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import streamlit as st
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import plotly.express as px
from PIL import Image
from wordcloud import WordCloud
st.set_page_config(
page_title = 'Sentiment Analysis',
layout = 'wide',
initial_sidebar_state='expanded'
)
def run():
# title
st.title( 'Sentiment Prediction')
# sub header
st.subheader('Positive, Neutral, Negative')
# insert image
image = Image.open('sensi.jpg')
st.image(image, caption='image from AltextSoft, education purpose only')
# Deskripsi
st.write('Exploratory Data from dataset')
# show data frame
st.write('The first 10 Data')
df = pd.read_csv('https://raw.githubusercontent.com/mukhlishr/rasyidi/main/tripadvisor_hotel_reviews.csv')
st.dataframe(df.head(10))
# Barplot target columns
st.write('###### Rating ')
fig=plt.figure(figsize=(15,5))
sns.countplot(x='Rating', data = df)
st.pyplot(fig)
def Sentimen(x):
if x<= 5 and x>3:
return 'positive'
if x== 3:
return 'neutral'
if x< 3 and x>=1:
return 'negative'
# Create column 'sentimen'
df['sentimen'] = df['Rating'].apply(Sentimen)
# Barplot Sentiment
st.write('###### Sentiment of Review ')
fig=plt.figure(figsize=(15,5))
sns.countplot(x='sentimen', data = df)
st.pyplot(fig)
# Wordcloud
st.write('###### Word Cloud ')
def show_wordcloud(data, title = None):
wordcloud = WordCloud(
background_color='black',
max_words=200,
max_font_size=45,
scale=1,
random_state=1
).generate(" ".join(data))
fig = plt.figure(1, figsize=(15, 15))
plt.axis('off')
if title:
fig.suptitle(title, fontsize=20)
fig.subplots_adjust(top=2.3)
plt.imshow(wordcloud)
st.pyplot(fig)
# Wordcloud all
show_wordcloud(df['Review'].values)
if __name__ == '__main__':
run() |