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

# In[1]:


DATA_DIR = '/home/notebook/shared-ns1000k/inputs/SEAICE_M/'

FILE = 'ci.mon.mean.nc'


# In[53]:


import pandas as pd
import matplotlib.pyplot as plt


# In[54]:


def load_seaice_xarray(filepath, shift_lons=True):
    import iris, xarray
    cube = iris.load_cube(DATA_DIR + FILE)
    if shift_lons:
        cube = cube.intersection(longitude=(-180, 180))
    return xarray.DataArray.from_iris(cube)


# In[55]:


xarr = load_seaice_xarray(DATA_DIR + FILE)
xarr


# In[62]:


xarr[0].plot(figsize=(18, 8));


# In[13]:


arctic_subset = xarr.sel(latitude=slice(90, 66))
sea_ice_timeseries = arctic_subset.mean(('latitude', 'longitude'))
df = sea_ice_timeseries.to_dataframe()
df # check groubpy pandas 


# In[27]:


import pandas as pd
df['month'] = df.index.month
mask = df.month.between(4,9)
only_summer = df[mask]
only_summer


# In[47]:


summer_mean = only_summer.groupby(only_summer.index.year).mean()
summer_mean


# In[52]:


ax = summer_mean['ci'].plot(figsize=(8, 8), ylim=(0, 1))
ax.set_title('Blaaaaa');