Sacramento Transit - Part 1 - Exploration
Written by sideprojects in Posts on Sun 07 April 2019. Tags: data analysis, GIS, python, cities, geopandas,
Background¶
As cities become increasingly concerned about traffic, infrstructure maintainence, and the environment; increased use of public transit could be way to address several of these challenges at once. I've become interested in understanding how cities can address these challenges, and began reading about urban planning a few years ago. Through reading what some long-time urban planners have to say, I'm beginning to see that if increasing public transit can help alleviate traffic, maintenance and environmental issues, increasing ridership is a multi-dimensional challenge in its own right. The way many places are organized, daily and individual car use is practically required due to the way that most activites and ammenities are spread over miles and metro areas and frequently aren't connected by transit networks.
Python Mapping libraries Introduction
Written by sideprojects in Notes on Sat 16 March 2019. Tags: data analysis, GIS, python, cities,
Intro Tour of Python Mapping Libraries¶
There are several libraries for making spatial visualizations in python. This post creates similar maps of baltimore neighborhoods and grocery stores using several libraries:
Static
- geopandas default mapping (matplotlib)
Interactive:
- Altair (Vega)
- Folium (Leaflet)
Each sections starts from a geopandas dataframes, and has subsections walking through:
- Display Shape
- Plot a Choropleth
Bus Mapping with GeoPandas
Written by sideprojects in Posts on Fri 20 January 2017. Tags: data analysis, GIS, python, cities,
Bus Mapping and Basic GIS with GeoPandas¶
GeoPandas wraps several of Python GIS tools into a set of convenient functions for storing and operating on shapefiles as DataFrames, and makes working with shapefiles look similar to working with Pandas. In this demo, I'm going to demonstrate some of the basic geopandas functionality for getting started with working with shapefiles, and compute some summary statistics from the data.
Pandas Multi-index notes
Written by sideprojects in Notes on Sat 07 May 2016. Tags: data analysis, pandas,
Basic observations of the Misconduct Database ( Part 2 )
Written by sideprojects in Posts on Sun 03 January 2016. Tags: data analysis, fcmd,
Exploring the variables in the Misconduct database
For info on how I came by this data, see part1. I wanted to break it free from looking at one or a handful of entries at a time as you find on the main website and see what I can find by looking at the data a bit differently. Keep in mind all of the caveats
Federal Contractor Misconduct Database ( Part 1 )
Written by sideprojects in Posts on Mon 28 December 2015. Tags: web scraping, docker, data analysis, fcmd,
The Project on Government Oversight has a database of misconduct that details settlements and cases that government entities have brought against their contractors going back to 1995. In the first post of this series, I will describe how I pulled the data for further analysis.