├── Main.py
├── README.md
├── UI.py
├── __pycache__
    └── UI.cpython-311.pyc
├── data.xlsx
├── pages
    └── 🌎 Add Record.py
├── requirements.txt
└── style.css


/Main.py:
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  1 | import streamlit as st
  2 | import pandas as pd 
  3 | import streamlit.components.v1 as stc
  4 | import plotly.express as px
  5 | import time
  6 | from streamlit_option_menu import option_menu
  7 | from numerize.numerize import numerize
  8 | import plotly.express as px
  9 | import plotly.subplots as sp
 10 | import plotly.graph_objects as go
 11 | 
 12 | #page behaviour
 13 | st.set_page_config(page_title="Descriptive Analytics ", page_icon="🌎", layout="wide")  
 14 | 
 15 | #remove default theme
 16 | theme_plotly = None # None or streamlit
 17 | 
 18 |  
 19 | # CSS Style
 20 | with open('style.css')as f:
 21 |     st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html = True)
 22 | 
 23 | #load excel file
 24 | df=pd.read_excel('data.xlsx', sheet_name='Sheet1')
 25 | 
 26 | 
 27 | #2. switcher
 28 | st.sidebar.header("Please Filter Here:")
 29 | region= st.sidebar.multiselect(
 30 |     "Select the Region:",
 31 |     options=df["Region"].unique(),
 32 |     default=df["Region"].unique()
 33 | )
 34 | location = st.sidebar.multiselect(
 35 |     "Select the Location:",
 36 |     options=df["Location"].unique(),
 37 |     default=df["Location"].unique(),
 38 | )
 39 | construction = st.sidebar.multiselect(
 40 |     "Select the Construction:",
 41 |     options=df["Construction"].unique(),
 42 |     default=df["Construction"].unique()
 43 |      
 44 |     
 45 | )
 46 | df_selection = df.query(
 47 |     "Region == @region & Location ==@location & Construction == @construction"
 48 | )
 49 | 
 50 | #method/function
 51 | 
 52 | def HomePage():
 53 |   #1. print dataframe
 54 |  with st.expander("🧭 My database"):
 55 |   #st.dataframe(df_selection,use_container_width=True)
 56 |   shwdata = st.multiselect('Filter :', df_selection.columns, default=[])
 57 |   st.dataframe(df_selection[shwdata],use_container_width=True)
 58 | 
 59 |  #2. compute top Analytics
 60 |  
 61 |  total_investment = float(df_selection['Investment'].sum())
 62 |  investment_mode = float(df_selection['Investment'].mode())
 63 |  investment_mean = float(df_selection['Investment'].mean())
 64 |  investment_median= float(df_selection['Investment'].median()) 
 65 |  rating = float(df_selection['Rating'].sum())
 66 | 
 67 |  #3. columns
 68 |  total1,total2,total3,total4,total5 = st.columns(5,gap='large')
 69 |  with total1:
 70 | 
 71 |     st.info('Total Investment', icon="🔍")
 72 |     st.metric(label = 'sum TZS', value= f"{total_investment:,.0f}")
 73 |     
 74 |  with total2:
 75 |     st.info('Most frequently', icon="🔍")
 76 |     st.metric(label='Mode TZS', value=f"{investment_mode:,.0f}")
 77 | 
 78 |  with total3:
 79 |     st.info('Investment Average', icon="🔍")
 80 |     st.metric(label= 'Mean TZS',value=f"{investment_mean:,.0f}")
 81 | 
 82 |  with total4:
 83 |     st.info('Investment Marging', icon="🔍")
 84 |     st.metric(label='Median TZS',value=f"{investment_median:,.0f}")
 85 | 
 86 |  with total5:
 87 |     st.info('Ratings', icon="🔍")
 88 |     st.metric(label='Rating',value=numerize(rating),help=f"""Total rating: {rating}""")
 89 |     
 90 |  st.markdown("""---""")
 91 | 
 92 |  #graphs
 93 |  
 94 | def Graphs():
 95 |  total_investments = int(df_selection["Investment"].sum())
 96 |  average_rating = round(df_selection["Rating"].mean(), 1)
 97 |  star_rating = ":star:" * int(round(average_rating, 0))
 98 |  average_investment = round(df_selection["Investment"].mean(), 2)
 99 | 
100 | #1. simple bar graph
101 |  investment_by_businessType = (
102 |     df_selection.groupby(by=["BusinessType"]).count()[["Investment"]].sort_values(by="Investment")
