Spaces:
Sleeping
Sleeping
File size: 2,053 Bytes
c913f06 909cb80 c913f06 909cb80 51109f7 c913f06 909cb80 6acd8b1 c913f06 6acd8b1 c913f06 6acd8b1 c913f06 6acd8b1 c913f06 6acd8b1 c913f06 6acd8b1 c913f06 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
from cmath import pi
from json import load, tool
from os import stat
#from telnetlib import RCP
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
#import streamlit_shared_funcs as my
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 = my.get_data()
df = pd.read_csv('US.txt')
return df
#AI Emotional State Score: Anxiety, Confusion, Trepidation, Fear, Guilt
import streamlit as st
import pandas as pd
import pydeck as pdk
def ShowCityDataframe(DATA_URL, SEARCH_DATA):
df = pd.read_csv(DATA_URL)
st.title("City FIPS, Location, and Population")
st.text("Search for any city in the United States:")
# Search query for existing data
search_query = st.text_input(label="City Name", value="")
if search_query != "":
df = df[df["city"].str.contains(search_query, case=False)]
# Search query for new data
search_query2 = st.text_input(label="Zip Code", value="")
if search_query2 != "":
df = df[df["Zip"].str.contains(search_query2)]
st.subheader("City Detail")
st.write(df)
Cities = "uscities.csv"
SearchData = "US.txt"
ShowCityDataframe(Cities, SearchData)
|