Introduction Sleeping, and python. Two of my favourite things, when combined with the the Python Fitbit library, Matplotlib, and Pandas, can generate informative plots of your sleeping habits! This post explores how we can pull date from the Fitbit API, create a Pandas Dataframe, and then plot the results. In this tutorial, I’ve used Python …
Nothing beats the bar plot for fast data exploration and comparison of variable values between different groups, or building a story around how groups of data are composed. The ability to render a bar plot quickly and easily from data in Pandas DataFrames is a key skill for any data scientist working in Python.
In this tutorial, we’ll examine every aspect of creating bar charts with the Pandas library in Python.
The ability to explore and grasp data structures through quick and intuitive visualisation is a key skill of any data scientist. At PyConIE 2018, I presented a talk on the various libraries available for data visualisation in Dublin. This post contains the slides from that talk, along with a video recording of same.
Anyone familiar with the use of Python for data science and analysis projects has googled some combination of “plotting in python”, “data visualisation in python”, “barcharts in python” at some point. It’s not uncommon to end up lost in a sea of competing libraries, confused and alone, and just to go home again! The purpose …
In this post, geocoded data for all property price sales in Ireland from 2012-2017 is available. Data is sourced on the Irish Property Price Register and geocoded using the Google geocoding script in Python. All of the GPS latitude/longitude coordinates are further tied to census small area and electoral division boundaries.