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get_locations.py
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get_locations.py
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import os
import sys
import pandas as pd
import numpy as np
from geopy import geocoders
from geopy.exc import GeocoderTimedOut
import pickle
import country_converter as coco
from tqdm import tqdm
if len(sys.argv) != 2:
print("Usage: python get_locations.py data_file")
COMPLETE_DATA = sys.argv[1]
df = pd.read_pickle(COMPLETE_DATA)
def get_users(thread):
users = [thread.author] if thread.author != '[deleted]' else []
for comment in thread.comments:
if comment['author'] != '[deleted]':
users.append(comment['author'])
return users
users = df.apply(get_users, axis=1)
print(users)
user_info_df = pd.read_csv('user_information.csv', sep=';')
def str_to_list(x):
x = x.strip('][')
x = x.replace(', ', ',')
x = x.replace("'", '')
return x.split(',')
user_info_df.places_lived = user_info_df.places_lived.apply(str_to_list)
user_dict = {}
def to_dict(user):
user_dict[user.user_name] = user.places_lived
user_info_df.apply(to_dict, axis=1)
def get_unique_locations(x):
locations = []
for user in x:
try:
user_list = user_dict[user]
if user_list != ['']:
locations += user_list
except:
continue
return set(locations)
def get_locations(x):
locations = []
for user in x:
try:
user_list = user_dict[user]
if user_list != ['']:
locations += user_list
except:
continue
return locations
unique_locs = users.apply(get_unique_locations)
locs = users.apply(get_locations)
df['unique_locations'] = unique_locs
df['locations'] = locs
all_locations = []
def get_all_locations(x):
for location in x:
if location not in all_locations:
all_locations.append(location)
df.locations.apply(get_all_locations)
def vectorize_locations(x):
ret = np.zeros(len(all_locations))
for location in x:
ret[all_locations.index(location)] += 1
return ret
def code_locations(x):
gn = geocoders.Nominatim(user_agent='nlp-controversy', timeout=6000)
places = []
for location in x:
try:
place = gn.geocode(location, addressdetails=True)
place = place.raw['address']['country_code']
places.append(place)
except TypeError as e:
print(e)
except GeocoderTimedOut as e:
print(e)
except AttributeError as e:
print(e)
places = coco.convert(names=places, to='ISO3')
if isinstance(places, list):
return places
else:
return [places]
tqdm.pandas()
df['vectorized_locations'] = df.locations.apply(vectorize_locations)
df['coded_locations'] = df.locations.apply(code_locations)
df.coded_locations.progress_apply(get_all_locations)
df['vectorized_coded_locations'] = df.coded_locations.apply(vectorize_locations)
print(len(df.vectorized_coded_locations.values[0]))
with open('all_locations.pickle', 'wb') as f:
pickle.dump(all_locations, f)
print(df.coded_locations)
df.to_pickle(COMPLETE_DATA)