Data Science

PySeaborn

Third-party Python package module — seaborn. Auto-indexed from CDN. Method-level security roles have not been annotated; rule writers should inspect the source before use.

Other Methods

.algorithms.bootstrap()Neutral
#
Signature
algorithms.bootstrap(*args, n_boot, func, axis, units, seed)

algorithms.bootstrap function.

.axisgrid.jointplot()Neutral
#
Signature
axisgrid.jointplot(data, x, y, hue, kind, height, ratio, space, dropna, xlim, ylim, color, palette, hue_order, hue_norm, marginal_ticks, joint_kws, marginal_kws, **kwargs)

axisgrid.jointplot function.

.axisgrid.pairplot()Neutral
#
Signature
axisgrid.pairplot(data, hue, hue_order, palette, vars, x_vars, y_vars, kind, diag_kind, markers, height, aspect, corner, dropna, plot_kws, diag_kws, grid_kws, size)

axisgrid.pairplot function.

.categorical.barplot()Neutral
#
Signature
categorical.barplot(data, x, y, hue, order, hue_order, estimator, errorbar, n_boot, units, weights, seed, orient, color, palette, saturation, fill, hue_norm, width, dodge, gap, log_scale, native_scale, formatter, legend, capsize, err_kws, ci, errcolor, errwidth, ax, **kwargs)

categorical.barplot function.

.categorical.boxenplot()Neutral
#
Signature
categorical.boxenplot(data, x, y, hue, order, hue_order, orient, color, palette, saturation, fill, dodge, width, gap, linewidth, linecolor, width_method, k_depth, outlier_prop, trust_alpha, showfliers, hue_norm, log_scale, native_scale, formatter, legend, scale, box_kws, flier_kws, line_kws, ax, **kwargs)

categorical.boxenplot function.

.categorical.boxplot()Neutral
#
Signature
categorical.boxplot(data, x, y, hue, order, hue_order, orient, color, palette, saturation, fill, dodge, width, gap, whis, linecolor, linewidth, fliersize, hue_norm, native_scale, log_scale, formatter, legend, ax, **kwargs)

categorical.boxplot function.

.categorical.catplot()Neutral
#
Signature
categorical.catplot(data, x, y, hue, row, col, kind, estimator, errorbar, n_boot, units, weights, seed, order, hue_order, row_order, col_order, col_wrap, height, aspect, log_scale, native_scale, formatter, orient, color, palette, hue_norm, legend, legend_out, sharex, sharey, margin_titles, facet_kws, ci, **kwargs)

categorical.catplot function.

.categorical.countplot()Neutral
#
Signature
categorical.countplot(data, x, y, hue, order, hue_order, orient, color, palette, saturation, fill, hue_norm, stat, width, dodge, gap, log_scale, native_scale, formatter, legend, ax, **kwargs)

categorical.countplot function.

.categorical.pointplot()Neutral
#
Signature
categorical.pointplot(data, x, y, hue, order, hue_order, estimator, errorbar, n_boot, units, weights, seed, color, palette, hue_norm, markers, linestyles, dodge, log_scale, native_scale, orient, capsize, formatter, legend, err_kws, ci, errwidth, join, scale, ax, **kwargs)

categorical.pointplot function.

.categorical.stripplot()Neutral
#
Signature
categorical.stripplot(data, x, y, hue, order, hue_order, jitter, dodge, orient, color, palette, size, edgecolor, linewidth, hue_norm, log_scale, native_scale, formatter, legend, ax, **kwargs)

categorical.stripplot function.

Fully-Qualified Names

FQNField
seabornfqns[0]

Wrong FQN → 0 findings. Verify with: change fqns to garbage → must produce 0 results.

Import

rule.py
import seaborn