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-rw-r--r--app.py95
1 files changed, 69 insertions, 26 deletions
diff --git a/app.py b/app.py
index ec05fcf..099c317 100644
--- a/app.py
+++ b/app.py
@@ -1,7 +1,9 @@
from dash import Dash, html, dcc, callback, Output, Input, dash_table
import plotly.express as px
import pandas as pd
+import numpy as np
import sqlite3
+from datetime import datetime, date
# Connect to database and query all incidents
connection = sqlite3.connect("./raw_data/ingress.db")
@@ -9,44 +11,51 @@ cursor = connection.cursor()
query = "SELECT * FROM incidents;"
df = pd.read_sql_query(query, connection).sort_values(by="description")
-# Create custom YEAR column to use in dropdown
-df['year'] = df['date'].str[-4:]
+# Replace empty cells with NaN
+df = df.replace(r'^\s*$', np.nan, regex=True)
+
+# Convert date column to datetime
+# TODO: Create a combined datetime column in the db to load/convert here
+df["date"] = pd.to_datetime(df["date"])
# Configure HTML layout
app = Dash(__name__)
app.layout = html.Div(children = [
- html.H1(children="Omaha Police Incidents", style={"textAlign":"center"}),
+ html.H1(children="Omaha Crime Mapping & Analysis", style={"textAlign":"center"}),
html.Div([
- html.H2(children="Totals per Category and Year", style={"textAlign":"center"}),
- dcc.Dropdown(df.sort_values("description").description.unique(), "INJURY", id="dropdown"),
- dcc.Dropdown(df.sort_values("year").year.unique(), "2023", id="year-dropdown"),
- html.Hr(),
- dash_table.DataTable(data=df.to_dict("records"), page_size=5, id="table"),
- html.H2(children="Map of Incidents per Category and Year", style={"textAlign":"center"}),
- dcc.Graph(id="map-graph")
+ html.Div(className="flex",
+ children = [
+ html.P("Crime:"),
+ dcc.Dropdown(df.sort_values("description").description.unique(), "INJURY", id="dropdown"),
+ ]
+ ),
+ html.Div(className="flex",
+ children = [
+ html.P("Date Range:"),
+ dcc.DatePickerRange(
+ id='date-picker-range',
+ min_date_allowed=date(2015, 1, 1),
+ max_date_allowed=date(2023, 12, 31),
+ start_date=date(2015, 1, 1),
+ end_date=date(2023,12,31)
+ ),
+ ]
+ ),
+ dcc.Graph(id="map-graph"),
+ dcc.Graph(id="line-graph"),
+ dash_table.DataTable(data=df.to_dict("records"), page_size=5, id="table")
])
])
-# Create table
-@callback(
- Output("table", "data"),
- Input("dropdown", "value"),
- Input("year-dropdown", "value")
-)
-def update_table(description, year):
- dff = df[df.year == year]
- dff = dff.reset_index()
- dff = dff[dff.description == description]
- return dff.to_dict("records")
-
# Create map
@callback(
Output("map-graph", "figure"),
Input("dropdown", "value"),
- Input("year-dropdown", "value")
+ Input('date-picker-range', 'start_date'),
+ Input('date-picker-range', 'end_date')
)
-def update_map(description, year):
- dff = df[df.year == year]
+def update_map(description, start_date, end_date):
+ dff = df[(df['date'] > start_date) & (df['date'] < end_date)]
dff = dff.reset_index()
dff = dff[dff.description == description]
@@ -54,7 +63,6 @@ def update_map(description, year):
dff,
lat="lat",
lon="lon",
- color="description",
hover_name="description",
hover_data=["date", "time"],
title="Incident Count by Coordinates",
@@ -69,5 +77,40 @@ def update_map(description, year):
return fig
+# Create line graph
+@callback(
+ Output("line-graph", "figure"),
+ Input("dropdown", "value"),
+ Input('date-picker-range', 'start_date'),
+ Input('date-picker-range', 'end_date')
+)
+def update_line(description, start_date, end_date):
+ dff = df[(df['date'] > start_date) & (df['date'] < end_date)]
+ dff = dff.reset_index()
+ dff = dff[dff.description == description]
+ dff = dff.groupby(by="date").count()
+ dff = dff.reset_index()
+
+ fig = px.line(
+ dff,
+ x="date",
+ y="description",
+ )
+
+ return fig
+
+# Create table
+@callback(
+ Output("table", "data"),
+ Input("dropdown", "value"),
+ Input('date-picker-range', 'start_date'),
+ Input('date-picker-range', 'end_date')
+)
+def update_table(description, start_date, end_date):
+ dff = df[(df['date'] > start_date) & (df['date'] < end_date)]
+ dff = dff.reset_index()
+ dff = dff[dff.description == description]
+ return dff.to_dict("records")
+
if __name__ == "__main__":
app.run(debug=True)