Function matrix

missingno/missingno.py:104–304

Presents a `matplotlib` matrix visualization of the nullity of the given DataFrame. Note that for the default `figsize` 250 is a soft display limit: specifying a number of records greater than approximately this value will cause certain records to show up in the sparkline but not in th

(df,
           filter=None, n=0, p=0, sort=None,
           figsize=(25, 10), width_ratios=(15, 1), color=(0.25, 0.25, 0.25),
           fontsize=16, labels=None, sparkline=True, inline=True,
           freq=None)

def matrix(df,
           filter=None, n=0, p=0, sort=None,
           figsize=(25, 10), width_ratios=(15, 1), color=(0.25, 0.25, 0.25),
           fontsize=16, labels=None, sparkline=True, inline=True,
           freq=None):
    """
    Presents a `matplotlib` matrix visualization of the nullity of the given DataFrame.

    Note that for the default `figsize` 250 is a soft display limit: specifying a number of records greater than
    approximately this value will cause certain records to show up in the sparkline but not in the matrix, which can
    be confusing.


    The default vertical display will fit up to 50 columns. If more than 50 columns are specified and the labels
    parameter is left unspecified the visualization will automatically drop the labels as they will not be very
    readable. You can override this behavior using `labels=True` and your own `fontsize` parameter.

    :param df: The DataFrame whose completeness is being nullity matrix mapped.
    :param filter: The filter to apply to the heatmap. Should be one of "top", "bottom", or None (default). See
    `nullity_filter()` for more information.
    :param n: The cap on the number of columns to include in the filtered DataFrame. See  `nullity_filter()` for
    more information.
    :param p: The cap on the percentage fill of the columns in the filtered DataFrame. See  `nullity_filter()` for
    more information.
    :param sort: The sort to apply to the heatmap. Should be one of "ascending", "descending", or None. See
    `nullity_sort()` for more information.
    :param figsize: The size of the figure to display. This is a `matplotlib` parameter.
    For the vertical configuration this defaults to (20, 10); the horizontal configuration computes a sliding value
    by default based on the number of columns that need to be displayed.
    :param fontsize: The figure's font size. This default to 16.
    :param labels: Whether or not to display the column names. Would need to be turned off on particularly large
    displays. Defaults to True.
    :param sparkline: Whether or not to display the sparkline. Defaults to True.
    :param width_ratios: The ratio of the width of the matrix to the width of the sparkline. Defaults to `(15,
    1)`. Does nothing if `sparkline=False`.
    :param color: The color of the filled columns. Default is a medium dark gray: the RGB multiple `(0.25, 0.25, 0.25)`.
    :return: If `inline` is True, the underlying `matplotlib.figure` object. Else, nothing.
    """

    # Apply filters and sorts.
    df = nullity_filter(df, filter=filter, n=n, p=p)
    df = nullity_sort(df, sort=sort)

    height = df.shape[0]
    width = df.shape[1]

    # z is the color-mask array.
    z = df.notnull().values

    # g is a NxNx3 matrix
    g = np.zeros((height, width, 3))

    # Apply the z color-mask to set the RGB of each pixel.
    g[z < 0.5] = [1, 1, 1]
    g[z > 0.5] = color

    # Set up the matplotlib grid layout.
    # If the sparkline is removed the layout is a unary subplot.