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| import streamlit as st | |
| import plotly.express as px | |
| import pandas as pd | |
| import numpy as np | |
| st.set_page_config( | |
| page_title="Crimes Visualizer", | |
| page_icon="🚨", | |
| layout="wide", | |
| initial_sidebar_state="expanded", | |
| ) | |
| st.markdown("<h1 style='text-align: centre; color: blue;'>UK CRIME'S VISUALIZER</h1>", | |
| unsafe_allow_html=True) | |
| lats_longs = {'avon_somerset' : [51.375801, -2.359904], 'bedfordshire' : [52.134832794, -0.46749813], 'cambridgeshire' : [52.204832514, 0.120166186], | |
| 'cheshire' : [53.2303, -2.7151], 'cleveland' : [54.48333, -0.91667], 'clumbria' : [54.328506, -2.743870], | |
| 'derbyshire' : [53.118755, -1.448822], 'devon_cornwall' : [50.3, -4.9], 'dorset' : [50.58821366195, -2.0649272858189], | |
| 'durhum' : [54.776100, -1.573300], 'dyfed_powys' : [52.1667, -4], 'essex' : [51.572376, -0.470009], 'gloucestershire' : [51.745735, -2.217758], | |
| 'gwent' : [51.581186, -3.030594], 'hampshire' : [51.150719, -0.973177], 'hertfordshire' : [51.817, -0.217], 'humberside' : [53.8, -0.5], 'kent' : [51.279999, 1.080000], | |
| 'lancashire' : [53.765762, -2.692337], 'leicestershire' : [52.633331, -1.133333], 'lincolnshire' : [53.234444, -0.538611], 'london' : [51.509865, -0.118092], 'merseyside' : [53.400002, -2.983333], 'norfolk' : [52.376492, 1.108394], 'north_wales' : [51.481583, -3.179090], | |
| 'north_yorkshire' : [53.958332, -1.080278], 'northamptonshire' : [52.240479, -0.902656], 'northern_ireland' : [54.607868, -5.926437], 'northumbria' : [55.166667, -2], 'nottinghampshire' : [53.12773, -11.0122699999999], 'south_wales' : [51.478970, -3.705163], | |
| 'south_yorkshire' : [53.383331, -1.466667], 'staffordshire' : [52.906002, -2.147913], 'suffolk' : [52.187248, 0.970780], 'surrey' : [51.215485, -0.631027], 'sussex' : [50.967941, 0.085831], 'thames_valley' : [51.5074, -0.1278], 'warwickshire' : [52.370876, -1.265032], | |
| 'west_mercia' : [52.6, -1.6], 'west_midlands' : [52.489471, -1.898575], 'west_yorkshire' : [53.801277, -1.548567], 'wiltshire' : [51.458057, -2.116074]} | |
| counties = st.selectbox('Select a County below', list(lats_longs.keys())) | |
| # but = st.button('SHOW') | |
| def county_select(county): | |
| path = "county\\{}.csv".format(county) | |
| crime = pd.read_csv(path) | |
| return crime | |
| crime = county_select(counties) | |
| st.markdown("<h4 style='text-align: centre; color: red;'>CRIMES ON MAP</h4>", | |
| unsafe_allow_html=True) | |
| map_crime = px.scatter_mapbox(crime, lat='Latitude', lon='Longitude', color='Crime type', | |
| title = 'CRIMES ON MAP', | |
| color_continuous_scale="Viridis", | |
| range_color=(0, 12), | |
| mapbox_style="carto-positron", | |
| zoom=7.5, center={"lat": lats_longs[counties][0], "lon": lats_longs[counties][1]}, | |
| opacity=0.5, animation_frame='Month', width=1200, # Set the width of the figure | |
| height=500,) | |
| map_crime.update_layout(margin={"r":0,"t":0,"l":0,"b":0}) | |
| st.plotly_chart(map_crime) | |
| st.markdown("<h4 style='text-align: centre; color: red;'>CRIMES WITH INTENSITIES</h4>", | |
| unsafe_allow_html=True) | |
| intensity = px.density_mapbox(crime, lat='Latitude', lon='Longitude', z='intensity', radius=10, width=1200, height=500, | |
| center=dict(lat=lats_longs[counties][0], lon=lats_longs[counties][1]), zoom=7.5, mapbox_style="open-street-map", animation_frame = 'Month', color_continuous_scale=["blue", "yellow"]) | |
| st.plotly_chart(intensity) | |
| st.markdown("<hr>", unsafe_allow_html=True) | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| yearcol1 = st.selectbox('Select Year', [2020, 2021, 2022, 2023], key = 'year1') | |
