Commit
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6a5ab3f
1
Parent(s):
719ba38
Update app.py
Browse files
app.py
CHANGED
@@ -8,6 +8,46 @@ import sweetviz as sv
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from autoviz.AutoViz_Class import AutoViz_Class
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from traceml.summary.df import DataFrameSummary
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def generate_report(file, type):
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df = pd.read_csv(file) if file.name.endswith(".csv") else pd.read_excel(file)
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@@ -87,7 +127,7 @@ def generate_report(file, type):
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return temp_file1.name ,temp_file3.name ,dfviz,sd1
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with gr.Blocks() as cluster:
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@@ -107,11 +147,14 @@ with gr.Blocks() as cluster:
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gr.HTML(value="""<h1 style="color: #3399FF; text-shadow: 1px 1px 2px #ddd;">SWEETVIZ REPORT</h1>""")
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out3=gr.File(label="Download CSV")
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with gr.Column():
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gr.Markdown("Uploaded File")
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dataframe1=gr.Dataframe()
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with gr.Column():
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gr.Markdown("Columns Analysis")
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dataframe2=gr.Dataframe()
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btn.click(generate_report,inputs=[file],outputs=[out1,out3,dataframe1,dataframe2])
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cluster.launch()
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from autoviz.AutoViz_Class import AutoViz_Class
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from traceml.summary.df import DataFrameSummary
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def variable_table(df):
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"""
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Analyzes a DataFrame and categorizes variables with colorful HTML formatting.
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Args:
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df (pandas.DataFrame): The DataFrame to analyze.
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Returns:
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str: HTML code representing the analysis results with colorful highlights.
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"""
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# Analyze variable types
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categorical_vars = df.select_dtypes(include=['category', 'object']).columns.tolist()
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numerical_vars = df.select_dtypes(include=['int64', 'float64']).columns.tolist()
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text_vars = df.select_dtypes(include=['object']).difference(categorical_vars).tolist()
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# Build HTML table with styles
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table_style = 'border: 1px solid #ddd; border-collapse: collapse; text-align: left; font-size: 14px;'
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header_style = 'background-color: #f2f2f2; padding: 5px 10px;'
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data_style = 'padding: 5px 10px; border-bottom: 1px solid #ddd;'
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category_color = '#90ee90' # Light green for categorical
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numerical_color = '#add8e6' # Light blue for numerical
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text_color = '#ffd9b3' # Light yellow for text
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html = f"<table style='{table_style}'>"
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html += f"<tr><th style='{header_style}'>Variable Type</th><th style='{header_style}'>Columns</th></tr>"
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# Add rows for each variable type with coloring
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if categorical_vars:
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html += f"<tr style='background-color: {category_color};'><td>Categorical</td><td style='{data_style}'>{', '.join(categorical_vars)}</td></tr>"
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if numerical_vars:
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html += f"<tr style='background-color: {numerical_color};'><td>Numerical</td><td style='{data_style}'>{', '.join(numerical_vars)}</td></tr>"
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if text_vars:
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html += f"<tr style='background-color: {text_color};'><td>Text</td><td style='{data_style}'>{', '.join(text_vars)}</td></tr>"
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# Handle cases where no variables are found
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if not (categorical_vars or numerical_vars or text_vars):
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html += "<tr><td>No variables found!</td></tr>"
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html += "</table>"
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return html
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def generate_report(file, type):
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df = pd.read_csv(file) if file.name.endswith(".csv") else pd.read_excel(file)
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return temp_file1.name ,temp_file3.name ,variable_table(df),dfviz,sd1
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with gr.Blocks() as cluster:
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gr.HTML(value="""<h1 style="color: #3399FF; text-shadow: 1px 1px 2px #ddd;">SWEETVIZ REPORT</h1>""")
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out3=gr.File(label="Download CSV")
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with gr.Column():
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gr.Markdown("***Uploaded File***")
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var=gr.HTML()
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with gr.Column():
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gr.Markdown("#Uploaded File")
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dataframe1=gr.Dataframe()
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with gr.Column():
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gr.Markdown("#Columns Analysis")
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dataframe2=gr.Dataframe()
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btn.click(generate_report,inputs=[file],outputs=[out1,out3,var,dataframe1,dataframe2])
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cluster.launch()
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