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app.py
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app.py
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import streamlit as st
import folium as f
import pandas as pd
import numpy as np
import os
from plotly import graph_objects as go
from plotly.subplots import make_subplots
from streamlit_folium import folium_static
import folium
from streamlit_option_menu import option_menu
import streamlit.components.v1 as components
import matplotlib.pyplot as plt
import plotly.express as px
import chart_studio
import chart_studio.plotly as py
username = 'hrishi332'
api_key = 'CFUwESfbKWWspeJJ8ye8'
chart_studio.tools.set_credentials_file(username=username, api_key=api_key)
#Then go for the analysis stuff
upload=st.sidebar.file_uploader(label="Upload Crime Record file in csv format", type=["csv"])
#df=pd.read_csv('Crimes_-_2001_to_Present.csv')
df1=pd.read_csv('Police_Stations.csv')
df2=pd.read_csv('chattisgarh.csv')
df3=pd.read_csv('crime.csv')
df3.dropna()
selected = option_menu(
menu_title=None,
options=["Crime Hotspot", "About us"],
icons=["geo-alt", "pin-map", "bar-chart", "info-circle"],
menu_icon="cast",
default_index=0,
orientation="horizontal",
)
#df4=pd.read_csv('Chicago_Crimes_2012_to_2017.csv')
#df4['Date']= pd.to_datetime(df4['Date'], format='%m/%d/%Y %I:%M:%S %p')
#df4['index'] = pd.DatetimeIndex(df4['Date'])
if (selected=="Crime Hotspot"):
global df
temp=False
if upload is not None:
try:
df=pd.read_csv(upload)
temp=True
except Exception as e:
print(e)
try:
if temp:
#st.markdown("<script>img.style.visibility = 'hidden';</script>", unsafe_allow_html=True)
#st.markdown("<style>img{z-index: -1;}</style>", unsafe_allow_html=True)
m= f.Map(location=[41.70,-87.67], zoom_start=12)
tooltip="Click for info"
f.TileLayer('Stamen Terrain').add_to(m)
f.TileLayer('Stamen Toner').add_to(m)
f.TileLayer('Stamen Water Color').add_to(m)
f.TileLayer('cartodbpositron').add_to(m)
f.TileLayer('cartodbdark_matter').add_to(m)
f.LayerControl().add_to(m)
df=df.dropna()
#year=st.sidebar.selectbox("Select the Year: ", df["Year"].drop_duplicates().sort_values().tolist(), 0)
year=st.sidebar.slider("Select the year range: ", 2001, 2022, (2015, 2022))
#type1=st.sidebar.selectbox("Type of Crime: ", df["Type"].unique().tolist(), 0)
type1= st.sidebar.multiselect("Type of Crime: ", df.Type.unique().tolist())
dist=st.sidebar.selectbox("Select the District: ", df["District"].drop_duplicates().sort_values().tolist(), 0)
#def fun1():
# for x in range(0, len(df)):
# if ((df.iloc[x]["Type"]==type1) and (df.iloc[x]["District"]==dist) and (df.iloc[x]["Year"]<=year[0]) and (df.iloc[x]["Year"]<=year[1])):
# f.CircleMarker(location=[df.iloc[x]['Latitude'], df.iloc[x]['Longitude']], radius=25, popup=df.iloc[x]["Type"], color=df.iloc[x]["color1"], fill=True, fill_color=df.iloc[x]["color2"]).add_to(m)
def fun1(p, color1, color2):
df11=df[df["Type"]==p]
for x in range(0, len(df11)):
if ((df11.iloc[x]["District"]==dist) and (df11.iloc[x]["Year"]<=year[0]) and (df11.iloc[x]["Year"]<=year[1])):
