Look for trends, patterns, and anomalies in the data. Either way, you’ll want to accomplish the following during these early investigations.ĭiscover the underlying structure of the data. This could be done separate from or in conjunction with data cleaning. Exploratory data analysis, or EDA for short, helps you explore what questions to ask. Exploratory data analysis (EDA)ĭata analysis is all about answering questions with data. Some sites where you can find “dirty” data sets to work with include:Įxample data cleaning project: This Medium article outlines how data analyst Raahim Khan cleaned a set of daily-updated statistics on trending YouTube videos. Data cleaning (also called data scrubbing) is the process of removing incorrect and duplicate data, managing any holes in the data, and making sure the formatting of data is consistent.Īs you look for a data set to practice cleaning, look for one that includes multiple files gathered from multiple sources without much curation. Data cleaningĪ significant part of your role as a data analyst is cleaning data to make it ready to analyze. Schneider of Wedding Crunchers scraped some 60,000 New York Times wedding announcements published from 1981 to 2016 to measure the frequency of specific phrases. If you’re unsure where to start, here are some websites with interesting data options to inspire your project:Įxample web scraping project: Todd W.
#Octoparse reddit free#
You’ll also find several tools that automate the process (many offer a free trial), like Octoparse or ParseHub.
#Octoparse reddit how to#
If you don’t know how to code, don’t worry. If you know some Python, you can use tools like Beautiful Soup or Scrapy to crawl the web for interesting data. Plus, knowing how to scrape web data means you can find and use data sets that match your interests, regardless of whether or not they’ve already been compiled. While you’ll find no shortage of excellent (and free) public data sets on the internet, you might want to show prospective employers that you’re able to find and scrape your own data as well. These data analytics project ideas reflect the tasks often fundamental to many data analyst roles. As an aspiring data analyst, you’ll want to demonstrate a few key skills in your portfolio.
0 kommentar(er)
