我想向熊猫数据框添加新索引

用途

ngroup

• 对于新列

  index

  df[‘index’] = df.groupby(‘date’, sort=False).ngroup() + 1
  print (df)
  date price neg_vol pos_vol index
  0 2017-10-17 01:00:00 51.88 11 4 1
  1 2017-10-17 01:00:00 51.89 10 2 1
  2 2017-10-17 01:00:00 51.90 16 27 1
  3 2017-10-17 01:00:00 51.91 1 10 1
  4 2017-10-17 01:05:00 51.87 12 0 2
  5 2017-10-17 01:05:00 51.88 0 12 2
  6 2017-10-17 01:10:00 51.87 8 0 3
  7 2017-10-17 01:10:00 51.88 0 5 3
  8 2017-10-17 01:15:00 51.87 12 0 4
  9 2017-10-17 01:15:00 51.88 0 8 4
  10 2017-10-17 01:20:00 51.87 6 0 5
  
  
  

• 用于新索引

  df.index = df.groupby(‘date’, sort=False).ngroup() + 1
  print (df)
  date price neg_vol pos_vol
  1 2017-10-17 01:00:00 51.88 11 4
  1 2017-10-17 01:00:00 51.89 10 2
  1 2017-10-17 01:00:00 51.90 16 27
  1 2017-10-17 01:00:00 51.91 1 10
  2 2017-10-17 01:05:00 51.87 12 0
  2 2017-10-17 01:05:00 51.88 0 12
  3 2017-10-17 01:10:00 51.87 8 0
  3 2017-10-17 01:10:00 51.88 0 5
  4 2017-10-17 01:15:00 51.87 12 0
  4 2017-10-17 01:15:00 51.88 0 8
  5 2017-10-17 01:20:00 51.87 6 0

另一个解决方案是

factorize

df['index'] = pd.factorize(df['date'])[0] + 1

df.index = pd.factorize(df['date'])[0] + 1