Selected KDE bandwidth is 0. Cannot estimate density.

[anilkumarpanda]

Selected KDE bandwidth is 0. Cannot estimate density. runtime error is thrown when trying to plot the kde of data, with the below characteristics:

default_df['overdue_accts'].value_counts()

0 43408 1 5382 2 1241 3 361 4 120 5 48 6 22 7 7 8 7 9 4 11 4 12 2 16 1 10 1 13 1 14 1 18 1

nondefault_df['overdue_accts'].value_counts()

0 163471 1 14588 2 3061 3 841 4 284 5 118 6 74 7 31 9 21 8 20 11 8 12 6 10 5 13 4 14 4 17 2 23 1 15 1 18 1 19 1 25 1

This behaviour is seen when the package statsmodels is installed in the same environment, as seaborn tries use statsmodels.

The following is the error stack trace :

ValueError Traceback (most recent call last) ~/Developer/anaconda3/envs/gdd3.6/lib/python3.6/site-packages/statsmodels/nonparametric/kde.py in kdensityfft(X, kernel, bw, weights, gridsize, adjust, clip, cut, retgrid) 450 try: --> 451 bw = float(bw) 452 except:

ValueError: could not convert string to float: 'scott'

During handling of the above exception, another exception occurred:

RuntimeError Traceback (most recent call last) in 6 for col in default_df.columns: 7 print(col) ----> 8 distribution_compare_pretty(default_df,nondefault_df,col=col,figsize=None)

~/Developer/anaconda3/envs/gdd3.6/lib/python3.6/site-packages/pydqc/data_compare.py in distribution_compare_pretty(_df1, _df2, col, figsize, date_flag) 125 plt.legend(loc=1) 126 else: --> 127 ax1 = sns.distplot(df1_draw_values, color=TABLE1_DARK, hist=False, label='table1') 128 ax2 = sns.distplot(df2_draw_values, color=TABLE2_DARK, hist=False, label='table2') 129 y_low_1, y_up_1 = ax1.get_ylim()

~/Developer/anaconda3/envs/gdd3.6/lib/python3.6/site-packages/seaborn/distributions.py in distplot(a, bins, hist, kde, rug, fit, hist_kws, kde_kws, rug_kws, fit_kws, color, vertical, norm_hist, axlabel, label, ax) 231 if kde: 232 kde_color = kde_kws.pop("color", color) --> 233 kdeplot(a, vertical=vertical, ax=ax, color=kde_color, **kde_kws) 234 if kde_color != color: 235 kde_kws["color"] = kde_color

~/Developer/anaconda3/envs/gdd3.6/lib/python3.6/site-packages/seaborn/distributions.py in kdeplot(data, data2, shade, vertical, kernel, bw, gridsize, cut, clip, legend, cumulative, shade_lowest, cbar, cbar_ax, cbar_kws, ax, **kwargs) 703 ax = _univariate_kdeplot(data, shade, vertical, kernel, bw, 704 gridsize, cut, clip, legend, ax, --> 705 cumulative=cumulative, **kwargs) 706 707 return ax

~/Developer/anaconda3/envs/gdd3.6/lib/python3.6/site-packages/seaborn/distributions.py in _univariate_kdeplot(data, shade, vertical, kernel, bw, gridsize, cut, clip, legend, ax, cumulative, **kwargs) 293 x, y = _statsmodels_univariate_kde(data, kernel, bw, 294 gridsize, cut, clip, --> 295 cumulative=cumulative) 296 else: 297 # Fall back to scipy if missing statsmodels

~/Developer/anaconda3/envs/gdd3.6/lib/python3.6/site-packages/seaborn/distributions.py in _statsmodels_univariate_kde(data, kernel, bw, gridsize, cut, clip, cumulative) 365 fft = kernel == "gau" 366 kde = smnp.KDEUnivariate(data) --> 367 kde.fit(kernel, bw, fft, gridsize=gridsize, cut=cut, clip=clip) 368 if cumulative: 369 grid, y = kde.support, kde.cdf

~/Developer/anaconda3/envs/gdd3.6/lib/python3.6/site-packages/statsmodels/nonparametric/kde.py in fit(self, kernel, bw, fft, weights, gridsize, adjust, cut, clip) 138 density, grid, bw = kdensityfft(endog, kernel=kernel, bw=bw, 139 adjust=adjust, weights=weights, gridsize=gridsize, --> 140 clip=clip, cut=cut) 141 else: 142 density, grid, bw = kdensity(endog, kernel=kernel, bw=bw,

~/Developer/anaconda3/envs/gdd3.6/lib/python3.6/site-packages/statsmodels/nonparametric/kde.py in kdensityfft(X, kernel, bw, weights, gridsize, adjust, clip, cut, retgrid) 451 bw = float(bw) 452 except: --> 453 bw = bandwidths.select_bandwidth(X, bw, kern) # will cross-val fit this pattern? 454 bw *= adjust 455

~/Developer/anaconda3/envs/gdd3.6/lib/python3.6/site-packages/statsmodels/nonparametric/bandwidths.py in select_bandwidth(x, bw, kernel) 172 # eventually this can fall back on another selection criterion. 173 err = "Selected KDE bandwidth is 0. Cannot estimate density." --> 174 raise RuntimeError(err) 175 else: 176 return bandwidth

RuntimeError: Selected KDE bandwidth is 0. Cannot estimate density.