Create backup.app.py

backup.app.py

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+from cmath import pi
+from json import load, tool
+from os import stat
+import streamlit as st
+import pandas as pd
+import numpy as np
+import pydeck as pdk
+from typing import Dict, Union
+import streamlit.components.v1 as components
+
+st.title("Live 3D Map")
+location = st.checkbox('Location Filter')
+queried_zip_code = None
+queried_city = None
+queried_state = None
+queried_age = None
+if location:
+    queried_zip_code = st.text_input('Zip Code:')
+    queried_city = st.text_input('City')
+    queried_state = st.selectbox('State:',  ('AL', 'AK', 'AZ', 'AR', 'AS','CA','CO','CT','DE','DC','FL','GA','GU','HI','ID','IL',
+    'IN','IA','KS','KY','LA','ME','MD','MA','MI','MN','MS','MO','MT','NE','NV','NH','NJ','NM','NY','NC','ND','CM','OH',
+    'OK','OR','PA','PR','RI','SC','SD','TN','TX','UT','VT','VA','VI','WA','WV','WI','WY'))
+ageBox = st.checkbox("Age Filter")
+if ageBox:
+    queried_age = st.slider("Age",0,200,(0,200))
+
+queried_male = st.checkbox("Male",value=True)
+queried_female = st.checkbox("Female",value=True)
+
+@st.cache(allow_output_mutation=True)
+def gen_load() -> pd.DataFrame:
+    df = pd.read_csv('US.txt')
+    return df
+
+import streamlit as st
+import pandas as pd
+import pydeck as pdk
+
+def ShowCityDataframe(uscities, US):
+    df = pd.read_csv(uscities)
+    df1 = pd.read_csv(uscities)
+    df2 = pd.read_csv(uscities)
+    
+    st.title("City FIPS, Location, and Population")
+    st.text("Search for any city in the United States:")
+
+    search_query = st.text_input(label="City Name", value="")
+    if search_query != "":
+        df = df1[df1["city"].str.contains(search_query, case=False)]
+    st.subheader("City Detail")
+    st.write(df)
+    
+    search_query2 = st.text_input(label="Zip Code", value="")
+    if search_query2 != "":
+        df = df2[df2["zips"].str.contains(search_query2, case=False)]
+    st.subheader("Zip Code Area Detail")
+    st.write(df)
+
+uscities = "uscities.csv"  # CSV - Columns are: "city","city_ascii","state_id","state_name","county_fips","county_name","lat","lng","population","density","source","military","incorporated","timezone","ranking","zips","id"
+US = "US.txt"   # TSV - Columns are: Country	Zip	City	State	Area	AreaCode	Latitude	Longitude	Include
+                # TSV Columns sample:       US	99553	Akutan	Alaska	AK	Aleutians East	013			54.143	-165.7854	1
+us-zip-codes = "us-zip-code-latitude-and-longitude.txt"  # SSV - Columns are:  Zip;City;State;Latitude;Longitude;Timezone;Daylight savings time flag;geopoint
+                # SSV Columns sample:       71937;Cove;AR;34.398483;-94.39398;-6;1;34.398483,-94.39398
+
+ShowCityDataframe(uscities, US)