Duplicate from Chitranshu/Dashboard-Dmart

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
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+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
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+*.pickle filter=lfs diff=lfs merge=lfs -text
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+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

Dockerfile

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+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+RUN python3 -m pip install --no-cache-dir --upgrade pip
+RUN python3 -m pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["panel", "serve", "/code/app.py", "--address", "0.0.0.0", "--port", "7860",  "--allow-websocket-origin", "*"]
+
+RUN mkdir /.cache
+RUN chmod 777 /.cache
+RUN mkdir .chroma
+RUN chmod 777 .chroma

README.md

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+---
+title: Dmart-Dashboard
+emoji: 📊
+colorFrom: green
+colorTo: green
+sdk: docker
+pinned: false
+duplicated_from: Chitranshu/Dashboard-Dmart
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import pandas as pd
+import numpy as np
+import panel as pn
+pn.extension('tabulator')
+
+import hvplot.pandas
+
+project_data = pd.read_csv(r'DMart.csv')
+project_data.columns
+project_data.info()
+project_data.describe()
+project_data.isna().sum()
+project_data.shape
+project_data['Brand'] = project_data['Brand'].fillna('others')
+project_data.isna().sum()
+project_data = project_data.dropna()
+project_data.isna().sum()
+df = pd.DataFrame(project_data)
+idf = df.interactive()
+df.groupby(by=["SubCategory","Quantity"], dropna=False, sort=True).sum()
+import pandas as pd
+import panel as pn
+import hvplot.pandas
+import seaborn as sns
+import pandas as pd
+import seaborn as sns
+import hvplot.pandas
+import panel as pn
+
+# Assuming your dataset is stored in a DataFrame called 'df'
+
+# Create an interactive DataFrame
+idf = df.interactive()
+
+# Define Panel widgets for Top 10 Brands and Top 10 Categories
+brand_count = df['Brand'].value_counts().nlargest(10)
+category_count = df['Category'].value_counts().nlargest(10)
+
+# Define the hvplot charts with increased size
+brand_chart = brand_count.hvplot.bar(rot=90, title='Top 10 Brands', color=['#206b33'], width=800, height=400)  # Different shades of green
+category_chart = category_count.hvplot.bar(rot=90, title='Top 10 Categories', color=['#206b33'], width=800, height=400)
+
+# Create brand_price and category_price dictionaries
+brand_price = {}
+category_price = {}
+
+def brand_and_top_price():
+    for index, row in project_data.iterrows():
+        if row["Brand"] in brand_price:
+            if brand_price.get(row["Brand"]) < row["Price"]:
+                brand_price[row["Brand"]] = row["Price"]
+        else:
+            brand_price[row["Brand"]] = row["Price"]
+            
+def category_and_top_price():
+    for index, row in project_data.iterrows():
+        if row["Category"] in category_price:
+            if category_price.get(row["Category"]) < row["Price"]:
+                category_price[row["Category"]] = row["Price"]
+        else:
+            category_price[row["Category"]] = row["Price"]
+            
+brand_and_top_price()
+category_and_top_price()
+project_data_interactive = project_data.interactive()
+idf = df.interactive()
+
+# Define Panel widgets
+category_1 = project_data['Category'].value_counts().nlargest(10)
+brand_1 = project_data["Brand"].value_counts().nlargest(15).sort_values(ascending=False)
+# Define the hvplot charts
+category_chart1 = category_1.hvplot.bar(rot=90, title='Category Distribution', color=['#206b33'], width=800, height=400)
+brand_chart1 = brand_1.hvplot.bar(rot=90, title='Brand Count Distribution (Top 15)', color=['#206b33'], width=800, height=400)
+price_chart = df.hvplot(y='Price', color='#006400', width=800, height=400)
+discounted_price_chart = df.hvplot(y='DiscountedPrice', color='#006400', width=800, height=400)
+brand_price = dict(sorted(brand_price.items(), key=lambda item: item[1], reverse=True))
+category_price = dict(sorted(category_price.items(), key=lambda item: item[1], reverse=True))
+
+df_brand = pd.DataFrame(brand_price.items(), columns=['Brand', 'Price']).head(20)
+df_category = pd.DataFrame(category_price.items(), columns=['Category', 'Price']).head(20)
+
+# Create a reversed green color palette
+green_palette = sns.color_palette('Greens', n_colors=20)
+reversed_palette = list(reversed(green_palette))
+
+# Create brand bar chart using hvPlot
+brand_price_chart = df_brand.hvplot.bar(x='Brand', y='Price', rot=90, color=reversed_palette,
+                                    title='Top Price in Every Brand', xlabel='Brand', ylabel='Price',
+                                    width=800, height=400)
+
