streamlittest.py

"""
# My first app
Here's our first attempt at using data to create a table:
"""
#streamlit run streamlittest.py


import streamlit as st
import pandas as pd

st.title('Streamlit test cases')

st.subheader('st.write examples')

df = pd.DataFrame({
  'first column': [1, 2, 3, 4],
  'second column': [10, 20, 30, 40]
})

df

st.write("Here's our first attempt at using data to create a table:")
st.write(pd.DataFrame({
    'first column': [1, 2, 3, 4],
    'second column': [10, 20, 30, 40]
}))

import numpy as np

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

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))

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

st.line_chart(chart_data)

st.subheader('st.map examples')
map_data = pd.DataFrame(
    np.random.randn(1000, 2) / [50, 50] + [37.76, -122.4],
    columns=['lat', 'lon'])
#use Numpy to generate some sample data and plot it on a map of San Francisco.
st.map(map_data)

st.subheader('Controller examples')
#When you've got the data or model into the state that you want to explore, you can add in widgets like st.slider(), st.button() or st.selectbox()
x = st.slider('x')  # 👈 this is a widget
st.write(x, 'squared is', x * x)

st.text_input("Your name", key="name")
# You can access the value at any point with:
st.session_state.name

#Use checkboxes to show/hide data
if st.checkbox('Show dataframe'):
    chart_data = pd.DataFrame(
       np.random.randn(20, 3),
       columns=['a', 'b', 'c'])

    chart_data

#Use st.selectbox to choose from a series. You can write in the options you want, or pass through an array or data frame column.
df = pd.DataFrame({
    'first column': [1, 2, 3, 4],
    'second column': [10, 20, 30, 40]
    })
option = st.selectbox(
    'Which number do you like best?',
     df['first column'])
'You selected: ', option

#Streamlit makes it easy to organize your widgets in a left panel sidebar with st.sidebar. Each element that's passed to st.sidebar is pinned to the left
# Add a selectbox to the sidebar:
add_selectbox = st.sidebar.selectbox(
    'How would you like to be contacted?',
    ('Email', 'Home phone', 'Mobile phone')
)
# Add a slider to the sidebar:
add_slider = st.sidebar.slider(
    'Select a range of values',
    0.0, 100.0, (25.0, 75.0)
)

st.subheader('Two columns example')
#Beyond the sidebar, Streamlit offers several other ways to control the layout of your app. st.columns lets you place widgets side-by-side, and st.expander lets you conserve space by hiding away large content.
left_column, right_column = st.columns(2)
# You can use a column just like st.sidebar:
left_column.button('Press me!')

# Or even better, call Streamlit functions inside a "with" block:
with right_column:
    chosen = st.radio(
        'Sorting hat',
        ("Gryffindor", "Ravenclaw", "Hufflepuff", "Slytherin"))
    st.write(f"You are in {chosen} house!")

st.subheader('Progress example')
#When adding long running computations to an app, you can use st.progress() to display status in real time.
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!'

#exploring a public Uber dataset for pickups and drop-offs in New York City
#ref: https://docs.streamlit.io/library/get-started/create-an-app
st.subheader('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)