Initial Commit

Author: CSFelix

5 - Julia/gitpersist

@@ -0,0 +1 @@
+gitpersist

6 - Streamlit/0 - Add Contact Form/app.py

@@ -0,0 +1,25 @@
+import streamlit as st
+
+# ---- HEADER ----
+st.header(':mailbox: Get in Touch With Me!')
+
+# ---- FORM ----
+# documentation: https://formsubmit.co
+contact_form = """
+<form action="https://formsubmit.co/[email protected]" method="POST">
+     <input type="hidden" name="_captcha" value="false">
+     <input type="text" name="name" placeholder="Your name" required>
+     <input type="email" name="email" placeholder="Your email" required>
+     <textarea name="message" placeholder="Details of your message" required></textarea>
+     <button type="submit">Send</button>
+</form>
+"""
+
+st.markdown(contact_form, unsafe_allow_html=True)
+
+# ---- FORM STYLE ----
+def local_css(file_name):
+	with open(file_name) as f:
+		st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)
+
+local_css('./style/style.css')

6 - Streamlit/0 - Add Contact Form/style/style.css

@@ -0,0 +1,24 @@
+input[type=text], input[type=email], textarea {
+  width: 100%;
+  padding: 12px;
+  border: 1px solid #ccc;
+  border-radius: 4px;
+  box-sizing: border-box;
+  margin-top: 6px;
+  margin-bottom: 16px;
+  resize: vertical;
+}
+
+button[type=submit] {
+  background-color: #0a394d;
+  color: white;
+  padding: 12px 20px;
+  border: none;
+  border-radius: 4px;
+  cursor: pointer;
+  transition:  all 0.3s ease;
+}
+
+button[type=submit]:hover {
+  opacity: 0.75;
+}

6 - Streamlit/1 - Transform Excel File in a Dashboard/README.md

@@ -0,0 +1,37 @@
+
+# Interactive Dashboard with Python – Streamlit
+
+Sales Dashboard built in Python and the Streamlit library to visualize Excel data.
+
+## Run the app
+```Powershell
+# vanilla terminal
+streamlit run app.py
+
+# quit
+ctrl-c
+```
+
+## Demo
+Sales Dashboard: https://www.salesdashboard.pythonandvba.com/
+
+## Screenshot
+
+![Dashboar Screenshot](https://content.screencast.com/users/jubbel3/folders/Snagit/media/64b4d64a-4e59-4bec-9f16-771eb1a99005/08.18.2021-19.50.jpg)
+
+
+## Author
+
+- Sven from Coding Is Fun
+- YouTube: https://youtube.com/c/CodingIsFun
+- Website: https://pythonandvba.com
+
+
+
+## Feedback
+
+If you have any feedback, please reach out to me at [email protected]
+
+
+![Logo](https://www.pythonandvba.com/banner-img)
+

