Empresas
Empregos
  • Sobre nós
  • Soluções
    • Publicação de vagas
      Publique sua vaga e receba candidatos qualificados em 48h.
    • Avaliações de candidatos
      Mais de 500 testes técnicos e psicológicos, mais anti-fraude.
    • Headhunting
      Busca executiva personalizada do início ao fim.
    • Folha de Pagamento + EOR
      Dispersão de folha e EOR em mais de 15 países da LATAM.
  • Preços
  • Empregos

0

548
Visualizações
What is the difference between save a pandas dataframe to pickle and to csv?

I am learning python pandas. I see a tutorial which shows two ways to save a pandas dataframe.

  1. pd.to_csv('sub.csv') and to open pd.read_csv('sub.csv')

  2. pd.to_pickle('sub.pkl') and to open pd.read_pickle('sub.pkl')

The tutorial says to_pickle is to save the dataframe to disk. I am confused about this. Because when I use to_csv, I did see a csv file appears in the folder, which I assume is also save to disk right?

In general, why we want to save a dataframe using to_pickle rather than save it to csv or txt or other format?

over 4 years ago · Santiago Trujillo
2 Respostas
Responde à pergunta

0

csv

  • ✅human readable
  • ✅cross platform
  • ⛔slower
  • ⛔more disk space
  • ⛔doesn't preserve types in some cases

pickle

  • ✅fast saving/loading
  • ✅less disk space
  • ⛔non human readable
  • ⛔python only

Also take a look at parquet format (to_parquet, read_parquet)

  • ✅fast saving/loading
  • ✅less disk space than pickle
  • ✅supported by many platforms
  • ⛔non human readable
over 4 years ago · Santiago Trujillo Relatório

0

Pickle is a serialized way of storing a Pandas dataframe. Basically, you are writing down the exact representation of the dataframe to disk. This means the types of the columns are and the indices are the same. If you simply save a file as csv, you are just storing it as a comma separated list. Depending on your data set, some information will be lost when you load it back up.

You can read more about pickle library in python, here.

over 4 years ago · Santiago Trujillo Relatório
Responde à pergunta
Encontrar trabalhos remotos

Descubra a nova forma de encontrar um emprego!

melhores empregos
Principais categorias de trabalho
Empresas
Postar vaga Preços Comercial
Jurídico
Termos e Condições Política de privacidade
© 2026 PeakU Inc. All Rights Reserved.
Andres GPT
Recomende algumas ofertas para mim
Preciso de ajuda