def makeMissingCustomDataframe(nrows, ncols, density=0.9, random_state=None, c_idx_names=True, r_idx_names=True, c_idx_nlevels=1, r_idx_nlevels=1, data_gen_f=None, c_ndupe_l=None, r_ndupe_l=None, dtype=None, c_idx_type=None, r_idx_type=None):
 df = makeCustomDataframe(nrows, ncols, c_idx_names=c_idx_names, r_idx_names=r_idx_names, c_idx_nlevels=c_idx_nlevels, r_idx_nlevels=r_idx_nlevels, data_gen_f=data_gen_f, c_ndupe_l=c_ndupe_l, r_ndupe_l=r_ndupe_l, dtype=dtype, c_idx_type=c_idx_type, r_idx_type=r_idx_type)
 (i, j) = _create_missing_idx(nrows, ncols, density, random_state)
 df.values[(i, j)] = np.nan
 return df

def makeMissingCustomDataframe ( nrows , ncols , density = 0.9 , random_state = None , c_idx_names = True , r_idx_names = True , c_idx_nlevels = 1 , r_idx_nlevels = 1 , data_gen_f = None , c_ndupe_l = None , r_ndupe_l = None , dtype = None , c_idx_type = None , r_idx_type = None ) : df = makeCustomDataframe ( nrows , ncols , c_idx_names = c_idx_names , r_idx_names = r_idx_names , c_idx_nlevels = c_idx_nlevels , r_idx_nlevels = r_idx_nlevels , data_gen_f = data_gen_f , c_ndupe_l = c_ndupe_l , r_ndupe_l = r_ndupe_l , dtype = dtype , c_idx_type = c_idx_type , r_idx_type = r_idx_type ) ( i , j ) = _create_missing_idx ( nrows , ncols , density , random_state ) df . values [ ( i , j ) ] = np . nan return df
parameters density : float .