import pandas as pd
import geopandas as gps
import datetime
import ee

ee.Authenticate()
ee.Initialize()

from google.colab import drive
drive.mount('/content/drive')

"""Selccionar Cultivo"""
#Maiz_str = '/content/drive/MyDrive/Puntos/Maiz.csv'
#df = pd.read_csv(Maiz_str, parse_dates=['Fecha_Siembra', 'Rango_Floor','Rango_Top'])

Soja_str = '/content/drive/MyDrive/Puntos/Soja.csv'
df = pd.read_csv(Soja_str, parse_dates=['Fecha_Cosecha', 'R3', 'R6'])
# En archivo de soja fila 315, columna Fecha_Cosecha modifiqué año 0201 por 2016 

df['Start_Date'] = df['R3']
df['End_Date'] = df['R6']

df = df[df['Start_Date'].notna()]
df = df[df['End_Date'].notna()]
df = df[df['Longitud'].notna()]
df = df[df['Latitud'].notna()]

new_df = pd.DataFrame([],columns=['id', 'longitude', 'latitude', 'time', 'NDVI', 'Parcela','Codigo_Lote'])

for index, row in df.iterrows():

    feature = ee.Algorithms.GeometryConstructors.Point([row.Longitud,row.Latitud])

    Start_Date = ee.Date(row.Start_Date)
    End_Date = ee.Date(row.End_Date)

    dataset = ee.ImageCollection("MODIS/061/MOD13Q1").select('NDVI').filter(ee.Filter.date(Start_Date,End_Date))
    NDVIvalues = dataset.getRegion(feature, 250).getInfo()
    NDVI_df = pd.DataFrame(NDVIvalues)
    NDVI_df.columns = NDVI_df.iloc[0]
    NDVI_df = NDVI_df.iloc[1:].reset_index(drop=True)
    NDVI_df.insert(1, "Parcela", row.Parcela)
    NDVI_df.insert(1, "Codigo_Lote", row.Codigo_Lote)
    new_df = new_df.append(NDVI_df)

new_df.to_csv('/content/drive/MyDrive/Puntos/NDVI_Puntos.csv',header=True, index=False)