Spaces:
Sleeping
Sleeping
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) | |
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) | |