Jun 17, 2016

Where to Live in Barcelona in a Dashboard

Barcelona best barrio visualization

Sometimes data can tell a story much faster and effectively than many words. That's why I´ve decided to start sharing more data stories via this blog, hoping to both:

  1. address specific topics readers want to dive in (often these will not be data-people, they would be new to my blog, probably coming after googling a specific questions e.g. "which are the best boroughs to live in Barcelona?").
  2. showcase data visualization tools and best practices to present your data (these are data-people, yes you my regular readers, you might like to see a tool in action).

I will mainly make use of Tableau Public to build and share the data visualizations. Tableau Public is basically the free version of Tableau Software. You can take advantage of the great analytics power offered by Tableau, make amazing visualizations quickly and share them on the web (remember that once published they are all freely accessible to everybody). There is a huge community of people sharing stories via Tableau Public (take a look at the Tableau Public Gallery here) and it is very popular in data journalism.

Back to this post, this quick data viz story is about the city of Barcelona and its boroughs. As the title says, the dashboard aims to help users explore and choose the best borough to live in, given a set of variables. These are:

  • rent price (avg. rent price for a 50 square meter apartment)
  • sales price (avg. sales price for a 50 square meter apartment) 
  • safety 
  • green areas 
  • a short tourism description
The dashboard is composed of three viz:

  1. A map showing how Barcelona it is divided by its 10 main boroughs ("distritos"). The colour scale indicates the average renting price: the darker is the colour and the more expensive is renting in that area. If you click on any of the borough, the correspondent tourism description will show up in the below section.
  2. A vertical bar chart which lets you compare boroughs by different variables using a drop-down filter.  
  3. A bottom section containing the tourism description of the borough selected in the map.
In the "data sources" I provided the sources of data.  

Below is the viz, I hope enjoy it. Any issue, you can view it directly in my Tableau Public profile.

I know it's quite a simplified model in terms of variables considered. Choosing where to live is a complex decision and you'll probably take into account many more factors like proximity to your job/school, public transports, nightlife, etc. etc.  

But, like I did in other previous posts about dashboards, I like proof of concepts (POC) and this wants to be mostly a proof of concept. Can an interactive data visualization help you choose the best place to live in a city? I think so. At least it can narrow down your focus in your initial search for a house, especially when you are new to it. Often you need to check out many websites before you can get an idea of how a city is structured. A dashboard equipped with relevant information can help you explore a city much more quickly.

We need more dashboards about cities!

Why Barcelona? It´s one of my favourite cities. I have been to Barcelona 5 times, always as a tourist, and if you ask me which city would you like to move in the future.... guess which one?

PS: would you like to enrich this dashboard with more relevant info? Feel free to suggest other variables and sources of data and I will try to include them.

Mar 27, 2016

Enhance your Blog Measurement with these Google Analytics Calculated Metrics

Calculated Metrics in GA

Google Analytics has recently incorporated a new powerful feature that offers more flexibility for measuring your own business objectives. I am talking about calculated metrics.

In this post I am going to suggest a list of calculated metrics that you can easily configure in Google Analytics to better measure your blog performance.

As a blogger, when it comes to measure performance of my content, I am very focused on measuring readers engagement with the content I publish. Also, I am constantly looking to increase my readers base, giving my blog more exposure and acquiring new subscribers. Here is an outline of my measurement plan using Google Analytics (I highly recommend this read if you are new on the concept of digital measurement plan).

The new calculated metrics feature gives me the opportunity to customize my own measurement plan. How?

Feb 8, 2016

What happens when you have outliers in your data?

In this post I am going to talk briefly about outliers and the effect they might have on your data. With an example of course. Let's start with defining the word "outlier": what is an outlier in math/statistics?

An outlier is basically a number (or data point) in a set o data that is either way smaller or way bigger than most of the other data points.

Let's go through a practical example in order to understand the implications of having an outlier within your data set.

Jan 17, 2016

Scheduling R Markdown Reports via Email

GA markdown report using R
R Markdown is an amazing tool that allows you to blend bits of R code with ordinary text and produce well-formatted data analysis reports very quickly. You can export the final report in many formats like HTML, pdf or MS Words which makes it easy to share with others. And of course, you can modify or update it with fresh data very easily.

I have recently been using it R Markdown for pulling data from various data source such Google Analytics API and MySQL database, perform several operations on it (merging for example) and present the outputs with tables, visualizations and insights (text).

But what about automating the whole report generation and emailing the final report as an attached document every month at a specific time?