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| import tweepy | |
| from tweepy import Cursor,API | |
| from tweepy.streaming import StreamListener | |
| from tweepy import OAuthHandler,Stream | |
| import Credential | |
| auth=OAuthHandler(Credential.CUSTOMER_KEY,Credential.CUSTOMER_SECRECT_KEY) | |
| auth.set_access_token(Credential.ACCESS_TOKEN,Credential.ACCESS_SECRECT_TOKEN) | |
| api=API(auth,wait_on_rate_limit=True) |
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| import pandas as pd | |
| data=pd.read_csv('location.csv') | |
| print(data.columns) | |
| data=data[['country_name','city_name','country_iso_code']] | |
| print(data) | |
| data.to_csv('city_country_data.csv') |
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| import json | |
| def string_to_json(line): | |
| import ast | |
| jsonval=ast.literal_eval(line) | |
| return jsonval | |
| location=[] | |
| for line in open('tweetCur.json', 'r',encoding="utf-8"): | |
| line=string_to_json(line) |
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| import pandas as pd | |
| import numpy as np | |
| import tqdm | |
| data=pd.read_csv('city_country_data.csv') | |
| df=pd.DataFrame(columns=['Country','code']) | |
| with open('location.txt','r')as r: | |
| location=r.readlines() | |
| for i in tqdm.tqdm(data['country_name'].unique()): | |
| for j in location: |
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| import plotly.offline as py | |
| import pandas as pd | |
| df = pd.read_csv('tweet_location.csv') | |
| count_dict=dict(df['Country'].value_counts()) | |
| df['count']=df['Country'].map(count_dict) | |
| df=df.drop(['Unnamed: 0'],axis=1) | |
| df=df.drop_duplicates() | |
| print(df) |
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| CONTRACTION_MAP = { | |
| "ain't": "is not", | |
| "aren't": "are not", | |
| "can't": "cannot", | |
| "can't've": "cannot have", | |
| "'cause": "because", | |
| "could've": "could have", | |
| "couldn't": "could not", | |
| "couldn't've": "could not have", | |
| "didn't": "did not", |
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| from bs4 import BeautifulSoup | |
| import urllib3 | |
| import json | |
| http=urllib3.PoolManager() | |
| Abbr_dict={} | |
| #Function to get the Slangs from https://www.noslang.com/dictionary/ | |
| def getAbbr(alpha): | |
| global Abbr_dict | |
| r=http.request('GET','https://www.noslang.com/dictionary/'+alpha) | |
| soup=BeautifulSoup(r.data,'html.parser') |
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| import json | |
| with open('ShortendText.json','r') as file: | |
| Abbr_dict=json.loads(file.read()) | |
| splitLine=line.split() | |
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| from textblob import TextBlob | |
| #line == text | |
| blob=TextBlob(line) | |
| blob.correct() |
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| from gingerit.gingerit import GingerIt | |
| parser = GingerIt() | |
| #line==string you wanna correct | |
| tweet=parser.parse(line) |
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