103 |  )
104 |  fig_investment = px.bar(
105 |     investment_by_businessType,
106 |     x="Investment",
107 |     y=investment_by_businessType.index,
108 |     orientation="h",
109 |     title="Investment by Business Type",
110 |     color_discrete_sequence=["#0083B8"] * len(investment_by_businessType),
111 |     template="plotly_white",
112 |  )
113 | 
114 |  fig_investment.update_layout(
115 |     plot_bgcolor="rgba(0,0,0,0)",
116 |     xaxis=(dict(showgrid=False))
117 |  )
118 | 
119 | #2. simple line graph------------------
120 |  investment_by_state = df_selection.groupby(by=["State"]).count()[["Investment"]]
121 |  fig_state = px.line(
122 |     investment_by_state,
123 |     x=investment_by_state.index,
124 |      orientation="v",
125 |     y="Investment",
126 |     title="Investment by Region ",
127 |     color_discrete_sequence=["#0083B8"] * len(investment_by_state),
128 |     template="plotly_white",
129 |  )
130 |  fig_state.update_layout(
131 |     xaxis=dict(tickmode="linear"),
132 |     plot_bgcolor="rgba(0,0,0,0)",
133 |     yaxis=(dict(showgrid=False)),
134 |  )
135 | 
136 |  left_column, right_column,center = st.columns(3)
137 |  left_column.plotly_chart(fig_state, use_container_width=True)
138 |  right_column.plotly_chart(fig_investment, use_container_width=True)
139 | 
140 |  #pie chart
141 |  with center:
142 |   fig = px.pie(df_selection, values='Rating', names='State', title='Regions by Ratings')
143 |   fig.update_layout(legend_title="Regions", legend_y=0.9)
144 |   fig.update_traces(textinfo='percent+label', textposition='inside')
145 |   st.plotly_chart(fig, use_container_width=True, theme=theme_plotly)
146 | 
147 | #-----PROGRESS BAR-----
148 | 
149 | def ProgressBar():
150 |   st.markdown("""<style>.stProgress > div > div > div > div { background-image: linear-gradient(to right, #99ff99 , #FFFF00)}</style>""",unsafe_allow_html=True,)
151 |   target=3000000000
152 |   current=df_selection['Investment'].sum()
153 |   percent=round((current/target*100))
154 |   my_bar = st.progress(0)
155 | 
156 |   if percent>100:
157 |     st.subheader("Target 100 complited")
158 |   else:
159 |    st.write("you have ", percent, " % " ," of ", (format(target, ',d')), " TZS")
160 |    for percent_complete in range(percent):
161 |     time.sleep(0.1)
162 |     my_bar.progress(percent_complete + 1,text="Target percentage")
163 | 
164 | #-----SIDE BAR-----
165 |  
166 | def sideBar():
167 |  with st.sidebar:
168 |     selected=option_menu(
169 |         menu_title="Menu",
170 |          #menu_title=None,
171 |         options=["Home","Progress"],
172 |         icons=["house","eye"],
173 |         menu_icon="cast", #option
174 |         default_index=0, #option
175 |         )
176 |  if selected=="Home":   
177 |     try:
178 |      HomePage()
179 |      Graphs()
180 |     except:
181 |         st.warning("one or more options are mandatory ! ")
182 |      
183 |     
184 |  if selected=="Progress":
185 |    try:
186 |     ProgressBar()
187 |     Graphs()
188 |    except:
189 |     st.warning("one or more options are mandatory ! ")
190 |  
191 | #print side bar
192 | sideBar()
193 | 
194 | footer="""<style>
195 |  
196 | 
197 | a:hover,  a:active {
198 | color: red;
199 | background-color: transparent;
200 | text-decoration: underline;
201 | }
202 | 
203 | .footer {
204 | position: fixed;
205 | left: 0;
206 | height:5%;
207 | bottom: 0;
208 | width: 100%;
209 | background-color: #243946;
210 | color: white;
211 | text-align: center;
212 | }
213 | </style>
214 | <div class="footer">
215 | <p>Developed with  ❤ by <a style='display: block; text-align: center;' href="https://www.heflin.dev/" target="_blank">Samir.s.s</a></p>
216 | </div>
217 | """
218 | st.markdown(footer,unsafe_allow_html=True)
219 | 
220 | 


