Update app.py
Browse filesmaking small changes to the values in the respective containers
app.py
CHANGED
@@ -13,7 +13,7 @@ dataset = st.container(border=True) #
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# TOTAL COUNT SECTION
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with complaints_count:
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st.header("Complaints counts")
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data = "./data/complaints_v1.csv"
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complaints_df = pd.read_csv(data,sep=",")
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total_counts = len(complaints_df.index)
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@@ -30,29 +30,31 @@ with complaints_count:
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#Graphs SECTION
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with graphs:
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st.header("Complaints plots")
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col1, col2 = st.columns(2)
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with col1:
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st.subheader('Complaints mon-o-mon', divider=True)
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data = {
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'Month': ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun'],
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'Service Issues': np.random.randint(
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'Product Issues': np.random.randint(
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'Billing Issues': np.random.randint(
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}
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# Convert to DataFrame
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mom_df = pd.DataFrame(data)
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st.line_chart(mom_df,
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x='Month',
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use_container_width=True)
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with col2:
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st.subheader('Frequent Issues', divider=True)
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issue_labels = ['service_issues', 'product_issues', 'billing_issues']
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issue_counts = [complaints_df['sub_cat'].value_counts().get(label, 0) for label in issue_labels]
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theta=alt.Theta(field="issue_counts", type="quantitative"),
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color=alt.Color(field="issue_labels", type="nominal"),
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)
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@@ -62,7 +64,7 @@ with graphs:
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# RECENT COMPLAINTS SECTION
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with dataset:
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st.header("Recent Complaints")
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ground_truth_data = pd.read_csv("./data/ground_truth.csv")
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ground_truth_data.rename(columns= {'audio_id':'Audio ID','file_name':'File Name', 'transcription':'Complaints', 'sub_cat':'Complaint Category'}, inplace = True)
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columns = ['Audio ID','File Name', 'Complaints', 'Complaint Category']
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# TOTAL COUNT SECTION
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with complaints_count:
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st.header("Complaints counts",divider=True)
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data = "./data/complaints_v1.csv"
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complaints_df = pd.read_csv(data,sep=",")
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total_counts = len(complaints_df.index)
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#Graphs SECTION
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with graphs:
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st.header("Complaints plots", divider=True)
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col1, col2 = st.columns(2)
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with col1:
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st.subheader('Complaints mon-o-mon', divider=True)
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data = {
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'mon_indx': [1,2,3,4,5,6],
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'Month': ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun'],
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'Service Issues': np.random.randint(0, 36, size=6),
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'Product Issues': np.random.randint(0, 22, size=6),
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'Billing Issues': np.random.randint(0, 19, size=6)
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}
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# Convert to DataFrame
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mom_df = pd.DataFrame(data)
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st.line_chart(mom_df,
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x='Month',
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y=['Service Issues','Product Issues','Billing Issues'],
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use_container_width=True)
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with col2:
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st.subheader('Frequent Issues', divider=True)
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issue_labels = ['service_issues', 'product_issues', 'billing_issues']
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issue_counts = [complaints_df['sub_cat'].value_counts().get(label, 0) for label in issue_labels]
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source = pd.DataFrame({"issue_labels": ['Service Issues', 'Product Issues', 'Billing Issues'], "issue_counts": issue_counts})
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chart = alt.Chart(source).mark_arc(innerRadius=120).encode(
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theta=alt.Theta(field="issue_counts", type="quantitative"),
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color=alt.Color(field="issue_labels", type="nominal"),
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)
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# RECENT COMPLAINTS SECTION
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with dataset:
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st.header("Recent Complaints",divider=True)
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ground_truth_data = pd.read_csv("./data/ground_truth.csv")
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ground_truth_data.rename(columns= {'audio_id':'Audio ID','file_name':'File Name', 'transcription':'Complaints', 'sub_cat':'Complaint Category'}, inplace = True)
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columns = ['Audio ID','File Name', 'Complaints', 'Complaint Category']
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