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""" |
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Created on Fri Jan 13 15:39:48 2023 |
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@author: Lenovo |
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""" |
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import pandas as pd |
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import numpy as np |
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import matplotlib.pyplot as plt |
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import plotly.express as px |
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import streamlit as st |
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import plotly.graph_objects as go |
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import seaborn as sns |
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@st.cache |
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def load_data(): |
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df=pd.read_csv(r"C:\Users\Lenovo\Downloads\new_data.csv") |
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return df |
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df=load_data() |
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def calculate_total_sales(sales_data): |
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total_sales = df['Sales'].sum() |
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return total_sales |
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def Sales_dashboard(): |
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st.title(":bar_chart: Sales Dashboard") |
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st.markdown("##") |
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st.sidebar.subheader("Please Filter Here:") |
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category_type = st.sidebar.multiselect("Select the Category:", |
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options=df["Category"].unique(), |
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default=df["Category"].unique()) |
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region_type = st.sidebar.multiselect("Select the Region:", |
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options=df["Region"].unique(), |
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default=df['Region'].unique() |
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) |
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df_selection = df.query( |
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"Category ==@category_type & Region == @region_type") |
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Total_sales = int(df_selection['Sales'].sum()) |
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Total_profit = int(df_selection['Profit'].sum()) |
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st.write("Showing Results Based on Filter:") |
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left_column, middle_column, right_column= st.columns(3) |
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with left_column: |
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st.subheader("Total Sales:") |
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st.subheader(f"Rs {Total_sales:,}") |
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with middle_column: |
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st.subheader("Total Profit:") |
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st.subheader(f"Rs {Total_profit:,}") |
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with right_column: |
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st.subheader("Profit margin:") |
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profit_margin = Total_profit / Total_sales |
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st.subheader(f"{profit_margin:.2%}") |
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st.markdown("""---""") |
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sales_by_product_line = ( |
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df_selection.groupby(by=["Category"]).sum()[["Sales"]].sort_values(by="Sales") |
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) |
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fig_product_sales = px.bar( |
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sales_by_product_line, |
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x="Sales", |
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y=sales_by_product_line.index, |
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orientation="h", |
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title="<b>Sales by Product Line</b>", |
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color_discrete_sequence=["#0083B8"] * len(sales_by_product_line), |
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template="plotly_white", |
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) |
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fig_product_sales.update_layout( |
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plot_bgcolor="rgba(0,0,0,0)", |
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xaxis=(dict(showgrid=False)) |
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) |
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profit_by_region = df_selection.groupby(by=["Region"]).sum()[["Profit"]] |
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regionly_profit = px.bar( |
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profit_by_region, |
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x=profit_by_region.index, |
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y="Profit", |
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title="<b>Profit by region by </b>", |
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color_discrete_sequence=["#0083B8"] * len(profit_by_region), |
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template="plotly_white", |
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) |
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regionly_profit.update_layout( |
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xaxis=dict(tickmode="linear"), |
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plot_bgcolor="rgba(0,0,0,0)", |
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yaxis=(dict(showgrid=False)), |
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) |
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left_column, right_column = st.columns(2) |
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left_column.plotly_chart(regionly_profit, use_container_width=True) |
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right_column.plotly_chart(fig_product_sales, use_container_width=True) |
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st.subheader("Click on buttons to see visuals") |
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if st.button('Show yearly Profit'): |
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chart2= st.bar_chart(df.groupby('year')['Profit'].sum()) |
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if st.button('Show City Sales Chart'): |
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chart = st.bar_chart(df.groupby('City')['Sales'].sum().sort_index(ascending=False)) |
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if st.button('Show sub-Category Sales'): |
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chart1 = st.bar_chart(df.groupby('Sub Category')['Sales'].sum().sort_index(ascending=False)) |
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st.markdown("""---""") |
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return Sales_dashboard() |
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