def do_prepare(coin, specific_hour):
pd.set_option('display.max_rows', 99)
pd.set_option('precision', 10)
pd.set_option('display.width', 1000)
#Getting Tweets from DB
tweetio = TweetIO()
df = tweetio.read_db_tweet_last_n_hour_by_specific_hour_by_coin(
coin, specific_hour)
coin.tweets = df
print("tweets from DB: ")
print(len(df))
#Filter and sort tweets
#tapi = TwitterApi() we dont need twitter connection:
tweetcollector = TweetCollector(None)
df = tweetcollector.filter_tweets(coin.tweets)
df = tweetio.sort_and_clip(df, coin.loadtime)
coin.tweets = df
print("tweets>: ")
print(len(df))
#Collect retweets, users
rdf = tweetio.read_db_retweet_last_n_hour_by_specific_hour_by_coin(
coin, specific_hour)
setattr(coin, 'retweets', rdf)
print("retweets>: ")
#print(rdf)
udf = tweetio.read_db_referenced_users(coin)
print("Users>: ")
print(len(udf))
#tweetcollector.collect_all_users(coin, tapi, tmpdir=tmpd)
##PREPARE 1
#df = tweetio.read_all_scraped_retweet(coin, tmpd)
## MERGING TWEET FOLLOWERS
#tweetio.read_users_for_tweets(coin, tmpd)
print("nr. of tweets before merge:")
print(len(coin.tweets))
coin.tweets = coin.tweets.merge(udf,
left_on='user_history_row_id',
right_on='user_row_id',
how='inner')
print("nr. of tweets after merge:")
print(len(coin.tweets))
sid = SentimentAnalyzer()
#only with multicore CPU:
#dfsents = sid.paralellanalyse(coin.tweets)
#this with singlecore CPU:
dfsents = sid.analysedf(coin.tweets)
# print(dfsents.head())
print("coin.tweets ready.")
setattr(coin, 'tweets', dfsents)
# PREPARE 2
#df = tweetio.sort_and_clip(coin.tweets, coin.ico)
#coin.tweets = df
## MULTIPLYING RETWEETS FOLLOWERS
print("multiplying nr. of retweet followers by sentiments.")
sentanalyzer = SentimentAnalyzer()
sentanalyzer.merge_tweets_with_retweets(coin)
sentanalyzer.sent_mul_tweet_followers(coin)
sentanalyzer.sent_mul_retweet_followers(coin)
print(len(coin.retweets))
#print(coin.retweets.head())
## GROUPING RETWEETS BY HOUR
print("grouping retweets by hour basis")
sentanalyzer.group_retweet_by_hour(coin)
#print(coin.grtdf.head())
print("grouping tweets by hour basis")
sentanalyzer.group_tweet_by_hour(coin)
#print(coin.gtdf.head())
print("RETWEET S")
#print(coin.retweets)
print(len(coin.retweets))
print("TWEETS")
#print(coin.tweets)
print(len(coin.tweets))
print("USERS")
#print(udf)
print(len(udf))
## Setting in prices:
bapi = BinanceApi()
coin_price = bapi.collect_coindata(coin, specific_hour)
setattr(coin, 'pricehourly', coin_price)
coin.save_to_storeage(PHASE, tmpdir='runtime/')
return coin
#cinfo=CoinInfo()
#coinlist=cinfo.list_coins('./data/altcoin-1hour')
## choosing first one: neo
#coin=coinlist[19]
coin = Coin()
coin.path = "./data/altcoin-1hour/ada.csv"
coin.name = "ada"
coin.ico = "2017-10-01"
#coin.ico="2016-02-17"
tweetio = TweetIO()
coin.read_from_storeage("prepare1")
print(coin.tweets.columns)
print(coin.retweets.columns)
df = tweetio.sort_and_clip(coin.tweets, coin.ico)
coin.tweets = df
## MULTIPLYING RETWEETS FOLLOWERS
print("multiplying nr. of retweet followers by sentiments.")
sentanalyzer = SentimentAnalyzer()
sentanalyzer.merge_tweets_with_retweets(coin)
#print(coin.tweets)
sentanalyzer.sent_mul_tweet_followers(coin)
sentanalyzer.sent_mul_retweet_followers(coin)
print(len(coin.retweets))
print(coin.retweets.tail())
## GROUPING RETWEETS BY HOUR
cinfo=CoinInfo()
coinlist=cinfo.list_coins('./data/altcoin-1hour')
## choosing first one: xyz
coin=coinlist[9]
print(coin.name)
coin.ico="2017-07-1"
coin.hashtags=['eos']
tapi=TwitterApi()
tweetcollector=TweetCollector(tapi.get_api())
#do not scrape, just once
#tweetcollector.scrape_coin_tweets(coin)
tweetio=TweetIO()
df=tweetio.read_all_scraped_tweet(coin)
df=tweetio.sort_and_clip(df,coin.ico)
coin.tweets=df
setattr( coin, 'tweets', df )
print(coin.tweets.tail())
stat=Statistics()
stat.plot_tweet_stat(coin)
#tweetcollector.collect_all_retweets(coin,tapi,1,99000)
#tweetcollector.collect_all_users(coin,tapi)