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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"
@st.cache_data
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)
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