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/README.md:
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 1 | ![Untitled 10](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/6bbda7d9-9539-4daa-a1b3-85287abe8190)
 2 | ![Untitled 12](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/1b4a3b89-17bd-4238-bf7c-155324a4c737)
 3 | ![Untitled 13](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/8b8bf6f4-f9c8-4ac1-9180-da60bde0e854)
 4 | ![Untitled 15](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/71f07ae3-eb20-4481-9483-7a3266ced364)
 5 | ![Untitled 16](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/b36d4dba-a41a-49f7-9a85-e3045baf6aee)
 6 | ![Untitled 18](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/0223ce79-6398-4285-bc5e-9aa6ae8b9fa5)
 7 | ![Untitled 20](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/f381cf1e-fa25-4b21-b060-b4a51c8cab86)
 8 | ![2](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/f2590286-051e-4384-97d5-966499311cd6)
 9 | ![1](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/251cdd77-46df-45f8-9417-a7ae8e9f6264)
10 | ![3](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/82b47d47-ac59-4640-a33b-425826254032)
11 | ![4](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/29faedca-be29-4c65-8e85-2de48315542c)
12 | ![6](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/c3c05845-9d39-4ec0-a978-3ad70be19968)
13 | ![5](https://github.com/shamiraty/AnalyticsDashboard-with-Excel-file/assets/129072179/a7cfa34c-c15d-4ac5-89cd-2d34901386f1)
14 | 
15 | 


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/UI.py:
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 1 | import streamlit as st
 2 | def heading():
 3 |     st.markdown("""  
 4 |             
 5 |  <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@4.6.2/dist/css/bootstrap.min.css" integrity="sha384-xOolHFLEh07PJGoPkLv1IbcEPTNtaed2xpHsD9ESMhqIYd0nLMwNLD69Npy4HI+N" crossorigin="anonymous">
 6 | <div class="container-fluid">
 7 |     <div class="card shadow">
 8 |     
 9 |              
10 |      ⚛ Analytics Dashboard | Python & Streamlit 
11 |   </div>
12 | </div>
13 |  
14 | 
15 |  """, unsafe_allow_html=True)
16 | 
17 |  


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/__pycache__/UI.cpython-311.pyc:
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https://raw.githubusercontent.com/shamiraty/AnalyticsDashboard-with-Excel-file/325a0ecbef19d090aa8d8f21626420c35225997b/__pycache__/UI.cpython-311.pyc


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/data.xlsx:
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https://raw.githubusercontent.com/shamiraty/AnalyticsDashboard-with-Excel-file/325a0ecbef19d090aa8d8f21626420c35225997b/data.xlsx


