[pandas] find missing data in each row

import pandas as pd
import numpy as np

def find_nan_columns(df):
  ix_row, ix_col = np.where(np.asanyarray(np.isnan(df)))
  prods = pd.DataFrame({'row_idx':ix_row,
                        'col_idx':ix_col})
  b = [-np.inf] + np.arange(len(df.columns)).tolist() + [np.inf]
  l = ['Error'] + df.columns.tolist()
  prods['label'] = pd.cut(prods['col_idx'], bins=b, labels=l, right=False)
  prods = prods.drop(['col_idx'], axis=1)

  keys, values = prods.sort_values('row_idx').values.T
  ukeys, index = np.unique(keys, True)
  arrays = np.split(values, index[1:])
  df2 = pd.DataFrame({'Row': ukeys,
                      'Missing data': [list(a) for a in arrays]})
  return df2