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  1. ValueError                                Traceback (most recent call last)
  2. <ipython-input-58-e0ac8c5bf9eb> in <module>
  3. ----> 1 sns.lmplot(x='TDS', y='Li', data=df_sub, hue='Group Location', legend=True)
  4.       2 plt.show()
  5.  
  6. C:ProgramDataAnaconda3libsite-packagesseabornregression.py in lmplot(x, y, data, hue, col, row, palette, col_wrap, height, aspect, markers, sharex, sharey, hue_order, col_order, row_order, legend, legend_out, x_estimator, x_bins, x_ci, scatter, fit_reg, ci, n_boot, units, order, logistic, lowess, robust, logx, x_partial, y_partial, truncate, x_jitter, y_jitter, scatter_kws, line_kws, size)
  7.     587         scatter_kws=scatter_kws, line_kws=line_kws,
  8.     588         )
  9. --> 589     facets.map_dataframe(regplot, x, y, **regplot_kws)
  10.     590
  11.     591     # Add a legend
  12.  
  13. C:ProgramDataAnaconda3libsite-packagesseabornaxisgrid.py in map_dataframe(self, func, *args, **kwargs)
  14.     818
  15.     819             # Draw the plot
  16. --> 820             self._facet_plot(func, ax, args, kwargs)
  17.     821
  18.     822         # Finalize the annotations and layout
  19.  
  20. C:ProgramDataAnaconda3libsite-packagesseabornaxisgrid.py in _facet_plot(self, func, ax, plot_args, plot_kwargs)
  21.     836
  22.     837         # Draw the plot
  23. --> 838         func(*plot_args, **plot_kwargs)
  24.     839
  25.     840         # Sort out the supporting information
  26.  
  27. C:ProgramDataAnaconda3libsite-packagesseabornregression.py in regplot(x, y, data, x_estimator, x_bins, x_ci, scatter, fit_reg, ci, n_boot, units, order, logistic, lowess, robust, logx, x_partial, y_partial, truncate, dropna, x_jitter, y_jitter, label, color, marker, scatter_kws, line_kws, ax)
  28.     787     scatter_kws["marker"] = marker
  29.     788     line_kws = {} if line_kws is None else copy.copy(line_kws)
  30. --> 789     plotter.plot(ax, scatter_kws, line_kws)
  31.     790     return ax
  32.     791
  33.  
  34. C:ProgramDataAnaconda3libsite-packagesseabornregression.py in plot(self, ax, scatter_kws, line_kws)
  35.     342             self.scatterplot(ax, scatter_kws)
  36.     343         if self.fit_reg:
  37. --> 344             self.lineplot(ax, line_kws)
  38.     345
  39.     346         # Label the axes
  40.  
  41. C:ProgramDataAnaconda3libsite-packagesseabornregression.py in lineplot(self, ax, kws)
  42.     387
  43.     388         # Fit the regression model
  44. --> 389         grid, yhat, err_bands = self.fit_regression(ax)
  45.     390
  46.     391         # Get set default aesthetics
  47.  
  48. C:ProgramDataAnaconda3libsite-packagesseabornregression.py in fit_regression(self, ax, x_range, grid)
  49.     206             yhat, yhat_boots = self.fit_logx(grid)
  50.     207         else:
  51. --> 208             yhat, yhat_boots = self.fit_fast(grid)
  52.     209
  53.     210         # Compute the confidence interval at each grid point
  54.  
  55. C:ProgramDataAnaconda3libsite-packagesseabornregression.py in fit_fast(self, grid)
  56.     228
  57.     229         beta_boots = algo.bootstrap(X, y, func=reg_func,
  58. --> 230                                     n_boot=self.n_boot, units=self.units).T
  59.     231         yhat_boots = grid.dot(beta_boots).T
  60.     232         return yhat, yhat_boots
  61.  
  62. C:ProgramDataAnaconda3libsite-packagesseabornalgorithms.py in bootstrap(*args, **kwargs)
  63.      84     boot_dist = []
  64.      85     for i in range(int(n_boot)):
  65. ---> 86         resampler = rs.randint(0, n, n)
  66.      87         sample = [a.take(resampler, axis=0) for a in args]
  67.      88         boot_dist.append(f(*sample, **func_kwargs))
  68.  
  69. mtrand.pyx in mtrand.RandomState.randint()
  70.  
  71. ValueError: low >= high
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