Just upgraded numpy to the latest intel conda’s, I am at pandas 2.2.1, numpy 1.24.3 and numexpr 2.10.0

If I try something simple like

   df=pd.DataFrame(index=[0,1,2,3])
   df["A"] = [1,2,np.NaN, 3]
   print(df)

then I get six run time warnings.

RuntimeWarning: invalid value encountered in less
  has_small_values = ((abs_vals < 10 ** (-self.digits)) & (abs_vals > 0)).any()  
RuntimeWarning: invalid value encountered in greater
  has_small_values = ((abs_vals < 10 ** (-self.digits)) & (abs_vals > 0)).any() 
RuntimeWarning: invalid value encountered in greater
  has_large_values = (abs_vals > 1e6).any()  
RuntimeWarning: invalid value encountered in less
  has_small_values = ((abs_vals < 10 ** (-self.digits)) & (abs_vals > 0)).any()  
RuntimeWarning: invalid value encountered in greater
  has_small_values = ((abs_vals < 10 ** (-self.digits)) & (abs_vals > 0)).any()

For a more complicated code the result is just overwhelming, hundreds and hundreds of such messages.

Did numpy drop support for NaN ??