Bituminous Coal /Spreader Stoker Fuel Comb - Electric Generation - Coal External Combustion Boilers Electric Generation Bituminous/Subbituminous Coal Spreader Stoker (Bituminous Coal) NA NA

Strucuture

## 'data.frame':    11717 obs. of  15 variables:
##  $ SCC                : Factor w/ 11717 levels "10100101","10100102",..: 1 2 3 4 5 6 7 8 9 10 ...
##  $ Data.Category      : Factor w/ 6 levels "Biogenic","Event",..: 6 6 6 6 6 6 6 6 6 6 ...
##  $ Short.Name         : Factor w/ 11238 levels "","2,4-D Salts and Esters Prod /Process Vents, 2,4-D Recovery: Filtration",..: 3283 3284 3293 3291 3290 3294 3295 3296 3292 3289 ...
##  $ EI.Sector          : Factor w/ 59 levels "Agriculture - Crops & Livestock Dust",..: 18 18 18 18 18 18 18 18 18 18 ...
##  $ Option.Group       : Factor w/ 25 levels "","C/I Kerosene",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ Option.Set         : Factor w/ 18 levels "","A","B","B1A",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ SCC.Level.One      : Factor w/ 17 levels "Brick Kilns",..: 3 3 3 3 3 3 3 3 3 3 ...
##  $ SCC.Level.Two      : Factor w/ 146 levels "","Agricultural Chemicals Production",..: 32 32 32 32 32 32 32 32 32 32 ...
##  $ SCC.Level.Three    : Factor w/ 1061 levels "","100% Biosolids (e.g., sewage sludge, manure, mixtures of these matls)",..: 88 88 156 156 156 156 156 156 156 156 ...
##  $ SCC.Level.Four     : Factor w/ 6084 levels "","(NH4)2 SO4 Acid Bath System and Evaporator",..: 4455 5583 4466 4458 1341 5246 5584 5983 4461 776 ...
##  $ Map.To             : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ Last.Inventory.Year: int  NA NA NA NA NA NA NA NA NA NA ...
##  $ Created_Date       : Factor w/ 57 levels "","1/27/2000 0:00:00",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ Revised_Date       : Factor w/ 44 levels "","1/27/2000 0:00:00",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ Usage.Notes        : Factor w/ 21 levels ""," ","includes bleaching towers, washer hoods, filtrate tanks, vacuum pump exhausts",..: 1 1 1 1 1 1 1 1 1 1 ...

3.2. Output

The results of this assignment are 6 (six) files .R and 6 (six) files png.

EI.Sector

There are 59 types of EI.Sector:

##  [1] Fuel Comb - Electric Generation - Coal            
##  [2] Fuel Comb - Electric Generation - Oil             
##  [3] Fuel Comb - Electric Generation - Natural Gas     
##  [4] Fuel Comb - Electric Generation - Other           
##  [5] Fuel Comb - Electric Generation - Biomass         
##  [6] Fuel Comb - Industrial Boilers, ICEs - Coal       
##  [7] Fuel Comb - Industrial Boilers, ICEs - Oil        
##  [8] Fuel Comb - Industrial Boilers, ICEs - Natural Gas
##  [9] Fuel Comb - Industrial Boilers, ICEs - Other      
## [10] Fuel Comb - Industrial Boilers, ICEs - Biomass    
## [11] Fuel Comb - Comm/Institutional - Coal             
## [12] Fuel Comb - Comm/Institutional - Oil              
## [13] Fuel Comb - Comm/Institutional - Natural Gas      
## [14] Fuel Comb - Comm/Institutional - Other            
## [15] Fuel Comb - Comm/Institutional - Biomass          
## [16] Industrial Processes - NEC                        
## [17] Fuel Comb - Residential - Other                   
## [18] Fuel Comb - Residential - Oil                     
## [19] Fuel Comb - Residential - Natural Gas             
## [20] Fuel Comb - Residential - Wood                    
## [21] Mobile - On-Road Gasoline Light Duty Vehicles     
## [22] Mobile - On-Road Gasoline Heavy Duty Vehicles     
## [23] Mobile - On-Road Diesel Light Duty Vehicles       
## [24] Mobile - On-Road Diesel Heavy Duty Vehicles       
## [25] Mobile - Non-Road Equipment - Gasoline            
## [26] Mobile - Non-Road Equipment - Other               
## [27] Mobile - Non-Road Equipment - Diesel              
## [28] Mobile - Aircraft                                 
## [29] Mobile - Commercial Marine Vessels                
## [30] Mobile - Locomotives                              
## [31] Dust - Paved Road Dust                            
## [32] Dust - Unpaved Road Dust                          
## [33] Industrial Processes - Chemical Manuf             
## [34] Commercial Cooking                                
## [35] Industrial Processes - Non-ferrous Metals         
## [36] Industrial Processes - Ferrous Metals             
## [37] Industrial Processes - Petroleum Refineries       
## [38] Industrial Processes - Oil & Gas Production       
## [39] Dust - Construction Dust                          
## [40] Industrial Processes - Mining                     
## [41] Solvent - Non-Industrial Surface Coating          
## [42] Solvent - Industrial Surface Coating & Solvent Use
## [43] Solvent - Degreasing                              
## [44] Solvent - Dry Cleaning                            
## [45] Solvent - Graphic Arts                            
## [46] Solvent - Consumer & Commercial Solvent Use       
## [47] Industrial Processes - Storage and Transfer       
## [48] Miscellaneous Non-Industrial NEC                  
## [49] Bulk Gasoline Terminals                           
## [50] Gas Stations                                      
## [51] Waste Disposal                                    
## [52] Agriculture - Livestock Waste                     
## [53] Agriculture - Crops & Livestock Dust              
## [54] Fires - Agricultural Field Burning                
## [55] Agriculture - Fertilizer Application              
## [56] Fires - Wildfires                                 
## [57] Fires - Prescribed Fires                          
## [58] Industrial Processes - Cement Manuf               
## [59] Industrial Processes - Pulp & Paper               
## 59 Levels: Agriculture - Crops & Livestock Dust ...

The EI.Sector related to Coal:

## [1] Fuel Comb - Electric Generation - Coal     
## [2] Fuel Comb - Industrial Boilers, ICEs - Coal
## [3] Fuel Comb - Comm/Institutional - Coal      
## 59 Levels: Agriculture - Crops & Livestock Dust ...