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body {
    margin: 0;
    font-family: Helvetica;
}
table.dataframe {
    border-collapse: collapse;
    border: none;
}
table.dataframe tr {
    border: none;
}
table.dataframe td, table.dataframe th {
    margin: 0;
    border: 1px solid white;
    padding-left: 0.25em;
    padding-right: 0.25em;
}
table.dataframe th:not(:empty) {
    background-color: #fec;
    text-align: left;
    font-weight: normal;
}
table.dataframe tr:nth-child(2) th:empty {
    border-left: none;
    border-right: 1px dashed #888;
}
table.dataframe td {
    border: 2px solid #ccf;
    background-color: #f4f4ff;
}

h3 {
    color: white;
    background-color: black;
    padding: 0.5em;
}

/* Add to ~/.ipython/profile_default/static/custom/custom.css */

/* Pretty Pandas Dataframes */
.dataframe * {border-color: #c0c0c0 !important;}
.dataframe th{background: #eee;}
.dataframe td{text-align: right; min-width:5em;}

/* Format summary rows */
.dataframe-summary-row tr:last-child,
.dataframe-summary-col td:last-child{
    background: #eee;
    font-weight: 500;
}

from numbers import Number

def as_percent(v, precision='0.2'):  
    """Convert number to percentage string."""
    if isinstance(v, Number):
        return "{{:{}%}}".format(precision).format(v)
    else:
        raise TypeError("Numeric type required")

import numpy as np
import pandas as pd  
from functools import partial

def summary(df, fn=np.sum, axis=0, name='Total',  
            table_class_prefix='dataframe-summary'):
    """Append a summary row or column to DataFrame.

    Input:
    ------
    df : Dataframe to be summarized
    fn : Summary function applied over each column
    axis : Axis to summarize on (1: by row, 0: by column)
    name : Index or column label for summary
    table_class_prefix : Custom css class for dataframe

    Returns:
    --------
    Dataframe with applied summary.

    """
    total = df.apply(fn, axis=axis).to_frame(name)

    table_class = ""

    if axis == 0:
        total = total.T
        table_class = "{}-row".format(table_class_prefix)
    elif axis == 1:
        table_class = "{}-col".format(tbale_class_prefix)

    out = pd.concat([df, total], axis=axis)
    # Patch to_html function to use custom css class
    out.to_html = partial(out.to_html, classes=table_class)
    return out