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Name | lat | lon | |
---|---|---|---|
The University of Aberdeen | 57.165019 | -2.099122 | |
University of Abertay Dundee | 56.46334 | -2.973441 | |
Aberystwyth University | 52.403473 | -4.043584 | |
Anglia Ruskin University | 51.741381 | 0.474495 | |
Aston University | 52.486637 | -1.890952 | |
Bangor University | 53.229193 | -4.129437 | |
Bath Spa University | 51.373209 | -2.440912 | |
The University of Bath | 51.380441 | -2.330673 | |
University of Bedfordshire | 51.87825 | -0.411539 |
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import gpxpy | |
import gpxpy.gpx | |
import folium | |
gpx_file = open('path_to_gpx_file.gpx', 'r') | |
gpx = gpxpy.parse(gpx_file) | |
points = [] | |
for track in gpx.tracks: | |
for segment in track.segments: |
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# Baudot | |
import random | |
import string | |
# Taken from https://www.cryptomuseum.com/ref/ita2/index.htm | |
baudot = { 'a': '0b00011', | |
'b': '0b11001', | |
'c': '0b01110', | |
'd': '0b01001', | |
'e': '0b00001', |
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\documentclass{article} | |
\usepackage{natbib} | |
\usepackage{bibunits} | |
\begin{document} | |
% bibunit to list our publications | |
\begin{bibunit}[plain] | |
\renewcommand{\bibsection}{\large \textbf{\begin{center} | |
Publications | |
\end{center}}} |
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# MIF 2.1 | |
# MIF Example File: ellipsoid.mif | |
# Description: Hysteresis loop of an ellipsoidal particle. | |
# This example uses an Oxs_EllipsoidAtlas to define the | |
# ellipsoid volume. This example is exactly equivalent | |
# to ellipsoid-atlasproc.mif and ellipsoid-fieldproc.mif. | |
set pi [expr {4*atan(1.0)}] | |
set mu0 [expr {4*$pi*1e-7}] | |
set theta 270 |
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import folium | |
points_a = [[1,50], [1.2,50.3], [1.23, 50.7]] | |
points_z = [[1,51], [1.2,51.3], [1.23, 51.7]] | |
# Load map centred on average coordinates | |
ave_lat = sum(p[0] for p in points_a)/len(points_a) | |
ave_lon = sum(p[1] for p in points_a)/len(points_a) | |
my_map = folium.Map(location=[ave_lat, ave_lon], zoom_start=9) |
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# -*- coding: utf-8 -*- | |
import pandas as pd | |
import matplotlib.pyplot as plt | |
import itertools | |
# Load data | |
prices = pd.read_csv("PizzaPrices.csv") | |
# Filter out an unwanted establishment | |
prices = prices[(prices['establishment_name'] != "Pizza Zone")] |
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# -*- coding: utf-8 -*- | |
""" | |
Created on Tue Oct 20 11:41:59 2015 | |
Find out from which years you cited most publications in your thesis or | |
dissertation. | |
https://xkcd.com/208/ | |
May need to somehow account for 'missing' years | |
http://pandas.pydata.org/pandas-docs/stable/missing_data.html |
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import gpxpy | |
import gpxpy.gpx | |
import folium | |
gpx_file = open('my_gpx_coords.gpx', 'r') | |
gpx = gpxpy.parse(gpx_file) | |
points = [] | |
for track in gpx.tracks: | |
for segment in track.segments: |
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import os | |
import folium | |
import pandas as pd | |
from bng_to_latlon import OSGB36toWGS84 | |
os.chdir("C:\Users\Duncan\Documents\Python Scripts\pythonGIS") | |
# Load map centred on Colchester | |
uk = folium.Map(location=[51.8860942,0.8336077], zoom_start=10) | |
# Load locally stored colchester public toilets data | |
toilets = pd.read_csv("public-toilets.csv") |
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