def showOnMap(address,locName,color):
mplt.register_api_key('AIzaSyAnRmqg-kRi7wBE_v1wkujL12RqQV2dGIA')
googleAddress, lat,lng = getLocation(address)
data = pd.DataFrame({
'latitude':lat,
'longitude':lng,
'color':color,
'name':locName
})
mplt.plot_markers(data)
def mapsplot_register():
"""
mapsplotlib Google Static Maps API key to enable queries to Google.
"""
try:
with open('data/api_key.txt', mode='r') as f:
API_key = f.readline().strip()
mplt.register_api_key(API_key)
logger.info("Google static map API_KEY successfully registered")
except:
logger.error("mplt.register API_KEY failed")
raise
from mapsplotlib import mapsplot as mplt
import pandas as pd
if __name__ == '__main__':
mplt.register_api_key('AIzaSyBuhS-obrP54G_ToqQAn3rnDY4hLxjy3Z4')
with open(
"../dataset/yelp_academic_dataset_business.json") as business_file:
df = pd.read_json(business_file, lines=True)
df = df[df['city'] == 'Phoenix']
mplt.density_plot(df['latitude'], df['longitude'])
import pandas as pd
from mapsplotlib import mapsplot as mplt
def string_to_coordinate_pair(input):
spl = input.split(",")
return (float(spl[0]), float(spl[1]))
f = open("googlemapskey.txt")
apikey = f.readline()[0:-1]
mplt.register_api_key(apikey)
data = pd.read_csv("2018-05-24T04.59.44.000.in",
sep="\t",
index_col=False,
encoding="ISO-8859-1")
points = set()
for idx, row in data.iterrows():
split = row["path"].split(" ")
#print(split)
path = [string_to_coordinate_pair(x) for x in split[1:]]
points |= set([path[0], path[-1]])
print(len(points))
dct = {'latitude': [], 'longitude': []}
for point in points:
dct['latitude'].append(point[0])
dct['longitude'].append(point[1])
df = pd.DataFrame(data=dct)
mplt.density_plot(df['latitude'], df['longitude'])
with open('openrice_data.json') as json_data:
original_data = json.load(json_data)
#get coords
for obj in original_data:
lats.append(obj['address'][0])
longs.append(obj['address'][1])
#get names
for obj in original_data:
names.append(obj['name'])
# for x in range( len(lats) ):
# temp = (lats[x], longs[x], reviews[x])
# combo.append(temp)
# labels = ['latitude', 'longitude', 'reviews']
# df = pd.DataFrame.from_records(combo, columns=labels)
mplt.register_api_key('AIzaSyBWMZIWfp9p0bdqqDoEuJN3D4IuVKtUttU')
## Getting data and filtering
## Please register your key and design the correct query
key = "AIzaSyBWMZIWfp9p0bdqqDoEuJN3D4IuVKtUttU"
query = ""
# you might want a for loop to send and receive the query
url = "https://maps.googleapis.com/maps/api/distancematrix/json?" + query
res = requests.get(url).json()
import csv
import string
import pandas as pd
import matplotlib.pyplot as plt
from mapsplotlib import mapsplot as mplt
mplt.register_api_key('AIzaSyC23WZ06xZau9Gw2R_ulYm6f0L5uxLdAeM')
def map(file_ext):
print('Generating Map')
f = open('distances_latlon'+file_ext+'.csv', 'r')
reader = csv.reader(f)
cities_list = list(reader)
f.close()
cities_lat = []
cities_lon = []
color = []
size = []
marker_list = []
Upper = list(string.ascii_uppercase)
digits = list(string.digits)
markers = Upper+digits
for i in range(len(cities_list)):
cities_lat.append(float(cities_list[i][0]))
cities_lon.append(float(cities_list[i][1]))
color.append('blue')
size.append('medium')
'''
This is the only separated file since you need python 2.x to run it, activate the python 2.x env to make it work
'''
from utilities.twitterparser import Twitter_Parser
from mapsplotlib import mapsplot as mplt
from utilities.env import *
parser = Twitter_Parser()
tweets_with_location = parser.get_location_tweets(remove_locality=True)
mplt.register_api_key(maps_api_key)
mplt.density_plot(tweets_with_location['latitude'],
tweets_with_location['longitude'])
#!/usr/bin/env
# -*- coding: utf-8 -*-
__author__ = "Powen Ko, www.powenko.com"
import pandas as pd
from mapsplotlib import mapsplot as mplt
df = pd.read_csv("data.csv")
mplt.register_api_key('your_google_api_key_here')
mplt.density_plot(df['latitude'], df['longitude'])
from mapsplotlib import mapsplot as mplt
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.io import loadmat
mplt.register_api_key('xxx') # xxx = your Google api key
fileLines_survey = 'lines_survey'
survey_data = loadmat('Lines/' + fileLines_survey + '.mat')
east_survey = survey_data['lines_survey'][:, 0]
north_survey = survey_data['lines_survey'][:, 1]
z_survey = survey_data['lines_survey'][:, 2]
eastn = east_survey[~np.isnan(east_survey)]
northn = north_survey[~np.isnan(north_survey)]
zn = z_survey[~np.isnan(z_survey)]
d_utm = {'east': eastn, 'north': northn, 'value': zn}
df_utm = pd.DataFrame(data=d_utm)
mplt.scatter_with_utm(df_utm['east'],
df_utm['north'],
df_utm['value'],
29,
'N',
maptype='satellite',
cbar=True,
title='Some Survey',
cLabel='Val',