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

# In[3]:


# Load UCI census and convert to json for sending to the visualization
import pandas as pd
features = ["Age", "Workclass", "fnlwgt", "Education", "Education-Num", "Martial Status",
            "Occupation", "Relationship", "Race", "Sex", "Capital Gain", "Capital Loss",
            "Hours per week", "Country", "Target"]
jsonstr = pd.read_csv(
    "https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.test",
    names=features,
    sep=r'\s*,\s*',
    engine='python',
    skiprows=[0],
    na_values="?").to_json(orient='records')


# In[4]:


# Display the Dive visualization for this data
from IPython.core.display import display, HTML

HTML_TEMPLATE = """<link rel="import" href="/nbextensions/facets-dist/facets-jupyter.html">
        <facets-dive id="elem" height="600"></facets-dive>
        <script>
          var data = {jsonstr};
          document.querySelector("#elem").data = data;
        </script>"""
html = HTML_TEMPLATE.format(jsonstr=jsonstr)
display(HTML(html))