Audit OpenStreetMap data for Greater Houston Area

Intro

This project chose the Great Houston Area and used data munging techniques to assess the quality of the data for validity, accuracy, completeness, consistency and uniformity. The following steps are accomplished in the project:

Audited dataset (800+mb) in XML format for Greater Houston Area
Fixed street names and deleted problematic nodes and ways
Found the most popular cuisine and religion in Houston using SQLite

In details, the dataset is cleaned by fixing street names and deleting some problematic nodes and ways. Using SQL, it was able to get some Houston-related insights like the most popular cuisine, the most popular religion and the busiest streets with most merchants.

Data Source

The data is from OpenStreetMap. You can download the Greater Houston Area data that I used here.

Note

This project is part of the efforts for Udacity Data Anaylst Nanodegree.

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
.gitattributes		.gitattributes
01 Create a sample and audit.ipynb		01 Create a sample and audit.ipynb
01+Create+a+sample+and+audit.py		01+Create+a+sample+and+audit.py
02 Data cleaning and output.ipynb		02 Data cleaning and output.ipynb
02+Data+cleaning+and+output.py		02+Data+cleaning+and+output.py
03 SQL.ipynb		03 SQL.ipynb
03+SQL.py		03+SQL.py
Example.ipynb		Example.ipynb
Map_Link_Houston.rtf		Map_Link_Houston.rtf
OpenStreetMap_DataWrangling.html		OpenStreetMap_DataWrangling.html
OpenStreetMap_DataWrangling.ipynb		OpenStreetMap_DataWrangling.ipynb
README.md		README.md
Reference.rtf		Reference.rtf
data_wrangling_schema.sql		data_wrangling_schema.sql
example.osm		example.osm
sample.osm		sample.osm
schema.py		schema.py
schema.pyc		schema.pyc

jeremy-dai/OpenStreetMap_Houston

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Audit OpenStreetMap data for Greater Houston Area

Intro

Data Source

Note

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