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Home.py
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Home.py
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import streamlit as st
import pandas as pd
import numpy as np
from PIL import Image
st.title('Streamlit Hello World')
st.image('https://www.socialpilot.co/wp-content/uploads/2023/02/gif.gif')
st.sidebar.info('Contact')
st.sidebar.markdown('[Twitter](https://twitter.com/giswqs)')
# st.title('Uber pickups in NYC')
# DATE_COLUMN = 'date/time'
# DATA_URL = ('https://s3-us-west-2.amazonaws.com/'
# 'streamlit-demo-data/uber-raw-data-sep14.csv.gz')
# @st.cache_data
# def load_data(nrows):
# data = pd.read_csv(DATA_URL, nrows=nrows)
# lowercase = lambda x: str(x).lower()
# data.rename(lowercase, axis='columns', inplace=True)
# data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])
# return data
# data_load_state = st.text('Loading data...')
# data = load_data(10000)
# data_load_state.text("Done! (using st.cache_data)")
# if st.checkbox('Show raw data'):
# st.subheader('Raw data')
# st.write(data)
# st.subheader('Number of pickups by hour')
# hist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]
# st.bar_chart(hist_values)
# # Some number in the range 0-23
# hour_to_filter = st.slider('hour', 0, 23, 17)
# filtered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]
# st.subheader('Map of all pickups at %s:00' % hour_to_filter)
# st.map(filtered_data)
# st.image('https://www.socialpilot.co/wp-content/uploads/2023/02/gif.gif')