Есть ли реализация недостающих карт в экосистеме python?

Missingmaps генерирует график отсутствующих значений в фрейме данных (подробнее см. http://hosho.ees.hokudai.ac.jp/~kubo/Rdoc/library/Amelia/html/missmap.html).

Есть ли что-то подобное в экосистеме python? (pandas/Matplotlib?)

An example of how it looks like

Ответ 1

EDIT: с июня 2016 года есть пакет для этого: https://github.com/ResidentMario/missingno Исходный ответ следует:

Это довольно близко:

ax = missmap(df)

enter image description here

import pandas as pd

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import collections as collections
from matplotlib.patches import Rectangle
from itertools import izip, cycle


def missmap(df, ax=None, colors=None, aspect=4, sort='descending',
            title=None, **kwargs):
    """
    Plot the missing values of df.

    Parameters
    ----------
    df : pandas DataFrame
    ax : matplotlib axes
        if None then a new figure and axes will be created
    colors : dict
        dict with {True: c1, False: c2} where the values are
        matplotlib colors.
    aspect : int
        the width to height ratio for each rectangle.
    sort : one of {'descending', 'ascending', None}
    title : str
    kwargs : dict
        matplotlib.axes.bar kwargs

    Returns
    -------
    ax : matplotlib axes

    """
    if ax is None:
        fig, ax = plt.subplots()

    # setup the axes
    dfn = pd.isnull(df)

    if sort in ('ascending', 'descending'):
        counts = dfn.sum()
        sort_dict = {'ascending': True, 'descending': False}
        counts.sort(ascending=sort_dict[sort])
        dfn = dfn[counts.index]

    ny = len(df)
    nx = len(df.columns)
    # each column is a stacked bar made up of ny patches.
    xgrid = np.tile(np.arange(len(df.columns)), (ny, 1)).T
    ygrid = np.tile(np.arange(ny), (nx, 1))
    # xys is the lower left corner of each patch
    xys = (zip(x, y) for x, y in izip(xgrid, ygrid))

    if colors is None:
        colors = {True: '#EAF205', False: 'k'}

    widths = cycle([aspect])
    heights = cycle([1])

    for xy, width, height, col in izip(xys, widths, heights, dfn.columns):
        color_array = dfn[col].map(colors)

        rects = [Rectangle(xyc, width, height, **kwargs)
                 for xyc, c in zip(xy, color_array)]

        p_coll = collections.PatchCollection(rects, color=color_array,
                                             edgecolor=color_array, **kwargs)
        ax.add_collection(p_coll, autolim=False)

    # post plot aesthetics
    ax.set_xlim(0, nx)
    ax.set_ylim(0, ny)

    ax.set_xticks(.5 + np.arange(nx))  # center the ticks
    ax.set_xticklabels(dfn.columns)
    for t in ax.get_xticklabels():
        t.set_rotation(90)

    # remove tick lines
    ax.tick_params(axis='both', which='both', bottom='off', left='off',
                   labelleft='off')
    ax.grid(False)

    if title:
        ax.set_title(title)
    return ax