Linwood Creekmore linwoodc3
linwoodc3
/ linwood_utilities.py
Last active
April 11, 2017 11:12
Utility functions for District Data Labs blog on geolocated social media. These functions clean and prepare Twitter data for geospation analysis, in addition to removing personally identifying information.
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| # Author: | |
| # Linwood Creekmore III | |
| # email: [email protected] | |
| # Custom functions for Twitter Geospatial Analysis Blog | |
| ################################# | |
| # Class for corrupt json | |
| ################################# |
linwoodc3
/ shapefilereader.py
Last active
September 23, 2017 00:12
Using Python 2 (doesn't work for 3), this function reads zipped shapefiles from the web or disk and convert it into a Python geodataframe (pandas dataframe with spatial features).
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| import geopandas as gpd | |
| import numpy as np | |
| import requests | |
| import gdal | |
| import fiona | |
| import uuid | |
| import re | |
| # informaed by: https://gis.stackexchange.com/questions/225586/reading-raw-data-into-geopandas/225627 |
linwoodc3
/ ddlTwitterPlotters.py
Created
April 18, 2017 03:13
matplotlib plotting functions for my District Data Labs Twitter post.
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| # Author: Linwood Creekmore | |
| # email: [email protected] | |
| # date: 17 April 2017 | |
| import matplotlib.pyplot as plt | |
| from matplotlib import gridspec | |
| import matplotlib.patches as patches | |
| import datetime | |
| import pandas as pd |
linwoodc3
/ tweetCountryChoropleth.py
Last active
April 22, 2017 23:18
Simple code to create a choropleth based on the number of tweets.
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| def continentlabs(row): | |
| shape = row['geometry'].centroid | |
| x,y = shape.x,shape.y | |
| return (x,y,row['name']) | |
| %matplotlib inline | |
| from matplotlib import legend | |
| f, ax = plt.subplots(1, figsize=(20, 12)) | |
| gpd.read_file(gpd.datasets.get_path('naturalearth_lowres')).plot(ax=ax,color='white',linewidth=0.2) | |
| gdf.merge(countdf,left_on='name',right_on='NAME').plot(column='counted',cmap='OrRd',scheme='Fisher_Jenks',ax=ax,linewidth=0.1,edgecolor='white',legend=True,alpha=0.4) |
linwoodc3
/ utilities.py
Last active
February 14, 2025 01:49
A python script to scrape text from websites. This works surprisingly well on most news websites when you have the URL to the story. Use GDELT urls for the best results.
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| # Author: Linwood Creekmore | |
| # Email: [email protected] | |
| # Description: Python script to pull content from a website (works on news stories). | |
| #Licensed under GNU GPLv3; see https://choosealicense.com/licenses/lgpl-3.0/ for details | |
| # Notes | |
| """ | |
| 23 Oct 2017: updated to include readability based on PyCon talk: https://github.com/DistrictDataLabs/PyCon2016/blob/master/notebooks/tutorial/Working%20with%20Text%20Corpora.ipynb | |
| 18 Jul 2018: added keywords and summary |
linwoodc3
/ worldDataframes.py
Last active
October 1, 2017 15:11
Python code to create geodataframe for countries, lakes, and oceans for geospatial analysis in Python. Use geopandas and Python 2 or download the
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| #Author: Linwood Creekmore | |
| #Date: October 1, 2017 | |
| # Instructions: | |
| """ | |
| Download and use my shapefilereader function in Python 2 OR just download the linked zip to your computer and read using geopandas | |
| gist to shapefilereader - > https://gist.github.com/linwoodc3/72b2f24b6d2ff6ffde1597f1ca2dea3f | |
| """ |
linwoodc3
/ timenormalize.py
Last active
October 18, 2017 11:29
Get a timezone string from a latitude and longitude pair for timezone normalization.
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| # Created by: Linwood Creekmore III | |
| # [email protected] | |
| from tzwhere import tzwhere | |
| tz = tzwhere.tzwhere() | |
| import numpy as np | |
| def getT(x): | |
| try: | |
| latitude=x[1] |
linwoodc3
/ index.html
Created
April 22, 2018 03:00
Simple front end for machine learning web application demo
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| <!DOCTYPE html> | |
| <html> | |
| <title>QB-Spective</title> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1"> | |
| <link rel="stylesheet" href="https://www.w3schools.com/w3css/4/w3.css"> | |
| <link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Lato"> | |
| <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css"> | |
| <style> | |
| body { font-family: sans-serif; } |
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| body { | |
| background-color: #E5E5FF; | |
| } | |
| img.resize { | |
| max-width:70%; | |
| max-height:70%; | |
| } | |
| #the-string { | |
| display: none; | |
| } |
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| <!DOCTYPE html> | |
| <html> | |
| <title>QB-Spective</title> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1"> | |
| <link rel="stylesheet" href="https://www.w3schools.com/w3css/4/w3.css"> | |
| <link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Lato"> | |
| <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css"> | |
| <style> | |
| body { font-family: sans-serif; } |