Expanding Functionality of the .iloc[] Attribute

We will learn some new features that iloc[] provides. The coolest one is that we can specify indices of both rows and columns. This attribute 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.

Завдання

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

Завдання

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

Все було зрозуміло?

Секція 1. Розділ 6

Expanding Functionality of the .iloc[] Attribute

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.

Завдання

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

Завдання

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

Все було зрозуміло?

Секція 1. Розділ 6

Expanding Functionality of the .iloc[] Attribute

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.

Завдання

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

Завдання

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

Все було зрозуміло?

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.

Завдання

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

Секція 1. Розділ 6

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