+# Create category bar chart using hvPlot
+category_price_chart = df_category.hvplot.bar(x='Category', y='Price', rot=90, color=green_palette[::-1],
+                                           title='Top Price in Every Category', xlabel='Category', ylabel='Price',
+                                           width=800, height=400)
+
+# Define Panel widgets
+yaxis_radio = pn.widgets.RadioButtonGroup(
+    name='Y axis',
+    options=['Top 10 Brands', 'Top 10 Categories', 'Top Price Brands', 'Top Price Categories', 'Category Distribution', 'Brand Count Distribution', 'Price', 'DiscountedPrice'],
+    button_type='success',
+    inline=True
+)
+
+# Define the Panel layout
+panel_layout = pn.Column(
+    yaxis_radio
+)
+
+# Define the callback function for the radio button
+def update_chart(event):
+    if event.new == 'Top 10 Brands':
+        panel_layout[1:] = [brand_chart]
+    elif event.new == 'Top 10 Categories':
+        panel_layout[1:] = [category_chart]
+    elif event.new == 'Top Price Brands':        
+        panel_layout[1:] = [brand_price_chart]
+    elif event.new == 'Top Price Categories':
+        panel_layout[1:] = [category_price_chart]
+    elif event.new == 'Category Distribution':
+        panel_layout[1:] = [category_chart1]
+    elif event.new == 'Brand Count Distribution':
+        panel_layout[1:] = [brand_chart1]
+    elif event.new == 'Price':
+        panel_layout[1:] = [price_chart]
+    elif event.new == 'DiscountedPrice':
+        panel_layout[1:] = [discounted_price_chart]
+
+yaxis_radio.param.watch(update_chart, 'value')
+
+# Display the initial chart
+panel_layout.append(brand_chart)
+
+# Display the Panel layout
+panel_layout
+dashboard = panel_layout
+import panel as pn
+pn.extension()  # Add this line to load the Panel extension
+
+# Layout using Template
+template = pn.template.FastListTemplate(
+    title='D-mart Products Analysis Dashboard', 
+    sidebar=[
+        pn.pane.PNG('Dmart.png', sizing_mode='scale_both'),
+        pn.pane.Markdown("# Key Performance Indicators (KPIs) of the EDA"),  
+        pn.pane.Markdown("1. Count of Brands: The count of each brand, indicating brand popularity or representation in the dataset."),
+        pn.pane.Markdown("2. Count of Prices: The count of different price values, providing insights into price distribution."),
+        pn.pane.Markdown("3. Count of Categories: The count of each category, helping understand the distribution of products across categories."),
+        pn.pane.Markdown("4. Price Distribution: The density plot shows the distribution of prices, allowing analysis of price ranges and outliers."),
+        pn.pane.Markdown("5. Top Price in Every Brand: Identifies the brands with the highest prices, indicating premium or luxury brands."),
+        pn.pane.Markdown("6. Top Price in Every Category: Shows the categories with the highest prices, providing insights into expensive product categories."),
+        pn.pane.Markdown("7. Grouping and Summarizing: Summarizes the data by grouping based on 'SubCategory' and 'Quantity,' enabling analysis of aggregated metrics."),
+        pn.pane.Markdown("8. Price Distribution (Discounted vs. Original): Compares the distributions of discounted and original prices, offering insights into pricing strategies and discounts.")
+    ],
+    main = [pn.Row(pn.Column(dashboard)),
+            pn.Row(pn.pane.Markdown("DMart is a one-stop supermarket chain that aims to offer customers a wide range of basic home and personal products under one roof. Each DMart store stocks home utility products - including food, toiletries, beauty products, garments, kitchenware, bed and bath linen, home appliances and more - available at competitive prices that our customers appreciate. Our core objective is to offer customers good products at great value.DMart was started by Mr. Radhakishan Damani and his family to address the growing needs of the Indian family. From the launch of its first store in Powai in 2002, DMart today has a well-established presence in 327 locations across India. With D-marts mission is to be the lowest priced retailer in the regions we operate, our business continues to grow with new locations planned in more cities.The supermarket chain of DMart stores is owned and operated by Avenue Supermarts Ltd. (ASL). The company has its headquarters in Mumbai.The brands D Mart, D Mart Minimax, D Mart Premia, D Homes, Dutch Harbour, etc are brands owned by ASL.")),
+            pn.Row(pn.pane.Markdown("Designed and Developed with ❤️ by Chitranshu Nagdawane © 2023"))
+           ],
+    accent_base_color="#206b33",
+    header_background="#206b33"
+)
+
+template.servable()
+
+
+
+

requirements.txt

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+panel
+jupyter
+numpy
+pandas
+hvplot
+bokeh
+seaborn