Create app.py

Adding the app.py from the vscode

app.py

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+import streamlit as st
+import pandas as pd
+
+complaints_count = st.container() # contains the number of complaints in each bucket
+graphs = st.container() # contains the graphs for the complaints
+dataset = st.container() # shows the recent complaints
+
+
+# TOTAL COUNT SECTION
+with complaints_count:
+    st.header("Complaints counts")
+    data = "./data/complaints_v1.csv"
+    complaints_df = pd.read_csv(data,sep=",")
+    total_counts = len(complaints_df.index)
+    service_issues_counts = complaints_df['sub_cat'].value_counts()['service_issues']
+    product_issues_counts = complaints_df['sub_cat'].value_counts()['product_issues']
+    billing_issues_counts = complaints_df['sub_cat'].value_counts()['billing_issues']
+
+    col1,col2,col3,col4 = st.columns(4)
+    col1.metric(label="Total Complaints", value=total_counts, delta="1.2 %")
+    col2.metric(label="Total Billing Issues", value=service_issues_counts, delta="-1 %")
+    col3.metric(label="Total Product Issues", value=product_issues_counts, delta="-1.3 %")
+    col4.metric(label="Total Service Issues   ", value=billing_issues_counts, delta="+1.2 ")
+
+
+#Graphs SECTION
+with graphs:
+    st.header("Gprahs")
+
+
+# RECENT COMPLAINTS SECTION
+with dataset:
+    st.header("Recent Complaints")
+    ground_truth_data = pd.read_csv("./data/ground_truth.csv")
+    ground_truth_data.rename(columns= {'audio_id':'Audio ID','file_name':'File Name', 'transcription':'Complaints', 'sub_cat':'Complaint Category'}, inplace = True)
+    columns = ['Audio ID','File Name', 'Complaints', 'Complaint Category']
+    st.dataframe(ground_truth_data[columns].iloc[15:23], 
+                 hide_index=True
+                 )