Data Work Sample

Introduction

Welcome to my professional portfolio. Here, I present a curated collection of data analysis and visualization projects, executed with proficiency in R and Python.

Visualization with R

The data source is Kaggle. Visualization created with R

temperature_data <- read.csv("/Users/apriasihpriyono/PycharmProjects/pythonProject/Average Temperature 1900-2023.csv")
# Load necessary library
library(ggplot2)
library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

# Ensure 'Year' is a factor and has levels in the order of appearance to maintain chronological order
temperature_data$Year <- factor(temperature_data$Year, levels = unique(temperature_data$Year))

# Plotting the data
p <- ggplot(temperature_data, aes(x=Year, y=Average_Fahrenheit_Temperature, fill=Average_Fahrenheit_Temperature)) +
    geom_bar(stat="identity", color="black") +
    scale_fill_gradient(low="blue", high="red") +
    labs(title="Annual Average Temperature",
         x="Year",
         y="Average Temperature (°F)") +
    theme_minimal() +
    theme(axis.text.x =element_text(size=5, angle=90, hjust=1))

ggplotly(p, tooltip = c("x", "y"))  # Tooltips will show year, temperature, and color scale value