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| import os | |
| from pathlib import Path | |
| import numpy as np | |
| import pandas as pd | |
| import streamlit as st | |
| from athai.data_utils import cached_download_csv | |
| 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" | |
| ) | |
| DATA_PATH = Path(os.environ.get("APP_DATA")) | |
| def load_data(nrows): | |
| data = cached_download_csv(DATA_PATH, DATA_URL, nrows=nrows) | |
| def lowercase(x): | |
| return 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)") | |
| 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) | |
| uploaded_file = st.file_uploader("Choose a file") | |
| if uploaded_file is not None: | |
| st.write(uploaded_file.name) | |
| bytes_data = uploaded_file.getvalue() | |
| st.write(len(bytes_data), "bytes") | |
| st.markdown("") | |