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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" | |
def load_data(nrows): | |
data = pd.read_csv(DATA_URL, nrows=nrows) | |
data.columns = data.columns.str.lower() | |
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) | |