Question: I'm trying to plot a regplot using seaborn and i'm not unable to plot it and facing TypeError: Cannot cast array data from dtype('int64') to dtype('int32') according to the rule 'safe' .  My data has 731 rows and 16 column - >>> bike_df.info() <class 'pandas.core.frame.DataFrame'> RangeIndex: 731 entries, 0 to 730 Data columns (total 16 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 instant 731 non-null int64 1 dteday 731 non-null object 2 season 731 non-null int64 3 yr 731 non-null int64 4 mnth 731 non-null int64 5 holiday 731 non-null int64 6 weekday 731 non-null int64 7 workingday 731 non-null int64 8 weathersit 731 non-null int64 9 temp 731 non-null float64 10 atemp 731 non-null float64 11 hum 731 non-null float64 12 windspeed 731 non-null float64 13 casual 731 non-null int64 14 registered 731 non-null int64 15 cnt 731 non-null int64 dtypes: float64(4), int64(11), object(1) memory usage: 88.6+ KB  Here is a snippet of the data  And when i'm trying to plot regplot using seaborn - >>> sns.regplot(x="casual", y="cnt", data=bike_df); --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-54-68533af96906> in <module> ----> 1 sns.regplot(x="casual", y="cnt", data=bike_df); ~\AppData\Local\Continuum\anaconda3\envs\rstudio\lib\site-packages\seaborn\regression.py in regplot(x, y, data, x_estimator, x_bins, x_ci, scatter, fit_reg, ci, n_boot, units, seed, order, logistic, lowess, robust, logx, x_partial, y_partial, truncate, dropna, x_jitter, y_jitter, label, color, marker, scatter_kws, line_kws, ax) 816 scatter_kws["marker"] = marker 817 line_kws = {} if line_kws is None else copy.copy(line_kws) --> 818 plotter.plot(ax, scatter_kws, line_kws) 819 return ax 820 ~\AppData\Local\Continuum\anaconda3\envs\rstudio\lib\site-packages\seaborn\regression.py in plot(self, ax, scatter_kws, line_kws) 363 364 if self.fit_reg: --> 365 self.lineplot(ax, line_kws) 366 367 # Label the axes ~\AppData\Local\Continuum\anaconda3\envs\rstudio\lib\site-packages\seaborn\regression.py in lineplot(self, ax, kws) 406 """Draw the model.""" 407 # Fit the regression model --> 408 grid, yhat, err_bands = self.fit_regression(ax) 409 edges = grid[0], grid[-1] 410 ~\AppData\Local\Continuum\anaconda3\envs\rstudio\lib\site-packages\seaborn\regression.py in fit_regression(self, ax, x_range, grid) 214 yhat, yhat_boots = self.fit_logx(grid) 215 else: --> 216 yhat, yhat_boots = self.fit_fast(grid) 217 218 # Compute the confidence interval at each grid point ~\AppData\Local\Continuum\anaconda3\envs\rstudio\lib\site-packages\seaborn\regression.py in fit_fast(self, grid) 239 n_boot=self.n_boot, 240 units=self.units, --> 241 seed=self.seed).T 242 yhat_boots = grid.dot(beta_boots).T 243 return yhat, yhat_boots ~\AppData\Local\Continuum\anaconda3\envs\rstudio\lib\site-packages\seaborn\algorithms.py in bootstrap(*args, **kwargs) 83 for i in range(int(n_boot)): 84 resampler = integers(0, n, n) ---> 85 sample = [a.take(resampler, axis=0) for a in args] 86 boot_dist.append(f(*sample, **func_kwargs)) 87 return np.array(boot_dist) ~\AppData\Local\Continuum\anaconda3\envs\rstudio\lib\site-packages\seaborn\algorithms.py in <listcomp>(.0) 83 for i in range(int(n_boot)): 84 resampler = integers(0, n, n) ---> 85 sample = [a.take(resampler, axis=0) for a in args] 86 boot_dist.append(f(*sample, **func_kwargs)) 87 return np.array(boot_dist) TypeError: Cannot cast array data from dtype('int64') to dtype('int32') according to the rule 'safe'  I tried changing the datatypes using dtypes for all the rows like below -  >>> bike_df['cnt'] = bike_df['cnt'].astype(np.int32)  but this did not help and got the same error again while plotting. Any suggestions are appreciated. Thanks in advance.

Answer: Update: this bug is solved in Seaborn version 0.10.1 (April 2020). I encountered the same problem. It is issue 1950 at Seaborn's github. Related to running a 32-bit version of numpy. It will be solved in the next release. To work around the problem, I changed line 84 of my local version of Seaborn's algorithm.py: resampler = integers(0, n, n, dtype=np.int_)  This happened with:  numpy version: 1.18.1 seaborn version: 0.10.0