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import streamlit as st | |
import pandas as pd | |
import numpy as np | |
from datetime import datetime, timedelta | |
from io import StringIO | |
st.title('Cumulative Trend') | |
uploaded_file = st.file_uploader("Choose a csv file including 'date' column.") | |
if uploaded_file is not None: | |
df = pd.read_csv(uploaded_file, sep=",", usecols=["date"]) | |
df = df.dropna(axis=0) | |
date_list = pd.to_datetime(df.squeeze()).dt.date.tolist() | |
date_list.sort() | |
start_date = date_list[0] | |
end_date = date_list[-1] | |
day_count = (end_date - start_date).days + 1 | |
x = np.arange(start_date, end_date + timedelta(days=1), timedelta(days=1)).astype(datetime) | |
y = np.zeros(day_count) | |
for d in date_list: | |
y[(d - start_date).days] += 1 | |
y_count = np.cumsum(y) | |
df = pd.DataFrame({'date': x, 'count': y_count}) | |
st.area_chart(df.set_index('date')) | |
col1, col2 = st.columns(2) | |
col1.metric("rows", len(date_list)) | |
col2.metric("days", day_count) | |
col3, col4 = st.columns(2) | |
col3.metric("start", str(start_date)) | |
col4.metric("end", str(end_date)) | |