documentacao.py

# main concept
# https://docs.streamlit.io/library/get-started/main-concepts


import streamlit as st
import numpy as np

# st. write('bem vindo')

# dataframe = np.random.randn(10,20)
# st.dataframe(dataframe)

import streamlit as st
import numpy as np
import pandas as pd


#highlight nos maiores valores de cada coluna
# dataframe = pd.DataFrame(
#     np.random.randn(10, 20),
#     columns=('col %d' % i for i in range(20)))

# st.dataframe(dataframe.style.highlight_max(axis=0))

# dataframe = pd.DataFrame(
#     np.random.randn(10, 20),
#     columns=('col %d' % i for i in range(20)))
# st.table(dataframe)

# chart_data = pd.DataFrame(
#      np.random.randn(20, 3),
#      columns=['a', 'b', 'c'])

# # st.line_chart(chart_data)

# map_data = pd.DataFrame(
#     np.random.randn(1000, 2) / [50, 50] + [37.76, -122.4],
#     columns=['lat', 'lon'])

# st.map(map_data)

# import streamlit as st
# x = st.slider('x')  # 👈 this is a widget
# st.write(x, 'squared is', x * x)

# import time

# 'Starting a long computation...'

# # Add a placeholder
# latest_iteration = st.empty()
# bar = st.progress(0)

# for i in range(100):
#   # Update the progress bar with each iteration.
#   latest_iteration.text(f'Iteration {i+1}')
#   bar.progress(i + 1)
#   time.sleep(0.1)

# '...and now we\'re done!'

# import streamlit as st
# import pandas as pd
# import numpy as np

# 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)

# import streamlit as st

# st.set_page_config(
#     page_title="Hello",
#     page_icon="👋",
# )

# st.write("# Welcome to Streamlit! 👋")

# st.sidebar.success("Select a demo above.")

# st.markdown(
#     """
#     Streamlit is an open-source app framework built specifically for
#     Machine Learning and Data Science projects.
#     **👈 Select a demo from the sidebar** to see some examples
#     of what Streamlit can do!
#     ### Want to learn more?
#     - Check out [streamlit.io](https://streamlit.io)
#     - Jump into our [documentation](https://docs.streamlit.io)
#     - Ask a question in our [community
#         forums](https://discuss.streamlit.io)
#     ### See more complex demos
#     - Use a neural net to [analyze the Udacity Self-driving Car Image
#         Dataset](https://github.com/streamlit/demo-self-driving)
#     - Explore a [New York City rideshare dataset](https://github.com/streamlit/demo-uber-nyc-pickups)
# """
# )

# def load_data(url):
#     df = pd.read_csv(url)  # 👈 Download the data
#     return df

# df = load_data("https://github.com/plotly/datasets/raw/master/uber-rides-data1.csv")
# st.dataframe(df)

# st.button("Rerun")

import streamlit as st
import datetime

st.title('Counter Example')
if 'count' not in st.session_state:
    st.session_state.count = 0
    st.session_state.last_updated = datetime.time(0,0)

def update_counter():
    st.session_state.count += st.session_state.increment_value
    st.session_state.last_updated = st.session_state.update_time

with st.form(key='my_form'):
    st.time_input(label='Enter the time', value=datetime.datetime.now().time(), key='update_time')
    st.number_input('Enter a value', value=0, step=1, key='increment_value')
    submit = st.form_submit_button(label='Update', on_click=update_counter)

st.write('Current Count = ', st.session_state.count)
st.write('Last Updated = ', st.session_state.last_updated)