datakota/Home.py at main · danielcpratama/datakota · GitHub

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
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183

# import libraries
import streamlit as st
from PIL import Image
from google.cloud import storage
import bcrypt
import datetime
from google.cloud import storage


# set page config
st.set_page_config(
    page_title="Home",
    layout="centered",
    page_icon= ":house:",
    menu_items= {'About':'Made by Daniel Caesar Pratama'},
    initial_sidebar_state= "collapsed"
)
# ------------------------------------------------------------------------------
# SET UP SIDEBAR
with st.sidebar:
    st.subheader('Contact us!')
    st.markdown("""
    [twitter](https://twitter.com/danielcaesarp)
    [instagram](https://instagram.com/datakota.app)
    [email](hi.datakota@gmail.com)
    [github](https://github.com/danielcpratama/datakota)

    """)


# ------------------------------------------------------------------------------
# SET UP TITLE
st.image('logo/logo.png')
st.title("Datakota")
st.subheader("Spatial Insights of Indonesian Cities")
st.write("Our curated spatial datasets and user-friendly analytic tools help businesses identify growth opportunities, optimize operations, and stay ahead of the competition.")
col_A, col_B = st.columns([1,2])
with col_A:
    if st.button('try datakota.explorer today', type='primary', use_container_width=True):
        st.switch_page("pages/datakota_explorer.py")
with col_B:
    st.caption('or scroll down to see our [other products](#our-products)')


# ------------------------------------------------------------------------------
# Hero
st.image("logo/hero.png", use_column_width=True)
# ------------------------------------------------------------------------------
# Introducing datakota.explorer
with st.container(border=False):
    st.subheader('Introducing datakota.explorer')
    st.markdown("""
                Explore demographic insights visualized spatially:
                age, jobs, religion, education level, gender, marital status, and more.
                """)
    col1, col2, col3 = st.columns([1,1,1])
    with col1:
        with st.container(border=True, height=280):
            st.markdown('##### Comprehensive ')
            st.image('logo/comprehensive.png')
            st.markdown('We provide a wide selection of variables gathered from various sources')

    with col2:
        with st.container(border=True, height=280):
            st.markdown('##### Granular ')
            st.image('logo/granular.png')
            st.markdown('We cover every nook & cranny of Indonesia up to Kelurahan level')

    with col3:
        with st.container(border=True, height=280):
            st.markdown('##### Intuitive ')
            st.image('logo/intuitive.png')
            st.markdown('Get insights quickly with our interactive maps & charts')

    st.subheader('what they say about datakota.explorer')

    st.markdown("👨🏽‍🦲      _datakota is cleaner & easier to use than government GIS geoportal!_ - twitter user")
    st.markdown("👧🏻      _datakota helped narrow down my research on informal economy!_ - Ms. KF")
    st.markdown("🙆🏽‍♂️      _I work in baby-care industry, and datakota helped me discover market potential in my province_ - Mr. FRB")
    st.markdown("""


    """)
if st.button('try datakota.explorer today', type='primary', use_container_width=False, key='trynow'):
        st.switch_page("pages/datakota_explorer.py")
st.markdown("""


    """)
# ------------------------------------------------------------------------------
# Product page
st.subheader('More Analytics Are Coming Soon', divider='grey', anchor='our-products')

col_l, col_r = st.columns([1,1])
# datakota.explorer

# datakota.retail
with col_l:
    with st.container(border=True, height=470):
        st.image("logo/kopi.png", use_column_width=True)
        st.subheader('🏪 datakota.retail', divider='grey')
        st.markdown("""
__Find the best location for your next restaurant, cafe, minimart and more using our location analysis tool__
""")
        with st.expander("learn more:"):
            st.markdown("""
- Identify customer demographic profile within a catchment area
- Analyse nearby competitors
- Understand your location accessibility
""")
        col_x, col_y = st.columns([1,1])
        with col_y:
            st.link_button('join waitlist',url='https://forms.gle/US1WirXFj5UNBx5GA', type='primary', use_container_width=True)

# datakota.housing
with col_r:
    with st.container(border=True, height=470):
        st.image("logo/house.png", use_column_width=True)
        st.subheader('🏠 datakota.housing', divider='grey')
        st.markdown("""
__buying a house is likely your biggest purchase-of-a-lifetime, don't choose the wrong location__

""")
        with st.expander("learn more:"):
            st.markdown("""
- compare comparable housing price in several locations
- estimate living cost in the area
- check disaster history
- check access to public transportation, school, healthcare, and parks
- check access to public service, i.e., water, electricity, internet
""")
        col_x, col_y = st.columns([1,1])
        with col_y:
            st.link_button('join waitlist', url= 'https://forms.gle/US1WirXFj5UNBx5GA', type='primary', use_container_width=True)

# datakota.enterprise

with st.container(border=True, height=540):
    st.image("logo/enterprise.png", use_column_width=True)
    st.subheader('💼 datakota.enterprise', divider='grey')
    st.markdown("""
__Customized spatial platform for your unique enterprise needs, from location intelligence, predictive analysis, and map visualization__

""")
    with st.expander("explore sectoral potential:"):
        st.markdown("""
- real estate market assessment
- healthcare analytics and facility planning
- supply chain optimization through network analysis
- geomarketing
""")
    col_x, col_y = st.columns([1,1])
    with col_y:
        st.link_button("let's talk", url = 'https://forms.gle/US1WirXFj5UNBx5GA', type='primary', use_container_width=True)


# ------------------------------------------------------------------------------
# Footer
st.divider()
st.subheader('Support Us!')
colA, colB = st.columns([2,1])
with colA:
    st.markdown('''
                - we are accepting donation through QRIS payment!
                - contribute a high quality dataset that you'd like the public to see! send us an email
                - follow us on social media & let us know how we are doing!
                ''')
    st.markdown("""


        [twitter](https://twitter.com/danielcaesarp) | [instagram](https://instagram.com/datakota.app)  | [email](hi.datakota@gmail.com)  | [github](https://github.com/danielcpratama/datakota)

        """)
    st.caption('&copy;datakota | datakota is a solo venture by Daniel Caesar Pratama')

with colB:
    st.image("logo/QRIS_small.jpg", width=200)