-
Notifications
You must be signed in to change notification settings - Fork 0
/
app.py
123 lines (102 loc) · 3.36 KB
/
app.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
import pandas as pd
import plotly_express as px
import streamlit as st
st.set_page_config(page_title='Sales information ',
page_icon=":bar_chart:",layout="wide")
def get_data_from_excel():
df = pd.read_excel(
io="supermarkt_sales.xlsx",
engine="openpyxl",
sheet_name="Sales",
skiprows=3,
usecols="B:R",
nrows=1000,
)
# Add 'hour' column to dataframe
df["hour"] = pd.to_datetime(df["Time"], format="%H:%M:%S").dt.hour
return df
df = get_data_from_excel()
#get the overview of the data
st.dataframe(df)
print(df)
st.dataframe(df)
sidebar
st.sidebar.header("Search ")
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"
)
# ---- MAINPAGE ----
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_sale_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_sale_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)",
xaxis=(dict(showgrid=False))
)
# 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)),
)
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)
# ---- 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)