6 - Streamlit/1 - Transform Excel File in a Dashboard/app.py

@@ -0,0 +1,150 @@
+import pandas as pd # pip install pandas openpyxl
+import streamlit as st # pip install streamlit
+import plotly.express as px # pip install plotly-express
+
+# Setting up the page
+#
+# Emojis: https://www.webfx.com/tools/emoji-cheat-sheet
+st.set_page_config(
+	page_title='Sales Dashboard'
+	, page_icon=':bar_chart:'
+	, layout='wide'
+)
+
+# Saving the dataframe into cache in order to
+# do not make streamlit reads the entire excel file
+# every time
+@st.cache
+def get_data_from_excel():
+	# Reading the file
+	df = pd.read_excel(
+		io='supermarkt_sales.xlsx'
+		, engine='openpyxl'
+		, sheet_name='Sales'
+		, skiprows=3
+		, usecols='B:R'
+		, nrows=1000
+	)
+	# Adding 'hour' column to dataframe
+	df['hour'] = pd.to_datetime(df['Time'], format='%H:%M:%S').dt.hour
+
+	return df
+
+df = get_data_from_excel()
+
+# ---- SIDEBAR ----
+st.sidebar.header('Please Filter Here:')
+
+city = st.sidebar.multiselect(
+	'Select the City:'
+	, options=df['City'].unique()
+	, default=df['City'].unique()
+)
+
+customer_type = st.sidebar.multiselect(
+	'Select the Customer Type:'
+	, options=df['Customer_type'].unique()
+	, default=df['Customer_type'].unique()
+)
+
+gender = st.sidebar.multiselect(
+	'Select the Gender:'
+	, options=df['Gender'].unique()
+	, default=df['Gender'].unique()
+)
+
+df_selection = df.query(
+	'City == @city & Customer_type == @customer_type & Gender == @gender'
+)
+
+#st.dataframe(df_selection)
+
+# ---- MAIN PAGE ----
+st.title(':bar_chart: Sales Dashboard')
+st.markdown('##')
+
+# TOP KPI's
+total_sales = int(df_selection['Total'].sum())
+average_rating = round(df_selection['Rating'].mean(), 1)
+star_rating = ':star:' * int(round(average_rating, 0))
+average_sales_by_transaction = round(df_selection['Total'].mean(), 2)
+
+left_column, middle_column, right_column = st.columns(3)
+
+with left_column:
+	st.subheader('Total Sales:')
+	st.subheader(f'US ${total_sales:,}')
+
+with middle_column:
+	st.subheader('Average Rating:')
+	st.subheader(f'{average_rating} {star_rating}')
+
+with right_column:
+	st.subheader('Average Sales Per Transaction:')
+	st.subheader(f'US ${average_sales_by_transaction}')
+
+st.markdown('----')
+
+# ---- SALES BY PRODUCT LINE [BAR CHART] ----
+sales_by_product_line = (
+	df_selection.groupby(by=['Product line']).sum()[['Total']].sort_values(by='Total')
+)
+
+fig_product_sales = px.bar(
+	sales_by_product_line
+	, x='Total'
+	, y=sales_by_product_line.index
+	, orientation='h'
+	, title='<b>Sales by Product Line</b>'
+	, color_discrete_sequence=['#0083b8'] * len(sales_by_product_line)
+	, template='plotly_white'
+)
+
+fig_product_sales.update_layout(
+	plot_bgcolor='rgba(0, 0, 0, 0)' # turning the background transparent
+	, xaxis=(dict(showgrid=False))
+)
+
+# st.plotly_chart(fig_product_sales)
+
+# ---- SALES BY HOUR [BAR CHART] ----
+sales_by_hour = df_selection.groupby(by=['hour']).sum()[['Total']]
+fig_hourly_sales = px.bar(
+	sales_by_hour
+	, x=sales_by_hour.index
+	, y='Total'
+	, title='<b>Sales by Hour</b>'
+	, color_discrete_sequence=['#0083b8'] * len(sales_by_hour)
+	, template='plotly_white'
+)
+fig_hourly_sales.update_layout(
+	xaxis=dict(tickmode='linear')
+	, plot_bgcolor='rgba(0,0,0,0)'
+	, yaxis=(dict(showgrid=False))
+)
+
+# st.plotly_chart(fig_hourly_sales)
+
+# ---- Adding the Charts ----
+left_column, right_column = st.columns(2)
+left_column.plotly_chart(fig_hourly_sales, use_container_width=True)
+right_column.plotly_chart(fig_product_sales, use_container_width=True)
+
+# ---- Adding DataFrame ----
+st.markdown('----')
+st.markdown('**DataSet**')
+st.dataframe(df_selection)
+
+# ---- HIDE STREAMLIT STYLE ----
+# hide_st_style = """
+# 	<style>footer {visibility: hidden;}</style>
+# """
+hide_st_style = """
+	<style>
+	#MainMenu {visibility: hidden;}
+	header {visibility: hidden;}
+	footer {visibility: hidden;}
+	</style>
+"""
+
+st.markdown(hide_st_style, unsafe_allow_html=True)

6 - Streamlit/1 - Transform Excel File in a Dashboard/requirements.txt

@@ -0,0 +1,4 @@
+openpyxl==3.0.10
+plotly==4.14.3
+pandas==1.4.3
+streamlit==1.12.0

