python - 如何使用 matplotlib 以图形形式显示结果？

Question

我正在使用 matplotlib 在 python 中学习 Twitter 情感分析。目前结果，即（1 为正，0 为中性，-1 为负）显示在控制台中。我想使用 matplotlib 以图形形式显示控制台数据结果。我希望有人帮助我使用 matplotlib 以图形形式显示数据。有人请帮我吗？下面列出了我的代码。

from tweepy import API
from tweepy import Cursor
from tweepy.streaming import StreamListener
from tweepy import OAuthHandler
from tweepy import Stream
from textblob import TextBlob

import twitter_credentials
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import re


## # # TWITTER CLIENT # # # #

class TwitterClient:

    def __init__(self, twitter_user=None):
        self.auth = TwitterAuthenticator().authenticate_twitter_app()
        self.twitter_client = API(self.auth)

        self.twitter_user = twitter_user

    def get_twitter_client_api(self):
        return self.twitter_client

    def get_user_timeline_tweets(self, num_tweets):
        tweets = []
        for tweet in Cursor(self.twitter_client.user_timeline,
                            id=self.twitter_user).items(num_tweets):
            tweets.append(tweet)
        return tweets

    def get_friend_list(self, num_friends):
        friend_list = []
        for friend in Cursor(self.twitter_client.friends,
                             id=self.twitter_user).items(num_friends):
            friend_list.append(friend)
        return friend_list

    def get_home_timeline_tweets(self, num_tweets):
        home_timeline_tweets = []
        for tweet in Cursor(self.twitter_client.home_timeline,
                            id=self.twitter_user).items(num_tweets):
            home_timeline_tweets.append(tweet)
        return home_timeline_tweets


## # # TWITTER AUTHENTICATER # # # #

class TwitterAuthenticator:

    def authenticate_twitter_app(self):
        auth = OAuthHandler(twitter_credentials.CONSUMER_KEY,
                            twitter_credentials.CONSUMER_SECRET)
        auth.set_access_token(twitter_credentials.ACCESS_TOKEN,
                              twitter_credentials.ACCESS_TOKEN_SECRET)
        return auth


## # # TWITTER STREAMER # # # #

class TwitterStreamer:

    """
    Class for streaming and processing live tweets.
    """

    def __init__(self):
        self.twitter_autenticator = TwitterAuthenticator()

    def stream_tweets(self, fetched_tweets_filename, hash_tag_list):

        # This handles Twitter authetification and the connection to Twitter Streaming API

        listener = TwitterListener(fetched_tweets_filename)
        auth = self.twitter_autenticator.authenticate_twitter_app()
        stream = Stream(auth, listener)

        # This line filter Twitter Streams to capture data by the keywords:

        stream.filter(track=hash_tag_list)


## # # TWITTER STREAM LISTENER # # # #

class TwitterListener(StreamListener):

    """
    This is a basic listener that just prints received tweets to stdout.
    """

    def __init__(self, fetched_tweets_filename):
        self.fetched_tweets_filename = fetched_tweets_filename

    def on_data(self, data):
        try:
            print data
            with open(self.fetched_tweets_filename, 'a') as tf:
                tf.write(data)
            return True
        except BaseException, e:
            print 'Error on_data %s' % str(e)
        return True

    def on_error(self, status):
        if status == 420:

            # Returning False on_data method in case rate limit occurs.

            return False
        print status


class TweetAnalyzer:

    """
    Functionality for analyzing and categorizing content from tweets.
    """

    def clean_tweet(self, tweet):
        return ' '.join(re.sub("(@[A-Za-z0-9]+)|([^0-9A-Za-z \t])|(\w+:\/\/\S+)"
                        , ' ', tweet).split())

    def analyze_sentiment(self, tweet):
        analysis = TextBlob(self.clean_tweet(tweet))

        if analysis.sentiment.polarity > 0:
            return 1
        elif analysis.sentiment.polarity == 0:
            return 0
        else:
            return -1

    def tweets_to_data_frame(self, tweets):
        df = pd.DataFrame(data=[tweet.text for tweet in tweets],
                          columns=['tweets'])

        df['id'] = np.array([tweet.id for tweet in tweets])
        df['len'] = np.array([len(tweet.text) for tweet in tweets])
        df['date'] = np.array([tweet.created_at for tweet in tweets])
        df['source'] = np.array([tweet.source for tweet in tweets])
        df['likes'] = np.array([tweet.favorite_count for tweet in
                               tweets])
        df['retweets'] = np.array([tweet.retweet_count for tweet in
                                  tweets])

        return df


if __name__ == '__main__':

    twitter_client = TwitterClient()
    tweet_analyzer = TweetAnalyzer()

    api = twitter_client.get_twitter_client_api()

    tweets = api.user_timeline(screen_name='realDonaldTrump', count=200)

    df = tweet_analyzer.tweets_to_data_frame(tweets)
    df['sentiment'] = np.array([tweet_analyzer.analyze_sentiment(tweet)
                               for tweet in df['tweets']])

    print df.head(10)

标签： pythonmatplotlib