dataprincess commited on
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74f22c0
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1 Parent(s): 623c2aa

Update app.py

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Files changed (1) hide show
  1. app.py +2 -2
app.py CHANGED
@@ -67,7 +67,7 @@ if user_type == 'New User':
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  'Processor Brand', 'SSD', 'RAM (in GB)', 'RAM Type', 'Expandable Memory',
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  'Operating System', 'Touchscreen', 'Screen Size (in inch)', 'Weight (in kg)',
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  'Refresh Rate', 'screen_resolution', 'company', 'Storage', 'Processor name',
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- 'CPU_ranking', 'battery_backup', 'gpu name ', 'gpu_benchmark']]
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  # Hyperlink the 'click to buy' text for the link column
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  recommendations_table['link'] = recommendations_table['link'].apply(lambda x: f"[click to buy]({x})")
@@ -90,7 +90,7 @@ elif user_type == 'Existing User':
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  'Processor Brand', 'SSD', 'RAM (in GB)', 'RAM Type', 'Expandable Memory',
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  'Operating System', 'Touchscreen', 'Screen Size (in inch)', 'Weight (in kg)',
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  'Refresh Rate', 'screen_resolution', 'company', 'Storage', 'Processor name',
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- 'CPU_ranking', 'battery_backup', 'gpu name ', 'gpu_benchmark']]
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  # Hyperlink the 'click to buy' text for the link column
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  recommendations_table['link'] = recommendations_table['link'].apply(lambda x: f"[click to buy]({x})")
 
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  'Processor Brand', 'SSD', 'RAM (in GB)', 'RAM Type', 'Expandable Memory',
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  'Operating System', 'Touchscreen', 'Screen Size (in inch)', 'Weight (in kg)',
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  'Refresh Rate', 'screen_resolution', 'company', 'Storage', 'Processor name',
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+ 'CPU_ranking', 'battery_backup', 'gpu name ', 'gpu_benchmark', 'link']]
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  # Hyperlink the 'click to buy' text for the link column
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  recommendations_table['link'] = recommendations_table['link'].apply(lambda x: f"[click to buy]({x})")
 
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  'Processor Brand', 'SSD', 'RAM (in GB)', 'RAM Type', 'Expandable Memory',
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  'Operating System', 'Touchscreen', 'Screen Size (in inch)', 'Weight (in kg)',
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  'Refresh Rate', 'screen_resolution', 'company', 'Storage', 'Processor name',
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+ 'CPU_ranking', 'battery_backup', 'gpu name ', 'gpu_benchmark', 'link']]
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  # Hyperlink the 'click to buy' text for the link column
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  recommendations_table['link'] = recommendations_table['link'].apply(lambda x: f"[click to buy]({x})")