6 - Streamlit/1 - Transform Excel File in a Dashboard/supermarkt_sales.xlsx

@@ -0,0 +1,123 @@
+import calendar
+from datetime import datetime
+
+import streamlit as st # pip install streamlit
+from streamlit_option_menu import option_menu # pip install streamlit-option-menu
+import plotly.graph_objects as go # pip install plotly
+
+import database as db # local import
+
+# ---- SETTINGS ----
+incomes = ['Salary', 'Blog', 'Other Income']
+expenses = ['Rent', 'Utilities', 'Groceries', 'Car', 'Other Expense', 'Saving']
+currency = 'USD'
+page_title = 'Income and Expense Tracker'
+page_icon = ':money_with_wings:'
+layout = 'centered' 
+
+st.set_page_config(
+	page_title=page_title
+	, page_icon=page_icon
+	, layout=layout
+)
+
+st.title(f'{page_title} {page_icon}')
+
+# ---- DROP DOWN VALUES FOR SELECTING THE PERIOD ----
+years = [datetime.today().year, datetime.today().year + 1]
+months = list(calendar.month_name[1:])
+
+# ---- DATABASE INTERFACE ----
+def get_all_periods():
+	items = db.fetch_all_periods()
+	periods = [item['key'] for item in items]
+	return periods
+
+# ---- HIDE STREAMLIT STYLE ----
+hide_st_style = """
+	<style>
+		#MainMenu {visibility: hidden;}
+		footer {visibility: hidden;}
+		header {visibility: hidden;}
+	</style>	
+"""
+st.markdown(hide_st_style, unsafe_allow_html=True)
+
+# ---- NAVIGATION MENU ----
+selected = option_menu(
+	menu_title=None
+	, options=['Data Entry', 'Data Visualization']
+	, icons=['pencil-fill', 'bar-chart-fill'] # https://icons.getbootstrap.com/
+	, orientation='horizontal'
+)
+
+# ---- INPUT & SAVE PERIODS ----
+if selected == 'Data Entry':
+	st.header(f'Data Entry in {currency}')
+
+	with st.form('entry_form', clear_on_submit=True):
+		col1, col2 = st.columns(2)
+		col1.selectbox('Select Month:', months, key='month')
+		col2.selectbox('Select Year:', years, key='year')
+
+		st.markdown('----')
+
+		with st.expander('Income'):
+			for income in incomes:
+				st.number_input(f'{income}:', min_value=0, format='%i', step=10, key=income)
+
+		with st.expander('Expenses'):
+			for expense in expenses:
+				st.number_input(f'{expense}:', min_value=0, format='%i', step=10, key=expense)
+
+		with st.expander('Comment'):
+			comment = st.text_area('', placeholder='Enter a comment here ...')
+
+
+		st.markdown('----')
+
+		submitted = st.form_submit_button('Save Data')
+		if submitted:
+			period = str(st.session_state['year']) + '_' + str(st.session_state['month'])
+			incomes = {income: st.session_state[income] for income in incomes}
+			expenses = {expense: st.session_state[expense] for expense in expenses}
+			db.insert_period(period, incomes, expenses, comment)
+			st.success('Data Saved!')
+
+# ---- PLOT PERIODS ----
+elif selected == 'Data Visualization':
+	st.header('Data Visualization')
+	with st.form('saved_periods'):
+		period = st.selectbox('Select a Period', get_all_periods())
+		submitted = st.form_submit_button('Plot Period')
+		if submitted:
+			period_data = db.get_period(period)
+			comment = period_data.get('comment')
+			expenses = period_data.get('expenses')
+			incomes = period_data.get('incomes')
+
+			# Metrics
+			total_income = sum(incomes.values())
+			total_expense = sum(expenses.values())
+			remaining_budget = total_income - total_expense
+			col1, col2, col3 = st.columns(3)
+			col1.metric('Total Income:', f'{total_income} {currency}')
+			col2.metric('Total Expense:', f'{total_expense} {currency}')
+			col3.metric('Remaining Budget:', f'{remaining_budget} {currency}')
+			st.text(f'Comment: {comment}')
+
+			# Sankey Plot
+			label = list(incomes.keys()) + ['Total Income'] + list(expenses.keys())
+			source = list(range(len(incomes))) + [len(incomes)] * len(expenses)
+			target = [len(incomes)] * len(incomes) + [label.index(expense) for expense in expenses]
+			value = list(incomes.values()) + list(expenses.values())
+
+			# Data to dict, dict to sankey
+			link = dict(source=source, target=target, value=value)
+			node = dict(label=label, pad=20, thickness=30, color='#e694ff')
+			data = go.Sankey(link=link, node=node)
+
+			# Plotting
+			fig = go.Figure(data)
+			fig.update_layout(margin=dict(l=0, r=0, t=5, b=5))
+			st.plotly_chart(fig, use_container_width=True)