GMARTINEZMILLA commited on
Commit
89cddd0
1 Parent(s): 7a66fe8

feat: updated website

Browse files
Files changed (1) hide show
  1. app.py +6 -12
app.py CHANGED
@@ -13,11 +13,6 @@ from utils import recomienda_tfid
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  # Page configuration
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  st.set_page_config(page_title="DeepInsightz", page_icon=":bar_chart:", layout="wide")
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- # Navigation menu
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- with st.sidebar:
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- st.sidebar.title("DeepInsightz")
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- page = st.sidebar.selectbox("Select the tool you want to use", ["Summary", "Customer Analysis", "Articles Recommendations"])
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-
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  # Custom CSS for dynamic theme styling
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  # Streamlit detects light and dark mode automatically via the user's settings in Hugging Face Spaces
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  if st.get_option("theme.base") == "dark":
@@ -62,6 +57,11 @@ st.markdown(f"""
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  </style>
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  """, unsafe_allow_html=True)
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  # Load CSV files at the top
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  df = pd.read_csv("df_clean.csv")
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  nombres_proveedores = pd.read_csv("nombres_proveedores.csv", sep=';')
@@ -186,13 +186,7 @@ if page == "Summary":
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  st.metric(label="Customers Analysed", value="3.000")
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  st.metric(label="Unique Products Sold", value="10.702")
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  st.metric(label="Total Sales Instances", value="764.396")
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-
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- st.markdown('#### Clustering Details')
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-
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- # Horizontal layout for clustering metrics similar to "General Data Information"
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- st.metric(label="Silhouette Score", value="0.57744")
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- st.metric(label="Calinski-Harabasz", value="422.98")
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- st.metric(label="Davies-Bouldin", value="0.63446")
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  # Middle Column (White): 3D Cluster Model and Bar Chart
 
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  # Page configuration
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  st.set_page_config(page_title="DeepInsightz", page_icon=":bar_chart:", layout="wide")
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  # Custom CSS for dynamic theme styling
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  # Streamlit detects light and dark mode automatically via the user's settings in Hugging Face Spaces
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  if st.get_option("theme.base") == "dark":
 
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  </style>
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  """, unsafe_allow_html=True)
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+ # Navigation menu
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+ with st.sidebar:
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+ st.sidebar.title("DeepInsightz")
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+ page = st.sidebar.selectbox("Select the tool you want to use", ["Summary", "Customer Analysis", "Articles Recommendations"])
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+
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  # Load CSV files at the top
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  df = pd.read_csv("df_clean.csv")
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  nombres_proveedores = pd.read_csv("nombres_proveedores.csv", sep=';')
 
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  st.metric(label="Customers Analysed", value="3.000")
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  st.metric(label="Unique Products Sold", value="10.702")
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  st.metric(label="Total Sales Instances", value="764.396")
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+ st.metric(label="Range of Dates", value="2021-2023")
 
 
 
 
 
 
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  # Middle Column (White): 3D Cluster Model and Bar Chart