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Photo by Zeyn Afuang on Unsplash

In data analytics, plotting is immensely important as it gives us insights from the data. There are various tools out there available for plotting. However, as python has been becoming the hottest programming language contemporarily — especially among data scientists, so I’m going to show you how to plot your data using the most eminent python library used for data plotting, matplotlib. Actually, at first I just wanted to make an article about Indonesia’s poverty year-by-year in visualization, but since I’ve been posting about python tutorials before, so why don’t I share the code too, right? Teehee.

Matplotlib is a prominent python library used for data plotting and it is among the most used ones. It is known for its reliability, convenience, and simplicity for plotting, though it might be not the prettiest one. You could plot your data just by typing a few lines of code and taadaa! you’ll get your data visualized. In this article, you will learn simple plotting using matplotlib as well as simple analysis (or maybe graph reading lmao) of the graph. Please note that the code in this article is just an example aimed to give you an overview of the matplotlib use for data plotting. You may adjust the code as you desire depending on how you want your data to be plotted. The next paragraphs will show you an example of data plotting using Indonesia’s poverty overview year-by-year data. …


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Photo by Markus Spiske on Unsplash

The internet has been evolving so fast and massively since the past few years. The amount of internet users is increasing every day. There are tons of data created each day and it makes data becoming a thing nowadays. Data analytics is an important role now in many fields. In a company — for example; many companies demanding data analytics to size up certain decisions the company makes, like pricing. A company needs to put a reasonable price for the products and sometimes they need to compare the prices from its competitors. They could collect the competitors’ pricing data from websites, and that is where web scraping is spot-on at. Web Scraping is one of the scraping methods that you can choose to collect data from the internet. However, here you will learn how to build an automated web scraper with Python. This method will absolutely ease your work to gather information from websites as it is automated. Okay, enough chit chat. …


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Photo by MORAN on Unsplash

Twitter is one of the most used data sources for data analysis. The reason is that it’s open and free to collect unless you subscribe to the paid version one. Besides, it’s pretty simple to collect data from it. If you haven’t known how to collect Twitter data using python, you can check my previous post, teehee.

Twitter data contains a bunch of information parameters. Sometimes, the data contain unnecessary things that need to be cleaned, such as unnecessary characters, links, newlines, and other kinds of stuff. …


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Photo by Brett Jordan on Unsplash

Twitter is a microblogging service or also called social media where you can tweet out your thoughts within 280 characters. It is used by 330 million people across the world and there are 500 million tweets sent per day. That means, there are a lot of data we could get too as a data geek, teehee 😁. Luckily, Twitter allows us to collect data from it for certain purposes. So, for us who want to do research and need Twitter data for it, we can actually ask Twitter for consent and ultimately get those data through Twitter API. …

About

Aron Akhmad

〖A data geek 📊〗〖Life-long learner〗〖ESFP-T〗〖✨ŸØⱠØ✨〗

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