f.CircleMarker(location=[df11.iloc[x]['Latitude'], df11.iloc[x]['Longitude']], radius=25, popup=df11.iloc[x]["Type"], color=color1, fill=True, fill_color=color2).add_to(m)
for p in range(len(type1)):
color1=['#ff005a',
'#AB96FF',
'#FCE49C',
'#FE9A65',
'#7BFC90',
'#CFFC8F',
'#A5FCD4',
'#95FDEA',
'#FF785A',
'#FF785A',
'#EF511F',
'#F9B0A5',
'#8FBDFF',
'#FF5244',
'#FF8861',
'#FF81C9',
'#FAFC87',
'#9BFBB4',
'#737BFF',
'#FDFD89',
'#FAEB70',
'#FE9491',
'#F9C4C2',
'#D1F9C2',
'#CDFEC0',
'#E74A31',
'#FCE096']
color2=['#eb0c83',
'#7251F9',
'#FBCF4F',
'#FD7C37',
'#11F537',
'#B6FA54',
'#6CFFBA',
'#5FFCE0',
'#FC4B24',
'#FC4B24',
'#B63208',
'#DE7E6F',
'#1B73F3',
'#F71300',
'#FF521B',
'#FF119A',
'#E1E412',
'#1AF953',
'#0915CF',
'#FCFC41',
'#F7DE06',
'#B60904',
'#F10C05',
'#5EE12D',
'#75F951',
'#DD270B',
'#FBC127']
fun1(type1[p], color1[p], color2[p])
st.markdown("<style> code { display: none; margin: 0 !important; padding: 0 !important; width: 0px !important; height: -50% !important;} </style>", unsafe_allow_html=True)
st.markdown("<style> .css-1v0mbdj img {position: absolute; top: -400px; left: 50%; width: 500px; height: 500px; margin-top: -250px; margin-left: -250px;} </style>", unsafe_allow_html=True)
sum1=0
for x in range(len(type1)):
df4=df[df["Type"]==type1[x]]
sum1+=len(df4)
total=sum1
station=len(df1)
sum2=0
for x in range(len(type1)):
df4=df[df["Type"]==type1[x]]
df5=df4[df4["District"]==dist]
sum2+=len(df5)
crime=sum2
left_column, middle_column, right_column = st.columns(3)
with left_column:
st.markdown(f"Total {type1} Crime Committed overall:")
st.title(f"{total}")
with right_column:
st.markdown(f"Total {type1} Crime Committed in the District no. {dist}:")
st.title(f"{crime}")
with middle_column:
st.markdown(f"Total police station in the city chicago :")
st.title(
station)
for x in range(len(type1)):
df11=df[df["Type"]==type1[x]]
df22=df11[df11["District"]==dist]
st.write(df22)
def fun2():
for x in range(0, len(df1)):
if len(df1.iloc[x]["DISTRICT NAME"])>0:
f.Marker([df1.iloc[x]['LATITUDE'], df1.iloc[x]['LONGITUDE']], popup=df1.iloc[x]["DISTRICT NAME"], tooltip=tooltip, icon=f.features.CustomIcon('policeman.png', icon_size=(50, 50))).add_to(m),
def fun3():
for x in range(0, len(df2)):
if len(df2.iloc[x]["Address"])>0:
f.Marker([df2.iloc[x]['LATITUDE'], df2.iloc[x]['LONGITUDE']], popup=df2.iloc[x]["Address"], tooltip=tooltip, icon=f.features.CustomIcon('policeman.png', icon_size=(50, 50))).add_to(m),
fun2()
fun3()
st.image("Suraksha.png")
folium_static(m, width=750, height=600)
df.Date = pd.to_datetime(df.Date, format='%m/%d/%Y %I:%M:%S %p')
df.index = pd.DatetimeIndex(df.Date)
df_type=list(df.Type.unique())[0:5]
type_count=[]
for x in range(len(df.Type.value_counts())):
type_count.append(int(df.Type.value_counts()[x]))
if x==4:
break
plot11=px.bar(data_frame=df, x=df_type, y=type_count, title="No. of Crimes by Type of Crime: ", color=type_count, color_continuous_scale=px.colors.sequential.Blues, template="plotly_dark")
py.plot(plot11, filename = 'plot11', auto_open=False)
# Top 5 place where
df_type=list(df.Where.unique())[0:5]
type_count1=[]
for x in range(len(df.Where.value_counts())):
type_count1.append(int(df.Where.value_counts()[x]))
if x==4:
break
