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

# ## Census API Example
# This example only works with an api key: https://www.census.gov/developers/.
# You can run it a limited number of times without a key; comment out block 2 and remove &key={api_key} from the data_url string in block 5

# In[1]:


#Pull data from Population Estimates Vintage 2018
get_ipython().run_line_magic('matplotlib', 'inline')
import requests,pandas as pd


# In[2]:


with open('census_key.txt') as key:
    api_key=key.read().strip()


# In[3]:


year='2018'
dsource='pep'
dname='components'
cols='GEONAME,NATURALINC,DOMESTICMIG,INTERNATIONALMIG'
state='42'
county='017,029,045,091,101'
#state='34'
#county='005,007,015,021'


# In[4]:


base_url = f'https://api.census.gov/data/{year}/{dsource}/{dname}'
base_url


# In[5]:


data_url = f'{base_url}?get={cols}&for=county:{county}&in=state:{state}&key={api_key}'
response=requests.get(data_url)
print(response.text)


# In[6]:


data=response.json()
df=pd.DataFrame(data[1:], columns=data[0]).\
    rename(columns={"NATURALINC": "Natural Increase", "DOMESTICMIG": "Net Domestic Mig", "INTERNATIONALMIG":"Net Foreign Mig"})
df['fips']=df.state+df.county
df.set_index('fips',inplace=True)
df.drop(columns=['state','county'],inplace=True)
df=df.astype(dtype={'Natural Increase':'int64','Net Domestic Mig':'int64','Net Foreign Mig':'int64'},inplace=True)
df


# In[7]:


#Total population change 2017-2018
df.sum(axis=1)


# In[8]:


labels=df['GEONAME'].str.split(' ',expand=True)[0]
ax=df.plot.bar(rot=0, title='Components of Population Change 2017-18')
ax.set_xticklabels(labels)
ax.set_xlabel('')


# In[ ]: