import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime
from datetime import date

#start_date = st.sidebar.date_input('start date', datetime.date(2011,1,1))

#st.write(start_date)





#df = ld.load_data_projet()

st.title("Date range")

min_date = datetime.datetime(2019,5,1)
max_date = datetime.date(2021,1,1)

a_date = st.date_input("Pick a date", (min_date, max_date))

##this uses streamlit 'magic'!!!!
"The date selected:", a_date
"The type", type(a_date)
"Singling out a date for dataframe filtering", a_date[0]
"Singling out a date for dataframe filtering 2", a_date[1]
data = pd.read_excel(r'C:\Users\stani\Desktop\Webapp\st_zagora\data_for_python2.xlsx') 
df = pd.DataFrame(data)

#df['data'].map(datetime.datetime.date) 
#df['data'] = df['data'].apply(lambda x: x.strftime('%Y-%m-%d'))
#df['data'] = pd.to_datetime(df['data'], format="%Y-%d-%m")
#dates = (df['data'])
df['data'] = pd.to_datetime(df['data']).dt.date

dates=df[(df['data'] >= a_date[0]) & (df['data'] <= a_date[1])]
x = np.arange(len(dates))
st.write(df[(df['data'] >= a_date[0]) & (df['data'] <= a_date[1])])
df_res=df[(df['data'] >= a_date[0]) & (df['data'] <= a_date[1])]
#st.write(df,dates)
production_cost =  df_res['production cost'] 
#plot(dates, production_cost)
st.line_chart(production_cost)