app.py

import streamlit as st
import pandas as pd
import numpy as np
import pydeck as pdk
import plotly.express as px

st.title("Motor Vehicle Collicions in NewYork City")
st.markdown("This is a data dashboard that can be used to analyze accident reports in NYC 🗽💥🚗")

@st.cache(persist=True)
def data_load(nrows):
	data = pd.read_csv('Motor_Vehicle_Collisions_-_Crashes.csv', nrows=nrows, parse_dates = [['CRASH_DATE','CRASH_TIME']])
	data.dropna(subset=['LATITUDE','LONGITUDE'],inplace=True)
	lowercase = lambda x: str(x).lower()
	data.rename(lowercase,axis='columns',inplace=True)
	data.rename(columns={'crash_date_crash_time':'date/time'},inplace=True)
	return data

data = data_load(100000)
original_data = data

st.header("Where are the most people injured in NYC?")
injured_people = st.slider("Number Of Persons injured",0,19)
st.map(data.query("injured_persons >= @injured_people")[['latitude','longitude']].dropna(how="any"))

st.header("How many collisions occur during a given time of day?")
hour = st.slider("Hour to look at",0,23)
data = data[data['date/time'].dt.hour == hour]

st.markdown('Vehicle collisions between %i:00 and %i:00'%(hour,(hour+1)%24))
midpoint = (np.average(data['latitude']),np.average(data['longitude']))

st.write(pdk.Deck(
	map_style = "mapbox://styles/mapbox/light-v9",
	initial_view_state={
	      "latitude":midpoint[0],
	      "longitude":midpoint[1],
	      "zoom" : 11,
	      "pitch" : 50,
	},
	layers = [
	    pdk.Layer(
	    	"HexagonLayer",
	    	data = data[['date/time','latitude','longitude']],
	    	get_position = ['longitude','latitude'],
	    	radius = 100,
	    	extruded = True,
	    	pickable = True,
	    	elevation_scale = 4,
	    	elevation_range = [0,1000],
		),
	],
))


st.subheader("Breakdown by minute between %i:00 and %i:00" % (hour,(hour+1)%24))

filtered = data[
   (data['date/time'].dt.hour >= hour) & (data['date/time'].dt.hour<(hour+1))   
]
hist = np.histogram(filtered['date/time'].dt.minute,bins = 60, range = (0,60))[0]
chart_data = pd.DataFrame({'minute':range(60),'crashes':hist})
fig = px.bar(chart_data,x='minute',y='crashes',hover_data = ['minute','crashes'],height = 400)
st.write(fig)

st.header("Top 5 dangerous streets by affected type")
select = st.selectbox('Affected type of people',['Pedestrians','Cyclists','Motorists'])
if select == 'Pedestrians':
	st.write(original_data.query('injured_pedestrians >=1')[['on_street_name',"injured_pedestrians"]].sort_values(by=['injured_pedestrians'],ascending = False).dropna(how= 'any')[:5])

elif select == 'Cyclists':
	st.write(original_data.query('injured_cyclists >=1')[['on_street_name',"injured_cyclists"]].sort_values(by=['injured_cyclists'],ascending = False).dropna(how= 'any')[:5])

else:
	st.write(original_data.query('injured_motorists >=1')[['on_street_name',"injured_motorists"]].sort_values(by=['injured_motorists'],ascending = False).dropna(how= 'any')[:5])


if st.checkbox('Show Raw Data',False):
	st.subheader('Raw Data')
	st.write(data)