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Author: bansalkanav

Case Studies/2. Airline Sentiment Analyser/web_app/data_app.py

@@ -8,12 +8,16 @@
 import plotly.express as px
 from wordcloud import WordCloud,STOPWORDS
 import create_wordcloud
+from PIL import Image
 
 
 dataset_loc = "data/Tweets.csv"
 image_loc = "img/airline.jpeg"
 pos_loc = "img/pos.png"
 neg_loc = "img/neg.png"
+img_airplane = Image.open(image_loc)
+img_pos_wc = Image.open(pos_loc)
+img_neg_wc = Image.open(neg_loc)
 
 # sidebar
 def load_sidebar():
@@ -70,8 +74,9 @@ def load_viz(df):
  st.header("Data Visualisation")
  # show tweet sentiment count
  st.subheader("Seaborn - Tweet Sentiment Count")
- st.write(sns.countplot(x='airline_sentiment', data=df))
- st.pyplot()
+ fig = plt.figure()
+ sns.countplot(x='airline_sentiment', data=df)
+ st.pyplot(fig)
 
  # ***************
  st.subheader("Plotly - Tweet Sentiment Count")
@@ -82,25 +87,27 @@ def load_viz(df):
 
  # show airline count
  st.subheader("Airline Count")
- st.write(sns.countplot(x='airline', data=df))
- st.pyplot()
+ fig = plt.figure()
+ sns.countplot(x='airline', data=df)
+ st.pyplot(fig)
 
  # Show sentiment based on airline
  st.subheader("Airline Count")
  airline = st.radio("Choose an Airline?", ("US Airways", "United", "American", "Southwest", "Delta", "Virgin America"))
  temp_df = df.loc[df['airline']==airline, :]
- st.write(sns.countplot(x='airline_sentiment', order=['neutral', 'positive', 'negative'], data=temp_df))
- st.pyplot()
+ fig = plt.figure()
+ sns.countplot(x='airline_sentiment', order=['neutral', 'positive', 'negative'], data=temp_df)
+ st.pyplot(fig)
 
  # Show WordCloud
  st.subheader("Word Cloud")
  type = st.radio("Choose the sentiment?", ("positive", "negative"))
  if(os.path.isfile(pos_loc)==False or os.path.isfile(neg_loc)==False):
  create_wordcloud.main()
  if(type=="positive"):
- st.image(pos_loc, use_column_width = True)
+ st.image(img_pos_wc, use_column_width = True)
  else:
- st.image(neg_loc, use_column_width = True)
+ st.image(img_neg_wc, use_column_width = True)
 
 
 
@@ -111,7 +118,7 @@ def main():
 
  # Title/ text
  st.title('Airline Sentiment Analysis')
- st.image(image_loc, use_column_width = True)
+ st.image(img_airplane, use_column_width = True)
  st.text('Analyze how travelers in February 2015 expressed their feelings on Twitter')
 
  # loading the data