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Import and Export Files | Unveiling the Power of Data Manipulation with Pandas
Unveiling the Power of Data Manipulation with Pandas
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Contenido del Curso

Unveiling the Power of Data Manipulation with Pandas

Import and Export Files

You may be wondering: Yes, working with DataFrames is engaging, but what if I have a dataset of 1,000,000 rows? I can't manually input every single row.

For this reason, pandas offers several methods to read and write data from and to various file formats, such as CSV, Excel, and JSON. These functions come with many options and parameters that allow you to customize how data is read and written.

P.S. These are just a few of the methods available. Did you know that you can also run SQL queries via pd.read_sql()?

Tarea

  1. Use the appropriate function to read the CSV file into a DataFrame.
  2. Use the appropriate function to export the DataFrame to an Excel file.
  3. Display the first 6 rows of the data DataFrame.

Tarea

  1. Use the appropriate function to read the CSV file into a DataFrame.
  2. Use the appropriate function to export the DataFrame to an Excel file.
  3. Display the first 6 rows of the data DataFrame.

Mark tasks as Completed
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

You may be wondering: Yes, working with DataFrames is engaging, but what if I have a dataset of 1,000,000 rows? I can't manually input every single row.

For this reason, pandas offers several methods to read and write data from and to various file formats, such as CSV, Excel, and JSON. These functions come with many options and parameters that allow you to customize how data is read and written.

P.S. These are just a few of the methods available. Did you know that you can also run SQL queries via pd.read_sql()?

Tarea

  1. Use the appropriate function to read the CSV file into a DataFrame.
  2. Use the appropriate function to export the DataFrame to an Excel file.
  3. Display the first 6 rows of the data DataFrame.

Mark tasks as Completed
Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Sección 1. Capítulo 3
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