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# %autosave 0

df['doy']

# +
import time
from datetime import datetime
import pprint

import pandas as pd
import ee; ee.Initialize()

# connection
import pymongo
from pymongo import MongoClient
mongourl = 'mongodb://admin:snap1234@ds251362.mlab.com:51362/snapdb-test'
client = MongoClient(mongourl)
db = client.get_database()

cur = db.variables.find({'District':'Krishna'})
df =  pd.DataFrame(list(cur))
# -

df.loc[(df['doy'] >= 152) & (df['doy'] <= 320)]

dir('334')

# +
df['year'] = df['idate'].apply(lambda x: datetime.fromtimestamp(x).strftime('%Y'))
df['doy'] = df['idate'].apply(lambda x: int(datetime.fromtimestamp(x).strftime('%j')))
df = df.loc[(df['doy'] > 152) & (df['doy'] < 320)]
df = df.sort_values(by=['doy'])
df['mmdd'] = df['idate'].apply(lambda x: datetime.fromtimestamp(x).strftime('%b-%d'))

lastyear = df.loc[df['year'] == '2017'].groupby(['doy','mmdd','District'])['value'].mean().reset_index()
thisyear = df.loc[df['year'] == '2018'].groupby(['doy','mmdd','District'])['value'].mean().reset_index()

vmin = df.groupby(['doy','mmdd','District'])['value'].quantile(0.30).reset_index()
vmax = df.groupby(['doy','mmdd','District'])['value'].quantile(0.70).reset_index();

import plotly
plotly.offline.init_notebook_mode() # run at the start of every notebook
import plotly.graph_objs as go
trace0 = go.Scatter(
    x=vmin['mmdd'],
    y=vmin['value'] / 10,
    fill= None,
#     mode='lines',
    name = 'quantile>30%',
    line=dict(
        width = 0.1,
        color='rgb(143, 19, 131)',
        dash = 'dash'
    )
)
trace1 = go.Scatter(
    x=vmax['mmdd'],
    y=vmax['value'] / 10,
    fill='tonexty',
#     mode='lines',
    name = 'quantile<70%',
    line=dict(
        width = 0,
        color='rgb(143, 19, 131)',
        dash = 'dash'
    )
)

trace2 = go.Bar(
    x = lastyear['mmdd'],
    y = lastyear['value']  / 10,
#     mode = 'markers',
    name = 'year 2017',
#     line=dict(
#         color='rgb(0, 255, 0)',
#     )
)

trace3 = go.Bar(
    x = thisyear['mmdd'],
    y = thisyear['value'] / 10,
#     mode = 'markers',
    name = 'year 2018',
#     line=dict(
#         color='rgb(255, 0, 0)',
#     )
)


data = [trace0, trace1, trace2, trace3]
legend=dict(
    x=0,
    y=1,
    traceorder='normal',
    font=dict(
        family='sans-serif',
        size=12,
        color='#000'
    ),
    bgcolor='#E2E2E2',
    bordercolor='#FFFFFF',
    borderwidth=2
)
layout = go.Layout(
    title='Krishna District: LAI',
    legend = legend,
    xaxis=dict(
        title='Date',
        hoverformat='.3f',
        titlefont=dict(
            family='Courier New, monospace',
            size=18,
            color='#7f7f7f'
        )
    ),
    yaxis=dict(
        title='Value',
        hoverformat='.3f',
        titlefont=dict(
            family='Courier New, monospace',
            size=18,
            color='#7f7f7f'
        )
    )
)
fig = go.Figure(data=data, layout=layout)
plotly.offline.iplot(fig, filename='basic-area-no-bound')
# -

pd.DataFrame({'vmin':vmin, 'vmax':vmax, 'lastyear':lastyear, 'thisyear': thisyear})

vmin = vmin.rename(index=str, columns={"value": "quantile>30%"})
vmax = vmax.rename(index=str, columns={"value": "quantile<70%"})
lastyear = lastyear.rename(index=str, columns={"value": "2017"})
thisyear = thisyear.rename(index=str, columns={"value": "2018"})
dataframe = lastyear.merge(thisyear,how='left').merge(vmin,how='left').merge(vmax,how='left')
dataframe.head()

dataframe

vmax.head()