├── README.md
├── Tweets.csv
└── app.py


/README.md:
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1 | # Twitter-sentiment-Streamlit-dashboard
2 | This is a guided cousera project in which we build a twitter sentiment dashbord using streamlit.
3 | 
4 | 
5 | 
6 | 
7 | 
8 | 


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/app.py:
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 1 | import streamlit as st
 2 | import pandas as pd
 3 | import numpy as np
 4 | import plotly.express as px
 5 | from wordcloud import WordCloud, STOPWORDS
 6 | import matplotlib.pyplot as plt
 7 | 
 8 | 
 9 | st.title("Sentiment analysis of Tweets about US Airlines")
10 | st.sidebar.title("Sentiment analysis of Tweets about US Airlines")
11 | 
12 | st.markdown("This application is a Streamlit dashboard to analyze the sentiment of Tweets🐦")
13 | st.sidebar.markdown("This application is a Streamlit dashboard to analyze the sentiment of Tweets🐦")
14 | 
15 | PATH = ("/home/rhyme/Desktop/Project/Tweets.csv")
16 | 
17 | @st.cache(persist=True)
18 | def load_data():
19 |     data = pd.read_csv(PATH)
20 |     data['tweet_created'] = pd.to_datetime(data['tweet_created'])
21 |     return data
22 | 
23 | data =  load_data()
24 | 
25 | #st.write(data)
26 | st.sidebar.subheader("Show random tweet")
27 | random_tweet = st.sidebar.radio('Sentiment',('positive', 'neutral', 'negative'))
28 | st.sidebar.markdown(data.query('airline_sentiment == @random_tweet')[['text']].sample(n=1).iat[0,0])
29 | 
30 | st.sidebar.markdown('### Number of tweets by sentiment')
31 | select = st.sidebar.selectbox('Visualization type', ['Histogram', 'Pie chart'], key='1')
32 | sentiment_count = data['airline_sentiment'].value_counts()
33 | #st.write(sentiment_count)
34 | sentiment_count = pd.DataFrame({'Sentiment':sentiment_count.index, 'Tweets':sentiment_count.values})
35 | 
36 | if st.sidebar.checkbox("Hide", True):
37 |     st.markdown("### Number of tweets by sentiment")
38 |     if select == "Histogram":
39 |         fig = px.bar(sentiment_count,x='Sentiment', y='Tweets', color='Tweets', height=500)
40 |         st.plotly_chart(fig)
41 |     else:
42 |         fig = px.pie(sentiment_count, values='Tweets', names='Sentiment')
43 |         st.plotly_chart(fig)
44 | 
45 | #st.map(data)
46 | 
47 | st.sidebar.subheader("When and where are users tweeting ?")
48 | hour = st.sidebar.slider("Hour of the day", 0 ,23)#alternatively:hour = st.sidebar.number_input("Hour of the day", min_value=1 ,max_value=24)
49 | modified_data = data[data['tweet_created'].dt.hour == hour]
50 | if not st.sidebar.checkbox("Close", True, key='1'):
51 |     st.markdown("##Tweets locations based on the time of day")
52 |     st.markdown("%i tweets %i:00 and %i:00" %(len(modified_data), hour, (hour+1)%24))
53 |     st.map(modified_data)
54 |     if st.sidebar.checkbox("Show raw data",False):
55 |         st.write(modified_data)
56 | 
57 | st.sidebar.subheader("Breakdown Airline tweets by sentiment")
58 | choice = st.sidebar.multiselect('Pick airlines', ('US airway', 'United', 'American', 'Southwest', 'Delta', 'Virgin America'),key='0')
59 | 
60 | if len(choice) > 0:
61 |     choice_data = data[data.airline.isin(choice)]
62 |     fig_choice = px.histogram(choice_data, x='airline', y='airline_sentiment',histfunc='count', color='airline_sentiment',
63 |     facet_col='airline_sentiment', labels={'airline_sentiment':'tweets'}, height=600, width=800)
64 |     st.plotly_chart(fig_choice)
65 | 
66 | st.sidebar.header("Word Cloud")
67 | word_sentiment = st.sidebar.radio('Which sentiment type would you like to display a word cloud?', ('positive', 'neutral', 'negative'))
68 | 
69 | if not st.sidebar.checkbox("Close", True, key='3'):
70 |     st.subheader('Word cloud for %s sentiment' %(word_sentiment))
71 |     df = data[data['airline_sentiment']==word_sentiment]
72 |     words = ' '.join(df['text'])
73 |     processed_words = ' '.join([word for word in words.split() if 'http' not in word and not word.startswith('@') and word != 'RT'])
74 |     wordcloud = WordCloud(stopwords=STOPWORDS, background_color='white', height=640, width=800).generate(processed_words)
75 |     plt.imshow(wordcloud)
76 |     plt.xticks([])
77 |     plt.yticks([])
78 |     st.pyplot()
79 | 


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