Name: Fast Fashion Eco-Data
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Fast Fashion Eco-Data

Investigating Price, Composition, and Eco-Tagging of Zara Clothing Items

About this dataset

This dataset provides valuable insight into Zara’s commitment to environmental sustainability. Containing information on the price, composition and eco-tagging of Zara's clothing items, this data underscores the company's efforts to reduce their production's carbon footprint. From this dataset, you can learn more about the items produced by Zara and how they are incorporating eco-friendly practices into their production processes. With this knowledge, we can gain a better understanding of how businesses are becoming more conscious of their impacts on our planet and taking steps to ensure a greener future

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How to use the dataset

This dataset provides a comprehensive overview of the price, composition, and eco-tagging for Zara clothing items. Specifically, this dataset includes information about item codes, names, descriptions, joint life titles, joint life descriptions and item prices. With this data researchers can make informed decisions around how much their clothing items cost and determine how sustainable different products are based on their compositions.

The following steps provide an outline of how to use the data in this dataset:

Lay out your research objectives. What questions are you looking to answer? Whether your goal is to compare pricing between different types of items or to analyze certain trends in eco-taggings it is important to clearly state your research goals before beginning with the analysis process.

Determine which columns should be used for analysis: Each column in the dataset contains different types of information that could be used for analyses; however depending on what you want to learn from the data it may be necessary only include certain columns in your analyses. For example if we wanted to look at only item name and associated prices then we would include just those two columns leaving out all other related fields such as descrition etc.. After you have selected which columns will best allow you answer your research questions move onto step 3!

Analyze & Interpret Data: Now that you have chosen which columns within the dataset will best help answer our research quesitons its time to begin analyzing! Depending on what type or kind of analysis or visualization methods we are planning on using (data sorting/cleasing procedures etc.)will heavily depend on how much manipulation will need undertaken prior moving onto visualization updates etc.. Thus once our data exploration has wrapped up its time draw conclusions based off any patterns display relationships noted through scrutinizing differt combinations viewpoints available through utilizing visualizations and derived summaries found during our data mnipulations as documented above!

Presenting & Sharing Findings: After reaching conclusions based off studied findings share outcomes results here and if possible highlight any actions plans strategies recommended - set forth decision makers anticipate present tackle identified issues enhance practices capabilities arising from current situation context evaluataed against insight gathered noyables gleaned during train tracks projections outlines formulates traced back linked evident via outlined steps covered break down results opinion scoped debate addressed further final conclusion(s)!

Research Ideas

Comparing and analyzing the prices, compositions, and eco-tagging of Zara clothing items to determine which items are the most affordable, sustainable, and offer the best value for customers.

Using the data to create a platform highlighting more sustainable brands within fast fashion and encouraging shoppers to purchase those items instead.

Creating a predictive model that can classify clothing into different categories based on price, composition, and eco-tagging data - to help customers find specific types of clothing more quickly

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: fastFasionItemsDim.csv

File: fastFashionCompDim.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Fastfashioncompdim

@kaggle.thedevastator_fast_fashion_eco_data.fastfashioncompdim

5.74 KB
457 rows
4 columns


CREATE TABLE fastfashioncompdim (
  "item_code" BIGINT,
  "part_name" VARCHAR,
  "material" VARCHAR,
  "percent" VARCHAR
);

Fastfasionitemsdim

@kaggle.thedevastator_fast_fashion_eco_data.fastfasionitemsdim

18.51 KB
276 rows
7 columns


CREATE TABLE fastfasionitemsdim (
  "item_code" BIGINT,
  "item_name" VARCHAR,
  "item_desc" VARCHAR,
  "join_life" BOOLEAN,
  "joinlife_title" VARCHAR,
  "joinlife_desc" VARCHAR,
  "item_price" BIGINT
);