Hello, everybody. In this post, I will show you about PUBG Mobile Global Championship Season Zero League Stage analysis using R. This data collected from Liquipedia page. I do copy-paste page to excell table (on December 23, 2020) and analysis in R using rio, tidyverse, janitor and ggthemer package.

Previously, I had done a similar analysis about PUBG Mobile. You can read it in the following post.

Loading library, and Prepare Data.

The data that I have is in the form of excell and each sheet contains one superweekend week. For that I combine (bindrow) for each sheet. …

Hello, everybody. In this post, I will show you about PUBG Mobile Pro League SEA Season 2 Scrapping and Analysis Using R. This data collected by scrapping from Liquipedia page. I do scrapping (on October 29, 2020) and analysis in R using tidyverse, ggdark and rvest package.

Loading library, scrapping and Prepare Data.

Because I only do scrapp on single page, so I don’t need to make a function. In the data preparation step, I added a new column, namely placement points based on team placement for each round and total points (kill + placement point).

Hello, everybody. In this post, I created a city-based weather monitoring application. This is a simple application for monitoring the weather in an area / city which is very easy for people to understand. I got this data from the Open Weather API. The library that I use to build this application is as follows.

flexdashboard, tidyverse, glue, httr, jsonlite, leaflet, shiny

Features.

Some of the features on this dashboard are as follows.

• Value Box, displays the important values that are the main highlights.
• Map, displays the position (coordinate) of the area / city that is the main highlight.
• Key Statistic…

Hello, everybody. In this post, I will show you about MotoGP race scrapping and analysis from Season 2014–2019. This data collected by scrapping from motorsportstats.com MotoGP page. I do scrapping (on October 13, 2020) and analysis in R using tidyverse and rvest package.

Loading Library, Create Function and Prepare Data.

Before I started, we need to loading library first. I use tidyverse, rvest and janitor. After that, I made function to do scrapping from the site. After the functions done, it’s time to store raw data into a data frame format. The raw data isn’t ready to analysis, I need to cleaning this data and modified some…

Hello everybody. In this post, I will show you top fives most usefull ggplot extensions for data visualization. Data visualization is the most important step for data analysis task. Data visualization can make everyone understanding about the data much easier. Ggplot one of the most popular tools for data visualization. I prefer using ggplot than base R function to make graph, because ggplot more easy, and readable code.

About Ggplot.

Ggplot2 is a data visualization package for the statistical programming language R. Created by Hadley Wickham in 2005, ggplot2 is an implementation of Leland Wilkinson’s Grammar of Graphics — a general scheme…

Hello, Everybody. In the previous post, I show you about dota 2 tournament (Grand Final Round) in general. In this post, I will show you in a specific team. That is Boom Esport (or Boom ID).

About Boom Esport.

Boom Esports, formerly known as Boom ID, is an esports organization that was founded in November 2016. They are also active in Counter Strike: Global Offensive. On January 30th, 2017, the organization entered the Dota 2 scene. On September 13, 2019, it changed its name from Boom ID to Boom Esports.

Source: Liquidpedia.

About dataset.

This data collected by scrapping from the Liquidpedia Tournament page. I…

Hello, everybody. In this post, I will show you about dota 2 tournament analysis from any tier (Liquidpedia Tier) except tier 4. This data collected by scrapping from Liquidpedia Tournament page. I do scrapping (in July 23, 2020) and analysis in R using tidyverse, rvest and cowplot package.

Get Data

After I made functions, it’s time to store raw data into a data frame format.

dota2_tournament_raw <- 
  bind_rows(map_df(2015:2020, get_tournament_tier3),
            map_df(c(2015, 2017, 2020), get_tournament_tier2),
            map_df(NA, get_tournament_tier1))

Data Preparation

The raw data isn’t ready to analysis, I need to cleaning this data and modified somo column/variable. I also save this data to csv format.

write.csv(dota2_tournament, "dota2_tournament.csv")

Visualize

…

Hello Everyone. In this post I will show you how to re-create diagram with Katadata.co.id style using Plotly and R programming of course.

Based on the information I got from the official website. Katadata.co.id is an online media, data and research company in the fields of economics and business. Founded on April 1, 2012 in Jakarta, the company presents in-depth news, information, data and research results for the benefit of business leaders and policy makers. The Katadata team consists of experienced journalists and researchers in the fields of energy, finance, macroeconomics, trade and infrastructure.

The articles in this word are…