Data Visualization and Communication Project 

Topic – Visualization “Over 100 Years of U.S. Oil Production” 

BRIEF DESCRIPTION OF THE PROJECT: 

The data set provides information on the annual production of crude oil in the United States from 1900 to 2020. It includes data on the total amount of crude oil produced in barrels per day, as well as information on the top-producing states and fields. This data set can be used to analyze trends in U.S. oil production over time and to understand the historical context of the country's oil industry. It is often used by researchers, policymakers, and industry professionals in the energy sector.

 OBJECTIVES:

 1) Development of models and forecasts of future U.S. oil production based on historical data, to inform decision-making related to energy policy, investment, and business strategy. 

2) Provide an accurate and comprehensive source of information on U.S. crude oil production over a long period of time, which can be used to identify trends and patterns, as well as potential drivers of production.

 3) Support the development of new technologies and strategies to increase U.S. crude oil production and improve energy security. 

METHODOLOGY: 

The methodology used in the project includes data collection, data processing, exploratory data analysis, statistical analysis, and data visualization using the R programming language and required packages. The types of visualizations used include –Scatter plots, Histograms, bar plot, Stacked bar plots, Bar charts, stacked bar charts, Box plots, and density curves.

 DATA SET: The name of the data set is “Over 100 Years of U.S. Oil Production”. 

TIME PERIOD: The time period duration of the data is from 02/1920 to 02/2022. The frequency of the data set is monthly.

 SOURCE: 

https://www.kaggle.com/datasets/jordancarlen/100-years-oil-production 

```{r}

# load necessary library

library(ggplot2)

# read in the data from the csv file

data <- read.csv("C:/Users/nived/Desktop/crudeOil.csv")

```

1. SCATTER PLOT

{r}

# Create a scatter plot using ggplot2

ggplot(data, aes(x = Month, y = Oil_tbpd)) +

  geom_point() +

  labs(title = "Oil Production over Time", x = "Month", y = "Oil (thousand barrels per day)")

2. HISTOGRAM

{r}

# Create a histogram of the Oil_tbpd column using the hist() function

hist(data$Oil_tbpd, main = "Oil_tbpd Distribution", xlab = "Oil_tbpd", ylab = "Frequency")

3. STACKED BAR PLOT

# create a stacked bar plot

ggplot(data, aes(x = Month, y = Oil_tbpd, fill = Month)) +

  geom_bar(stat = "identity") +

  labs(x = "Month", y = "Oil_tbpd", title = "Monthly Oil Production") +

  theme_classic()

4. BAR CHART

{r}

# Create a bar chart using ggplot2

ggplot(data, aes(x = Month, y = Oil_tbpd)) +

  geom_bar(stat = "identity", fill = "blue") +

  labs(title = "Oil Production over Time", x = "Month", y = "Oil (thousand barrels per day)")

5. LINE CHART

{r}

# Create a line chart using ggplot2

ggplot(data, aes(x = Month, y = Oil_tbpd)) +

  geom_line() +

  labs(x = "Month", y = "Oil (tbpd)", title = "Oil Production over Time")

6. BOX PLOT

{r}

# Plot the boxplot

boxplot(data$Oil_tbpd ~ data$Month, 

        xlab = "Month", 

        ylab = "Oil (tbpd)", 

        main = "Boxplot of Oil Production by Month")

7. DENSITY CURVE

```{r}

# Plot the density curve

plot(density(data$Oil_tbpd), 

     main = "Density Curve of Oil Production",

     xlab = "Oil (tbpd)", 

     ylab = "Density", 

     col = "blue")

```

This blog is part of the assignments submitted for the course - Data Visualization and Communication, one of the Business analytics courses offered in Amrita School of Business, Coimbatore.

Submitted by,

Mr. Nived Devadas,

CB.BU.P2MBA21083,

6th trimester, MBA,

Amrita School of Business,

Amrita Vishwa Vidyapeetham University,

Coimbatore campus.