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Where Large CSV Files are Available and Where They Are Used

A CSV file is a well-known and widely used text format for data exchange. CSV formats are best used to represent sets or sequences of records in which each record has an identical list of fields. Now because CSV is versatile, the CSV file format is supported by many software applications. Using a structure similar to that of a spreadsheet, also allows users to present information in a way that is easy to understand and share across applications including relational database management systems.

Let's consider a scenario where you are working on some machine learning application or you want some sample data for data analysis which requires some large CSV files. What to do in this situation?

At the beginning of this year, Google had launched the dataset search tool similar to regular Google search. This dataset search tool helps you to locate and provides access to publicly available data sets. It has more than 25 million data sources from repositories across the web like from government data to consumer sales data and many more. For example, if I search NFL football or player states then you will get the result something like the image given here.

Large CSV

You can further filter your result sets, for example, I want the results only in text or documents, etc. If I scroll down then you can see the different sources from which you can get the NFL player stats. Again if I select this (Kaggle) one then you can see the detailed information of this data set. Here are the last updated date and the author of this data set.

When you click on this (Explore at Kaggle) link you will be redirected to the source of the data set. In this case, it is Kaggle and if I scroll down then you can see the different types of CSV files related to NFL. If I select the (Game_Logs_Defensive_Line) file then you can see the size and statistics of the file which you will get in the CSV file. This CSV file contains 5263 unique values of player id and same way for player name and from this link, you can download this CSV file.

Large CSV File

When you click on the download option, it will ask you to login but you can select the last option Skip, and continue the download. It will ask to save the file, so in the same way, you can also refer to the other data sources which are listed over here. This Google datasets tool searches for all the data sets that are available in the market.

What are the other places where you can find a large data set in case you are associated with some domains like data science, data mining, AI, or machine learning related stuff? You can find one interesting article on the ByteScout website. Open that article, big data set providers are now growing exponentially every day.

In this article, the ByteScout team has done a very fantastic job to evaluate a variety of data sets and big data providers ideal for machine learning and data mining research projects. You will likewise see a code sample in python which shows how to use one of the most popular big data hosts.

Edit Large CSV

Here is the top 50 big data provider list, if you dig deeper into this article you can see one remarkable data set from each provider. Keep in mind that most of these providers host thousands of data sets. All of the items which you can see here are currently maintained and updated. Scroll up if I click on this Kaggle link then you can see this brief introduction of the OpenAQ data set. It means if you are interested in global air pollution measurement or climate change forecasting then this OpenAQ data set is for you.

If I open the Kaggle website which we have already seen earlier then on the home page you can find something like this and at the top when you click on the Datasets links, you can see the variety of data sets like recent U.S Election Covid-19 related data sets, etc.

Use Large CSV

All these data sets are publicly available. In short, Kaggle is one of the very biggest resources that you can find online to find out any data set you may require. Large CSV files are very helpful in data analysis and data mining related applications.

Many libraries of different programming languages can handle large CSV files easily and most of them provide some way to specify the field delimiters character encoding, coding conventions, debt formats, etc.

We have reached the end of the course hope you have enjoyed this course and stay tuned with us to get more updates so till then keep on learning.

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