Analysis of ‘Craft Beers Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/nickhould/craft-cans on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

It's a great time to be a craft beer fan in the U.S.! There are a ton of beer styles and brands to choose from and breweries have become very successful in the last several years. Breweries owe it all to beer lovers around the world! This dataset contains a list of 2,410 US craft beers and 510 US breweries. The beers and breweries are linked together by the "id". This data was collected in January 2017 from CraftCans.com. The dataset is an a tidy format and values have been cleaned up for your enjoyment.

Content

beers.csv - Contains data on 2000+ craft canned beers

breweries.csv - Contains data for 500+ breweries in the United States

Acknowledgements

If you are interested in learning more about how this dataset was acquired, I wrote an extensive blogpost about it http://www.jeannicholashould.com/python-web-scraping-tutorial-for-craft-beers.html.

Inspiration

Can you predict the beer type from the characteristics provided in the dataset?

What is the most popular beer in North Dakota?

Enjoy!

--- Original source retains full ownership of the source dataset ---

Small breweries have been growing in number and volume share in the US marketplace. Brewing is water- and energy-intensive, especially for small brewers who do not benefit from the same economies of scale as large brewers. A systematic approach to characterizing the water and energy flows in small breweries will help researchers and process owners identify opportunities for efficiency improvement by reducing waste. The information from such analysis yields granular information about where water and energy (electrical and thermal) are embedded into beer. It also contextualizes a small brewery's specific water and energy consumption relative to peer breweries, providing a quantitative basis for decision-making that ultimately impacts economic competitiveness. In the present work, a case study is performed on a microbrewery in northern California. Visualization tools are provided that delineate how water and energy flow through the brewery. Specific electrical energy consumption was 183.7 MJ per US beer barrel (bbl) (1.6 MJ/L) packaged in the first half of 2018, thermal energy 489.4 MJ/bbl (4.2 MJ/L), water 12.8 bbl consumed/bbl (12.8 L/L), and wastewater 10.8 bbl discharged/bbl (10.8 L/L). These specific resource consumptions are placed into context relative to other small breweries. The metrics are high due to general inefficiency relative to peer facilities, reverse economies of scale in small breweries, and associated utility costs impacted by geographic location. Overall utility costs were $26.95 per bbl packaged vs. $16.01 for similar-sized breweries. This analysis sheds light on the virtuous cycle of how reducing one input in the beer-water-energy nexus will often lead to other resources being conserved as well, due to the overlapping nature of their embedment in the final product.

Complete list of all 50 Brass Tap Craft Beer Bar store POI locations in the the USA with name, geo-coded address, city, email, phone number etc for download in CSV format or via the API.

Result of the yearly tasting of x-mas beer tasting.

The event took place at Underåsgatan in Gothenburg, Sweden 2018-12-09.

Following variable in the dataset:

• Name - name of the beer
• Brewery - producer of the beer
• Origin - area/country of origin
• Alc - percentage of alcohol (by volume)
• Volume (ml) - Volume in the bottle in milliliter
• Price - price in SEK (Swedish enkrona)
• Opening time - the time of the opening of the bottle
• Grade - average grade in the tasting (0-10)

This version have errors in the delimiter in the CSV-file, use version 1.1

Parsed data from WikiliQ website. Data is presented as-is. It wasn't cleaned, nor modified in any way.

There are three CSV files, containing information about wine, beer and liquors (Including whiskey, beer, vodka, liquors and spirits)

Common columns between these 3 files: Name (of the product), Brand, Country, Categories (Type of beer/wine/liquor) ABV (Alcohol by volume) Suggested Serving Temperature (in Fahrenheit) Rating (Scale 0 to 5) Rate count (Amount of reviews, the rating is based on) Price (Sometimes might be incorrect, be careful) Volume (Volume, the price is set for) Description of a product

There are additional columns in every file, but names speak for themselves.

CO2 enrichment is a strategy commonly employed by indoor/vertical farms to improve crop yields. Artificially elevating the CO2 concentration within an enclosed growth space results in improved photosynthetic efficiency, and therefore improved crop growth rates and flavor profiles. Alcohol fermentation provides a steady stream of CO2 that is emitted to the atmosphere as a by-product. To evaluate the feasibility of using fermentation off-gas as a source for indoor carbon dioxide (CO2) enrichment, spinach plants were randomly assigned to 2 growth chambers. The control chamber was maintained under ambient CO2 concentrations, while the treatment chamber was piped onto a flow control system capable of delivering CO2 from a beer fermentation vessel to the growth chamber to maintain CO2 levels at a setpoint of 1200 parts-per-million (ppm). CO2 flow was diverted to the growth chamber when levels were below 1200 ppm, and to an external exhaust when chamber levels were above 1200 ppm, with the flo..., The dataset wass collected by harvesting plants and evaluating them for fresh weight, dry weight, and longest leaf+stem, , # Controlled Carbon Dioxide Enrichment Using Beer Fermentation Off-Gas Results in 89% Spinach Yield Increase

https://doi.org/10.5061/dryad.15dv41p6f

Description of the data and file structure

8 plants were grown in each of 2 chambers (Control, and Treatment). The "Treatment" chamber was CO2 enriched using fermentation off-gas. One of the 8 control chamber plants was stunted, and therefore removed from analysis to prevent it from positively biasing the effect of the treatment relative to the control. The removed plant is identified in the data file. Total above ground biomass was harvested and weighed. The longest stem/leaf length was then taken, and finally, plants were dried and weighed for dry weight.Â

Files and variables

File: Raw_Data.csv

Description:Â Raw fresh weight, dry weight, and stem/leaf length data

Variables

• Control: 8 plants (7 used for analysis) grown under ambient air conditions
• Treatment: 8 plan...