Update app.py

app.py

@@ -1,20 +1,42 @@
-import streamlit as st 
-import pandas as pd 
-import numpy as np 
-from datetime import datetime, timedelta 
+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") 
+st.title('Cumulative Trend')
 
-uploaded_file = st.file_uploader("Choose a CSV file including 'date' column.") 
-                                   
-if uploaded_file is not None: 
+uploaded_file = st.file_uploader("Choose a csv file including 'date' column.")
 
-    df = pd.read CSV (uploaded_file, sep=',' usecols=["date"]) 
-    df = df.dropna(axis=0)
+if uploaded_file is not None:
 
-    date_list = pd.to_datetime(df.squeeze()).dt.date.tolist() 
-    date_list.sort()
+  df = pd.read_csv(uploaded_file, sep=",", usecols=["date"])
+  df = df.dropna(axis=0)
 
-    start_date = date_list[0] 
-    end_date = date_list[-1]
+  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))
+