📊 salesToolkit

Sales Time Series Analysis Toolkit in R

A professional R package for loading, cleaning, analyzing, visualizing, and forecasting retail sales time series data.

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🚀 Project Overview

salesToolkit is an R package designed for internal analytics teams in retail companies.
It transforms raw sales data into actionable business insights using time series analysis and forecasting methods.

The package supports:

• Data ingestion and validation
• Data cleaning and preprocessing
• Business KPI computation
• Time series visualization
• Forecasting using ARIMA and Prophet
• Automated management summaries

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📦 Installation

install.packages(\"devtools\")

devtools::install_github(\"oliwiacode/library_project\")

⚙️ Usage

📥 Load data

Option 1 — file in project folder

data <- load_sales_data("train.csv")

Option 2 — full path

data <- load_sales_data("C:/Users/Admin/Documents/salesToolkit/train.csv")

🔍 Data validation

validated <- validate_sales_ts(data)

🧹 Data cleaning

Note: this step uses dplyr internally (already included in Imports)

cleaned <- clean_sales_ts(data)

📊 Business metrics

metrics <- compute_sales_metrics(cleaned)
metrics

📈 Visualization

plot_sales_trends(cleaned)

📋 Management summary

summary <- create_management_summary(cleaned)
summary

🔮 Forecasting

forecast <- create_prognosis(cleaned)
forecast

🧠 Notes

• Forecasting may take longer to compute due to ARIMA and Prophet models
• Large datasets (3M+ rows) may require additional processing time
• All functions are designed for retail time series analysis workflows

🧪 Data Source

• Store Sales Time Series Forecasting (Kaggle)
  https://www.kaggle.com/competitions/store-sales-time-series-forecasting

• Dataset is not included due to size limitations.