text: Title: dask-expr increasing calculation time
  Body: Hi guys!
  I would like to report a possible bug on dask-expr. 
  
  Runing this code with dask-expr is tooking ~10 seconds on my machine
  
  Now, running without dask-expr  took ~2 secods
  
  I´ve attached a sample csv file as data sample.
  [a (1).csv](https://github.com/user-attachments/files/17492243/a.1.csv)
  
  ```
  import dask.dataframe as dd
  import pandas as pd 
  
  df = dd.read_csv('a (1).csv')
  
  df.head()
  novas_colunas = [
      'CD_5_AJST_PVS', 'CD_5_DT_CTB_AJST_PVS', 'CD_6_RCBT_RC', 'CD_6_DT_CTB_RCBT_RC',
      'CD_7_RVSA_RCBT_RC', 'CD_7_DT_CTB_RVSA_RCBT_RC', 'CD_8_PGTO_CBAC', 'CD_9_RVSA_PGTO_CBAC'
  ]
  for coluna in novas_colunas:
      df[coluna] = pd.Series(dtype='datetime64[ns]')
  
  df['CD_5_AJST_PVS'] = df['CD_5_AJST_PVS'].mask(cond=(df['codigoTipoEvento'] == 5), other=df['dataHoraEvento'])
  df['CD_5_DT_CTB_AJST_PVS'] = df['CD_5_DT_CTB_AJST_PVS'].mask(cond=(df['codigoTipoEvento'] == 5), other=df['dataHoraEvento'])
      
  df['CD_6_RCBT_RC'] = df['CD_6_RCBT_RC'].mask(cond=(df['codigoTipoEvento'] == 6), other=df['dataHoraEvento'])
  df['CD_6_DT_CTB_RCBT_RC'] = df['CD_6_DT_CTB_RCBT_RC'].mask(cond=(df['codigoTipoEvento'] == 6), other=df['dataHoraEvento'])
      
  df['CD_7_RVSA_RCBT_RC'] = df['CD_7_RVSA_RCBT_RC'].mask(cond=(df['codigoTipoEvento'] == 6), other=df['dataHoraEvento'])
  df['CD_7_DT_CTB_RVSA_RCBT_RC'] = df['CD_7_DT_CTB_RVSA_RCBT_RC'].mask(cond=(df['codigoTipoEvento'] == 6), other=df['dataHoraEvento'])
      
  df['CD_8_PGTO_CBAC'] = df['CD_8_PGTO_CBAC'].mask(cond=(df['codigoTipoEvento'] == 6), other=df['dataHoraEvento'])
  
  df['CD_9_RVSA_PGTO_CBAC'] = df['CD_9_RVSA_PGTO_CBAC'].mask(cond=(df['codigoTipoEvento'] == 6), other=df['dataHoraEvento'])
  
  df = df.drop(columns = ['codigoTipoEvento', 'dataHoraEvento'])
  df.compute()
  ```
  
  
  
  **Environment**:
  
  - Dask version: 2024.10.0
  - dask-expr : 1.1.16
  - Python version: 3.11
  - Operating System: Windows
  - Install method (conda, pip, source): Pip
  