plot2=px.bar(data_frame=df, x=df_type, y=type_count1, title="Where most of the crime occurred: ", color=type_count, color_continuous_scale=px.colors.sequential.Blues,labels=dict(x="Location", y="No. of crime"), template="plotly_dark")
py.plot(plot2, filename = 'plot2', auto_open=False)
#Map
fig1 = px.scatter_mapbox(df, lat="Latitude", lon="Longitude", color="Type",hover_data=["block"],
color_continuous_scale=px.colors.cyclical.IceFire, size_max=15, zoom=10)
fig1.update_layout(mapbox_style="open-street-map")
py.plot(fig1, filename = 'plot34', auto_open=False)
#Month
plot3=px.bar(data_frame=df, x=['Jan','Feb','Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'],
y=df.groupby([df.index.month]).size(), title="No. of occurrence of crime monthwise: ",
color=df.groupby([df.index.month]).size(),
color_continuous_scale=px.colors.sequential.Blues ,labels=dict(x="Days Of Week", y="No. of crime"),template="plotly_dark")
py.plot(plot3, filename = 'plot3', auto_open=False)
#days of week
plot4=px.bar(data_frame=df, x=['Monday','Tuesday','Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday'],
y=df.groupby([df.index.dayofweek]).size(), title="No. of occurrence of crime in days of a week: ",
color=df.groupby([df.index.dayofweek]).size(),
color_continuous_scale=px.colors.sequential.Blues ,labels=dict(x="Days Of Week", y="No. of crime"),template="plotly_dark")
py.plot(plot4, filename = 'plot4', auto_open=False)
#Arrest
#Which Type of Crime is more and arrest is done?
df_type=list(df_arrest.Type.unique())[0:5]
type_count2=[]
for x in range(len(df_arrest.Type.value_counts())):
type_count2.append(int(df_arrest.Type.value_counts()[x]))
if x==4:
break
plot111 = px.pie(df, values=type_count, names=df_type,title="% of Crime Occurence where the arrest is done: ", color=type_count, color_discrete_sequence=px.colors.sequential.Blues, template="plotly_dark")
py.plot(plot111, filename = 'plot1111', auto_open=False)
else:
#st.markdown("<style> #Hrishi { display: none; } </style><script></script>", unsafe_allow_html=True)
print(e)
st.subheader("Please upload the crime record data in this format:")
st.image("temp.png", caption="Format to be followed", width=400)
except Exception as e:
#a = """"""
#st.markdown("")
#a=temp.png
#st.markdown("<img src= "'+a'" id='a' alt='img'> ", unsafe_allow_html=True)
print(e)
st.subheader("Please upload the crime record data in this format:")
st.markdown('''------------------------Data Type-------------------------------- --------------Column Header Name Expected-------------
________________Date____________________ _____________Date_____________
Types of Crime/
Tool used to do crime/ Type
Type Any Details which
helps for investigation
District/Ward/Location/ District
District Block
Latitude Latitude
Longitude Longitude''')
#st.image("temp.png", caption="Format to be followed", width=400)
elif (selected=="About us"):
st.write("Made by Team: Four Bits")
col1, col2, col3 = st.columns(3)
with col1:
st.markdown('Ranjeet Saw')
st.image("Ranjeet (3).jpeg")
with col2:
st.markdown("Hrishikesh Yadav")
st.image("hrishi.jpeg")
with col3:
st.markdown("Abhishek Mishra")
st.image("abhishek.jpg")