app.py

import streamlit as st
import pandas as pd
import numpy as np
import plotly.express as px
from wordcloud import WordCloud, STOPWORDS
import matplotlib.pyplot as plt
import os

st.set_option('deprecation.showPyplotGlobalUse', False)

st.title("Sentiment Analysis of Tweets about US Airlines")
st. sidebar.title("Sentiment Analysis of Tweets about US Airlines")

st.markdown("This application is a streamlit dashboard used to analyze the sentiment of Tweets 🐦︎")
st.sidebar.markdown("This application is a streamlit dashboard used to analyze the sentiment of Tweets 🐦︎")

#data_url = "C://Users/testaccount/CurrentProject/Tweets.csv"
dir_path = os.path.dirname(os.path.realpath(__file__))
DATA_URL = os.path.join(dir_path, "Tweets.csv")

@st.cache(persist=True)
def load_data():
    data = pd.read_csv(DATA_URL)
    data.tweet_created = pd.to_datetime(data.tweet_created)
    return data

data = load_data()



st.sidebar.subheader("Show random tweet")
random_tweet = st.sidebar.radio('Sentiment', ('positive', 'neutral', 'negative'))
st.sidebar.markdown(data.query('airline_sentiment == @random_tweet')[["text"]].sample(n=1).iat[0,0])

st.sidebar.markdown("### Number of tweets by sentiment")
select = st.sidebar.selectbox('Visualization type', ['Histogram', 'Pie chart'], key='1')
sentiment_count = data['airline_sentiment'].value_counts()
sentiment_count = pd.DataFrame({'Sentiment':sentiment_count.index, 'Tweets':sentiment_count.values})

if not st.sidebar.checkbox('Hide', True):
    st.markdown('### Number of tweets by sentiment')
    if select == "Histogram":
        fig = px.bar(sentiment_count, x="Sentiment", y="Tweets", color='Tweets', height=500)
        st.plotly_chart(fig)
    else:
        fig = px.pie(sentiment_count, values="Tweets", names="Sentiment")
        st.plotly_chart(fig)

st.sidebar.subheader('When and where are users tweeting from?')
#hour = st.sidebar.number_input("Hour of day",min_value= 1, max_value=24)
hour = st.sidebar.slider("Hour of day",0, 23)
modified_data = data[data['tweet_created'].dt.hour == hour]
if not st.sidebar.checkbox("Close", True, key='1'):
    st.markdown("### Tweets location based on the time of day")
    st.markdown("%i tweets between %i:00 and %i:00"%(len(modified_data), hour, (hour+1)%24))
    st.map(modified_data)
    if st.sidebar.checkbox("Show raw dat", False):
        st.write(modified_data)

st.sidebar.subheader("Breakdown airline tweets by sentiments")
choice = st.sidebar.multiselect('Pick airlines', (set(data.airline)),key='0')

if len(choice) > 0:
    choice_data = data[data.airline.isin(choice)]
    fig_choice = px.histogram(choice_data, x='airline', y='airline_sentiment', histfunc='count', color='airline_sentiment',
    facet_col = 'airline_sentiment', labels={'airline_sentiment': 'tweets'}, height=600, width=800)
    st.plotly_chart(fig_choice)

st.sidebar.header("Word Cloud")
word_sentiment = st.sidebar.radio("Display word cloud for what sentiment?", ('positive', 'neutral', 'negative'))

if not st.sidebar.checkbox("Close", True, key="3"):
    st.header("Word cloud for %s sentiment" % (word_sentiment))
    df = data[data.airline_sentiment== word_sentiment]
    words = ' '.join(df.text)
    preproced_words = ' '.join([word for word in words.split() if 'http' not in word and not word.startswith('@') and word != "RT"])
    wordcloud = WordCloud(stopwords=STOPWORDS, background_color='white', height=640, width=800).generate(preproced_words)
    plt.imshow(wordcloud)
    plt.xticks([])
    plt.yticks([])
    st.pyplot()

st.sidebar.subheader("Dashboard developed by Ajmal Sarwary")