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

# ## Question 1: Binary Computation
# 
# How does this dataset treat people with non binary gender identity?
# 
# How can you test that?
# 

# In[2]:


import pandas as pd
# source = 'data/population.csv'
source = 'https://www.opendatani.gov.uk/dataset/62e7073f-e924-4d3f-81a5-ad45b5127682/resource/67c25586-b9aa-4717-9a4b-42de21a403f2/download/parliamentary-constituencies-by-single-year-of-age-and-gender-mid-2001-to-mid-2019.csv'

df = pd.read_csv(source) # `read_csv` can read from URL's or from local files aswell

df_2019 = df[
    (df['Mid_Year_Ending'] == 2019)
]


# In[5]:


gender_pop = df_2019.groupby('Gender')['Population_Estimate'].sum()
gender_pop


# In[6]:


gender_pop['Males']+gender_pop['Females'], gender_pop['All persons']


# In[11]:


pd.DataFrame.from_dict({
    'All persons': {'All':gender_pop['All persons']},
    'Gendered': {'Males':gender_pop['Males'],
                 'Females':gender_pop['Females']}
}).T.plot.bar(stacked=True, width=1)


# In[ ]: