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  "fetched_at": "2026-10-20T07:32:26Z",
  "source_url": "https://www.kaggle.com/competitions/egg-sales-predict-challenge-23sl/data",
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      "name": "data-description",
      "content": "This dataset provides a detailed look into the sales of eggs in a shop in Sri Lanka over a span of 30 years, capturing seasonal variations, cultural events, and even global incidents. Dive in to uncover patterns and predict future sales.\n\nParticipants should be able to answer these types of questions after reading the data description:\n\nWhat files do I need?\nWhat should I expect the data format to be?\nWhat am I predicting?\nWhat acronyms will I encounter?\n\nFiles\ntrain.csv - The training dataset containing egg sales data from 1993 to the end of 2021.\ntest.csv - The test dataset with dates for the year 2022. You will make sales predictions for these dates.\nsample_submission.csv - A sample submission file in the correct format, illustrating how to structure your predictions.\nmetaData.csv - Supplemental information about the dataset columns and any specific notes.\nColumns\nDate - Represents the date for which the sales data is recorded. It spans from the year 1993 to 2022.\nEgg Sales (only in train.csv) - The number of eggs sold on the corresponding date. This is the target variable you'll be predicting for the test dataset.\n\n* Update - Please note that while some of you figured out the correct columns of the submission format, Some had confusion. I have made the necessary adjustment and also added an updated submission column with corrected column names.\n",
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      "name": "Description",
      "content": "Dive into the world of time series forecasting with the Egg Sales Forecasting Challenge! This competition provides a rich dataset detailing 30 years of egg sales from a Sri Lankan shop. As participants, you'll uncover the nuances of seasonal fluctuations influenced by cultural festivities, global events, and even unexpected lockdowns. Beyond just raw numbers, this dataset tells a story of traditions, market dynamics, and the resilience of businesses. Your mission? Harness this wealth of information to predict the egg sales for 2022. Whether you're a newbie in forecasting or a seasoned data scientist, this challenge offers a unique opportunity to hone your skills\nYour task is to build a machine learning model that can predict future egg sales based on the provided historical data. Whether you're a beginner just starting out with time series forecasting or an expert looking to test new algorithms, this challenge is for you!",
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      "name": "Evaluation",
      "content": "Submissions will be evaluated using the Root Mean Squared Error (RMSE) between your predicted and the actual egg sales for 2022.\n\nSubmission Format:\nYour submission should be a CSV file with two columns:\n\nDate: The date for which the prediction is made (covering all dates in 2022).\nEgg Sales Prediction: Your predicted number of eggs sold on that date.\nEnsure your predictions are in the same chronological order as the dates of 2022, starting from January 1st to December 31st. Any deviation from this format might result in submission errors.",
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      "name": "rules",
      "content": "\n\n1. Data Usage: Use only the provided dataset for training your models. External data or using data after 2021 for training is prohibited.\n  \n2. Submission Limit: Participants are allowed a maximum of two submissions per day. Ensure your submissions adhere to the format specified in `sample_submission.csv`.\n  \n3. Collaboration: Team collaborations are allowed, with a maximum of four members in a team. Merging teams during the competition is not permitted.\n  \n4. Public Code Sharing: Upon conclusion of the competition, the top 5 winners must share their code and approach in the competition discussion forum to be eligible for any accolades.\n\n",
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    {
      "name": "abstract",
      "content": "Unearth the Patterns of Egg Sales!\n\nEggs, a staple in many diets worldwide, have a sales pattern that's influenced by a myriad of factors - cultural events, global happenings, seasonal shifts, and more. In this challenge, we invite you to dive deep into 30 years of egg sales data from a shop in Sri Lanka.\n\nWhile the dataset might seem simple, it encapsulates various intricacies. From the bustling sales during Sinhala & Tamil New Year to the calm of Wesak and the unforeseen global events like lockdowns - every year tells a story. Your mission, should you choose to accept, is to forecast the egg sales for the year 2022.\n\nWhether you're a time series novice eager to learn the ropes or a seasoned expert aiming to refine your techniques, this dataset offers a unique playground. Harness the data, experiment with models, and uncover the hidden rhythms of egg sales!\n\n\n\n",
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    {
      "name": "Acknowledgments",
      "content": "\nWe'd like to thank the shop owner in Sri Lanka for providing this dataset and allowing us to use it for educational purposes.\n\n",
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