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import streamlit as st
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import pandas as pd
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import numpy as np
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st.title('Uber pickups in NYC')
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DATE_COLUMN = 'date/time'
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DATA_URL = ('https://s3-us-west-2.amazonaws.com/'
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'streamlit-demo-data/uber-raw-data-sep14.csv.gz')
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@st.cache_data
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def load_data(nrows):
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data = pd.read_csv(DATA_URL, nrows=nrows)
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lowercase = lambda x: str(x).lower()
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data.rename(lowercase, axis='columns', inplace=True)
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data[DATE_COLUMN] = pd.to_datetime(data[DATE_COLUMN])
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return data
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data_load_state = st.text('Loading data...')
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data = load_data(10000)
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data_load_state.text("Done! (using st.cache_data)")
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if st.checkbox('Show raw data'):
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st.subheader('Raw data')
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st.write(data)
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st.subheader('Number of pickups by hour')
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hist_values = np.histogram(data[DATE_COLUMN].dt.hour, bins=24, range=(0,24))[0]
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st.bar_chart(hist_values)
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hour_to_filter = st.slider('hour', 0, 23, 17)
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filtered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]
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st.subheader('Map of all pickups at %s:00' % hour_to_filter)
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st.map(filtered_data)
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