#!/usr/bin/env python
# coding: utf-8

# In[144]:


from datetime import datetime
import matplotlib as plt
from vortexasdk import CargoMovements, Geographies, Products


# In[145]:


singapore = [g.id for g in Geographies().search(term='singapore').to_list() if 'port' in g.layer]


# In[146]:


fuel_oil = [p.id for p in Products().search(term='fuel oil').to_list()]


# In[147]:


df = CargoMovements()\
        .search(filter_activity='unloading_state',
            filter_destinations=singapore,
            filter_products=fuel_oil,
            filter_time_min=datetime(2019, 1, 1),
            filter_time_max=datetime(2019, 12, 31))\
        .to_df()


# In[148]:


timestamp_col = 'events.cargo_port_unload_event.0.start_timestamp'
df['month'] = pd.to_datetime(df[timestamp_col]).dt.month


# In[149]:


monthly_aggregate = df.groupby(by='month')['quantity'].sum()

monthly_aggregate.plot(title='Singapore Fuel Oil Imports ahead of IMO 2020', ylim=(0, 3.5e7), figsize=(15, 5))