push

app.py

@@ -1,73 +1,36 @@
-# -*- coding: utf-8 -*-
-# Copyright 2018-2022 Streamlit Inc.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#    http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
 
-"""An example of showing geographic data."""
+# Streamlined version of the Streamlit app code
 
-import os
-
-import altair as alt
-import numpy as np
 import pandas as pd
 import pydeck as pdk
 import streamlit as st
 
 # SETTING PAGE CONFIG TO WIDE MODE AND ADDING A TITLE AND FAVICON
-st.set_page_config(layout="wide", page_title="NYC Ridesharing Demo", page_icon=":taxi:")
-
+st.set_page_config(layout="wide", page_title="Data Visualization", page_icon=":chart_with_upwards_trend:")
 
-# LOAD DATA ONCE
-@st.cache_resource
+# Function to load data
 def load_data():
     path = "ipc.csv"
-    
-
     data = pd.read_csv(
         path,
-        nrows=100000,  # approx. 10% of data
-        names=[
-            "Lat",
-            "Lon",
-            "Number",
-            "Tract",
-        ],  # specify names directly since they don't change
-        skiprows=1,  # don't read header since names specified directly
-        usecols=[0, 1, 2],  # doesn't load last column, constant value "B02512"
-        parse_dates=[
-            "date/time"
-        ],  # set as datetime instead of converting after the fact
+        names=["Lat", "Lon", "Number", "Census Tract #"],
+        skiprows=1
     )
-
     return data
 
-
-# FUNCTION FOR AIRPORT MAPS
+# Function to display the map
 def map(data, lat, lon, zoom):
+    tooltip = {"html": "<b>Census Tract #:</b> {Census Tract #}<br><b>Number:</b> {Number}"}
     st.write(
         pdk.Deck(
             map_style="mapbox://styles/mapbox/dark-v9",
-            initial_view_state={
-                "latitude": lat,
-                "longitude": lon,
-                "zoom": zoom,
-                "pitch": 50,
-            },
+            initial_view_state={"latitude": lat, "longitude": lon, "zoom": zoom, "pitch": 50},
             layers=[
                 pdk.Layer(
                     "HexagonLayer",
                     data=data,
-                    get_position=["lon", "lat"],
+                    get_position=["Lon", "Lat"],
+                    get_elevation="Number",
                     radius=100,
                     elevation_scale=4,
                     elevation_range=[0, 1000],
@@ -75,90 +38,13 @@ def map(data, lat, lon, zoom):
                     extruded=True,
                 ),
             ],
+            tooltip=tooltip
         )
     )
 
-
-# FILTER DATA FOR A SPECIFIC HOUR, CACHE
-@st.cache_data
-def filterdata(df, hour_selected):
-    return df[df["date/time"].dt.hour == hour_selected]
-
-
-# CALCULATE MIDPOINT FOR GIVEN SET OF DATA
-@st.cache_data
-def mpoint(lat, lon):
-    return (np.average(lat), np.average(lon))
-
-
-# FILTER DATA BY HOUR
-@st.cache_data
-def histdata(df, hr):
-    filtered = data[
-        (df["date/time"].dt.hour >= hr) & (df["date/time"].dt.hour < (hr + 1))
-    ]
-
-    hist = np.histogram(filtered["date/time"].dt.minute, bins=60, range=(0, 60))[0]
-
-    return pd.DataFrame({"minute": range(60), "pickups": hist})
-
-
-# STREAMLIT APP LAYOUT
+# Main app execution part
 data = load_data()
+midpoint = (data['Lat'].mean(), data['Lon'].mean())
 
-# LAYING OUT THE TOP SECTION OF THE APP
-row1_1, row1_2 = st.columns((2, 3))
-
-# SEE IF THERE'S A QUERY PARAM IN THE URL (e.g. ?pickup_hour=2)
-# THIS ALLOWS YOU TO PASS A STATEFUL URL TO SOMEONE WITH A SPECIFIC HOUR SELECTED,
-# E.G. https://share.streamlit.io/streamlit/demo-uber-nyc-pickups/main?pickup_hour=2
-if not st.session_state.get("url_synced", False):
-    try:
-        pickup_hour = int(st.experimental_get_query_params()["pickup_hour"][0])
-        st.session_state["pickup_hour"] = pickup_hour
-        st.session_state["url_synced"] = True
-    except KeyError:
-        pass
-
-
-# IF THE SLIDER CHANGES, UPDATE THE QUERY PARAM
-def update_query_params():
-    hour_selected = st.session_state["pickup_hour"]
-    st.experimental_set_query_params(pickup_hour=hour_selected)
-
-
-with row1_1:
-    st.title("NYC Uber Ridesharing Data")
-    hour_selected = st.slider(
-        "Select hour of pickup", 0, 23, key="pickup_hour", on_change=update_query_params
-    )
-
-
-with row1_2:
-    st.write(
-        """
-    ##
-    Examining how Uber pickups vary over time in New York City's and at its major regional airports.
-    By sliding the slider on the left you can view different slices of time and explore different transportation trends.
-    """
-    )
-
-# LAYING OUT THE MIDDLE SECTION OF THE APP WITH THE MAPS
-row2_1, row2_2, row2_3, row2_4 = st.columns((2, 1, 1, 1))
-
-# SETTING THE ZOOM LOCATIONS FOR THE AIRPORTS
-la_guardia = [40.7900, -73.8700]
-jfk = [40.6650, -73.7821]
-newark = [40.7090, -74.1805]
-zoom_level = 12
-midpoint = mpoint(data["lat"], data["lon"])
-
-with row2_1:
-    st.write(
-        f"""**All New York City from {hour_selected}:00 and {(hour_selected + 1) % 24}:00**"""
-    )
-    map(filterdata(data, hour_selected), midpoint[0], midpoint[1], 11)
-
-
-# CALCULATING DATA FOR THE HISTOGRAM
-#chart_data = histdata(data, hour_selected)
+st.title("Interactive Data Visualization")
+map(data, midpoint[0], midpoint[1], 11)

requirements.txt

@@ -1,3 +1,4 @@
 streamlit==1.20.0
 pydeck==0.7.1
-protobuf==3.19.5
+protobuf==3.19.5
+pandas