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Expand Functionality of the .iloc[] Function | Get Familiar With Indexing and Selecting Data
Advanced Techniques in pandas

Expand Functionality of the .iloc[] Function

We will learn some new features that iloc[] provides. The coolest one is that we can specify indices of both rows and columns. This function is similar to .loc[], but the last index of the slicing is exclusive.

Look at the example and the relevant output:

  • data.iloc[1, 2] - extracts the item located in the dataset's second row and third column. The first index corresponds to the row index, and the second to the column index. Indeed, you can skip one of them;
  • data.iloc[:, 3] - extracts all values from the rows of the fourth column 'IMDb-Rating';
  • data.iloc[3, :] or data.iloc[3] - extracts the 4th row and all relevant columns;
  • data.iloc[:2, 1:4] - extracts the first two rows and column with the indices 1, 2, 3;
  • data.iloc[[2,4],[1,3]] - extracts the rows with indices 2,4 and columns with the indices 1, 3.

Tarea

Your task here is just to practice. Output information on the first 50 rows and the columns with indices 1 and 4.

¿Todo estuvo claro?

Sección 1. Capítulo 6
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course content

Contenido del Curso

Advanced Techniques in pandas

Expand Functionality of the .iloc[] Function

We will learn some new features that iloc[] provides. The coolest one is that we can specify indices of both rows and columns. This function is similar to .loc[], but the last index of the slicing is exclusive.

Look at the example and the relevant output:

  • data.iloc[1, 2] - extracts the item located in the dataset's second row and third column. The first index corresponds to the row index, and the second to the column index. Indeed, you can skip one of them;
  • data.iloc[:, 3] - extracts all values from the rows of the fourth column 'IMDb-Rating';
  • data.iloc[3, :] or data.iloc[3] - extracts the 4th row and all relevant columns;
  • data.iloc[:2, 1:4] - extracts the first two rows and column with the indices 1, 2, 3;
  • data.iloc[[2,4],[1,3]] - extracts the rows with indices 2,4 and columns with the indices 1, 3.

Tarea

Your task here is just to practice. Output information on the first 50 rows and the columns with indices 1 and 4.

¿Todo estuvo claro?

Sección 1. Capítulo 6
toggle bottom row
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