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/pages/🌎 Add Record.py:
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 1 | import streamlit as st
 2 | import pandas as pd
 3 | import seaborn as sns
 4 | from UI import *
 5 | 
 6 | st.set_page_config(page_title="Descriptive Analytics ", page_icon="📈", layout="wide")  
 7 | heading()
 8 | 
 9 | if 'number_of_rows' not in st.session_state:
10 |     st.session_state['number_of_rows']=3
11 |     st.session_state['type']='Categorical'
12 |     
13 | 
14 | increment=st.sidebar.button('show more columns ➕')
15 | if increment:
16 |   st.session_state.number_of_rows +=1
17 | decrement=st.sidebar.button('show fewer columns ➖')
18 | if decrement:
19 |  st.session_state.number_of_rows -=1
20 | 
21 | df=pd.read_excel('data.xlsx', sheet_name='Sheet1')
22 | 
23 | 
24 |  
25 | 
26 | theme_plotly = None # None or streamlit
27 | 
28 | # Style
29 | with open('style.css')as f:
30 |     st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html = True)
31 | 
32 | 
33 | st.markdown("##")
34 | 
35 | st.sidebar.header("Add New Product")
36 | options_form=st.sidebar.form("Option Form")
37 | location=options_form.selectbox("Location",{"Urban","Rural"})
38 | state=options_form.selectbox("State",{"Dodoma","Kilimanjaro","Dar es Salaam","Kigoma","Iringa","Mwanza"})
39 | region=options_form.selectbox("Region",{"East","Midwest","Northeast","Central"})
40 | investment=options_form.number_input("Investment")
41 | construction=options_form.selectbox("Construction",{"Frame","Metal Clad","Fire Resist","Masonry"})
42 | businesstype=options_form.selectbox("Business Type",{"Manufacturing","Apartment","Office Bldg","Farming","Construction","Recreation","Hospitality","Organization","Retail","Other"})
43 | earthquake=options_form.selectbox("Earthquake",{"Yes","No"})
44 | flood=options_form.selectbox("Flood",{"Yes","No"})
45 | rating=options_form.number_input("Rating")
46 | add_data=options_form.form_submit_button(label="Add new record")
47 | 
48 | if add_data:
49 |  if investment  !="" or location !="":
50 |      df = pd.concat([df, pd.DataFrame.from_records([{ 
51 |          'Location': location,
52 |          'State':state,
53 |          'Region':region,
54 |          'Investment':int(investment),
55 |          'Construction':construction,
56 |          'BusinessType':businesstype,
57 |          'Earthquake':earthquake,
58 |          'Flood':flood,
59 |          'Rating':float(rating)
60 |          }])])
61 |      try:
62 |         df.to_excel("data.xlsx",index=False)
63 |      except:
64 |         st.warning("Close dataset")
65 |      st.success("New record has been added successfully !")
66 |  else:
67 |     st.sidebar.error("product name required")
68 | 
69 | 
70 | 
71 | #st.dataframe(df_selection,use_container_width=True)
72 | shwdata = st.multiselect('Filter :', df.columns, default=["Location","State","Region","Investment","Construction","BusinessType","Earthquake"])
73 | st.dataframe(df.tail(st.session_state['number_of_rows']),use_container_width=True,)
74 | 
75 |  
76 |  


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/requirements.txt:
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 1 | Markdown==3.4.3
 2 | markdown-it-py==2.2.0
 3 | MarkupSafe==2.1.2
 4 | matplotlib==3.7.1
 5 | numerize==0.12
 6 | numpy==1.23.5
 7 | oauthlib==3.2.2
 8 | openpyxl==3.1.2
 9 | opt-einsum==3.3.0
10 | packaging==23.1
11 | pandas==2.0.1
12 | pandas-profiling==3.2.0
13 | streamlit==1.22.0
14 | streamlit-apexjs==0.0.3
15 | streamlit-card==0.0.4
16 | streamlit-elements==0.1.0
17 | streamlit-option-menu==0.3.2
18 | streamlit-pandas-profiling==0.1.3
19 | plotly==5.14.1
20 | plotly-express==0.4.1
21 | scikit-learn==1.2.2
22 | seaborn==0.12.2
23 | pandas-profiling==3.2.0
24 | 


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/style.css:
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 1 | [data-testid=metric-container] {
 2 |     box-shadow: 0 0 4px #cccccc;
 3 |     padding: 10px;
 4 | }
 5 | 
 6 | .plot-container>div {
 7 |     box-shadow: 0 0 4px #cccccc;
 8 |     padding: 10px;
 9 |     
10 |    
11 | }
12 | 
13 | div[data-testid="stExpander"] div[role="button"] p
14 | {
15 |     font-size: 1.3rem;
16 |     color:rgb(235, 238, 238);
17 | }


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