pandas行转列(unstack)

import pandas as pd

dict_df={'user_id': {0: 10001,
  1: 10001,
  2: 10001,
  3: 10001,
  4: 10002,
  5: 10002,
  6: 10002,
  7: 10002,
  8: 10003,
  9: 10003,
  10: 10003,
  11: 10003},
 'model': {0: 'eat',
  1: 'work',
  2: 'walk',
  3: 'sleep',
  4: 'eat',
  5: 'work',
  6: 'walk',
  7: 'sleep',
  8: 'eat',
  9: 'work',
  10: 'walk',
  11: 'sleep'},
 'hour': {0: 1.0,
  1: 10.0,
  2: 0.5,
  3: 7.0,
  4: 1.5,
  5: 9.0,
  6: 0.1,
  7: 1.2,
  8: 9.0,
  9: 1.0,
  10: 8.0,
  11: 9.0}}

df=pd.DataFrame(dict_df)

unstack()

df_tf=df.set_index(['user_id','model'])
df_tf=df_tf.unstack()
df_tf.reset_index(inplace=True)
df_tf

企业微信截图_a4dfcbeb-6b6a-401d-9eed-e58d4cef16c7.png

此时columns是多层索引,继续处理

企业微信截图_e788f6a7-58c1-4c9e-804b-1c2d3c97aacd.png

#删除0层索引
df_tf.columns=df_tf.columns.droplevel(0) 
df_tf.rename(columns={'':'user_id'},inplace=True) 
df_tf

企业微信截图_dbd34074-8058-4012-a6ba-8c9b4cc6b13c.png

#强制更改列名(注意顺序！！！)
df_tf.columns=['user_id','eat', 'sleep', 'walk', 'work']
df_tf

企业微信截图_9ddb95c8-8265-4a75-b6d9-cd78dad12f79.png