| most_common_crime = crime[crime['year'] == yearcol1]['Crime type'].value_counts().keys()[0].upper() | |
| st.markdown(f"**MOST COMMON TYPE OF CRIME IN {yearcol1} :** <span style='color: cyan;'>{most_common_crime}</span>", unsafe_allow_html=True) | |
| # st.write(f'MOST COMMON TYPE OF CRIME IN {yearcol1}: ', crime[crime['year'] == yearcol1]['Crime type'].value_counts().keys()[0].upper()) | |
| with col2 : | |
| yearcol2 = st.selectbox('Select Year', [2020, 2021, 2022, 2023], key = 'year2') | |
| no_crimes = str(crime[crime['year'] == yearcol2]['Crime type'].value_counts().values[0]) | |
| st.markdown(f"**NUMBER OF CRIMES OCCURRED IN {yearcol2} :** <span style='color: cyan;'>{no_crimes}</span>", unsafe_allow_html=True) | |
| # st.write(f'NUMBER OF CRIMES OCCURRED IN {yearcol2} : ', str(crime[crime['year'] == yearcol2]['Crime type'].value_counts().values[0])) | |
| st.markdown("<hr>", unsafe_allow_html=True) | |
| yearcol3 = st.selectbox('Select Year', [2020, 2021, 2022, 2023], key = 'year3') | |
| outcomes = crime[crime['year'] == yearcol3]['Last outcome category'].value_counts().keys()[0].upper() | |
| st.markdown(f"**MOST COMMON OUTCOME OF POLICE INVESTIGATION IN {yearcol3} :** <span style='color: cyan;'>{outcomes}</span>", unsafe_allow_html=True) | |
| # st.write(f'MOST COMMON OUTCOME OF POLICE INVESTIGATION IN {yearcol3}: ', crime[crime['year'] == yearcol3]['Last outcome category'].value_counts().keys()[0].upper()) | |
| st.markdown("<hr>", unsafe_allow_html=True) | |
| st.markdown("<h4 style='text-align: centre; color: red;'>CRIME COUNTS IN DIFFERENT MONTHS</h4>", | |
| unsafe_allow_html=True) | |
| yearcol44 = st.selectbox('Select Year', [2020, 2021, 2022, 2023], key = 'year4') | |
| scat = px.scatter(crime[crime['year'] == yearcol44], x = 'Crime type', y = 'counts', color = 'months', width=1200, height=500) | |
| st.plotly_chart(scat) | |
| st.markdown("<hr>", unsafe_allow_html=True) | |
| col3, col4 = st.columns(2) | |
| with col3: | |
| yearcol4 = st.selectbox('Select Year', [2020, 2021, 2022, 2023], key = 'year5') | |
| tot_crime_month = dict(crime[crime['year'] == yearcol4].groupby('months').counts.sum().sort_values(ascending = False)) | |
| first_pair = next(iter(tot_crime_month.items())) | |
| most_crime = str(first_pair[0]) | |
| st.markdown(f"**MOST CRIMES OCCURRED IN MONTH :** <span style='color: cyan;'>{most_crime}</span>", unsafe_allow_html=True) | |
| # st.write('MOST CRIMES OCCURRED IN MONTH : ', str(first_pair[0])) | |
| with col4: | |
| yearcol5 = st.selectbox('Select Year', [2020, 2021, 2022, 2023], key = 'year6') | |
| ints = str(np.mean(crime[crime['year'] == yearcol5]['intensity'])) | |
| st.markdown(f"**AVG INTENSITY OF CRIMES OCCURRED IN {yearcol5} :** <span style='color: cyan;'>{ints}</span>", unsafe_allow_html=True) | |
| # st.write(f"AVG INTENSITY OF CRIMES OCCURRED IN {yearcol5}", str(np.mean(crime[crime['year'] == yearcol5]['intensity']))) | |
| st.markdown("<hr>", unsafe_allow_html=True) | |
| st.markdown("<h4 style='text-align: centre; color: red;'>TYPES OF CRIMES AND THEIR DISTRIBUTION</h4>", | |
| unsafe_allow_html=True) | |
| yearcol6 = st.selectbox('Select Year', [2020, 2021, 2022, 2023], key = 'year7') | |
| pie = px.pie(crime[crime['year'] == yearcol6], names= 'Crime type', values='counts', width=1200, height=500) # 2021 | |
| st.plotly_chart(pie) | |
| st.markdown("<hr>", unsafe_allow_html=True) | |
| st.markdown("<h4 style='text-align: centre; color: red;'>MOST COMMON TYPES OF PLACES WHERE CRIMES OCCUR</h4>", | |
| unsafe_allow_html=True) | |
| yearcol7 = st.selectbox('Select Year', [2020, 2021, 2022, 2023], key = 'year8') | |
| ba = px.bar(pd.DataFrame(crime[crime['year'] == yearcol7].Location.value_counts()[:25]), y = 'count', width=1200, height=700) | |
| st.plotly_chart(ba) | |