The picture above comes from the dashboard that contains data from twitter concerning the Swedish Tax Agency, “Skatteverket”, that I created.
I used Python and R in this project. Python was used to download around 4 2000 old tweets that mentions “Skatteverket”, I was able to do this by using the package GetOldTweets3 in Python.
I used R and the package Rtweet to download data from the official account of Skatteverket.
The picture above is from the live dashboard that I created.
This was a fun project for me because I learned so much and used many different tooltips! The mission was to extract data from a website that contains information on figure skaters from all over the world.
I used Python in order to scrape the data by using Beautiful Soup and Pandas, I also cleaned the data in Python.
Using Excel at the workplace
At my current workplace I have been known as one of the “go to college” when it comes to tips and tricks in Excel but also more advance topics like new formulas or macros. One of my colleagues in another department asked over lunch if I knew something that could help him with updating names in a column in Excel. The problem was that another program outside of Excel automatically updates the names but just once a day, and new data can be imported with several thousand rows hours before which therefore have no name for a long time.
Web scraping Lund University for the student papers.
Lund University has this website: Student Papers. I used R with packages such as Rvest to gather the data and Rselium to loop trough some of the webpages.
I had to first collect the ID of every student paper and then create two loops for downloading the data. The first loop downloaded a dataframe that consist of data such as Author Names, Faculty, Department, title of the paper, Language, Year it was pubslihed and so on.
Introduction
This post will explore suicides across the world for a long time period. Questions that I asked and will be answered is What country have the relative highest suicides? What Countries increases and decreases in suicide? Is there a pattern considering continent? Is age an interesting variable to study?
Suicide is a sensitive topic and I only want to explore and try to understand it more by doing this analysis.
Exploration of Anime and the users of MyanimeList
This post will explore the Japanese Anime industry, for example, which studio produces the most Animes? Which studio have the “best” animes?.
I will aslo explore users that uses the website MyanimeList. The website let users create profiles where the can select their favorite anime, animes they have watched, animes they plan on watching, animes they have dropped, and each user can score the anime between 0 to 10.
It’sss aaaa Mee Mariooo analysis
Welcome! And a big thank you for viewing this post! This analysis is all about our favorite plumber Super Mario and the fantastic makers and players that have played the game Mario Maker.
But let me first explain what the game Mario Maker is all about. Mario Maker combines the best of traditional Mario games and human creativity, because players are given tools to create their own Mario levels and the other players can play those levels.
Classifying customers that open a term deposit
This data analysis will be a little different than the previous in that sense that I will now focus a little more on statistical modelling. The data in this post comes from UCI
The dataset comes from a real bank marketing campaign where the bank tried to tell the customers to open a term deposit.
I will use the package caret in order to perform the following models: