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Lære Expanding Functionality of the .iloc[] Attribute | Getting Familiar With Indexing and Selecting Data
Advanced Techniques in pandas
course content

Kursinnhold

Advanced Techniques in pandas

Advanced Techniques in pandas

1. Getting Familiar With Indexing and Selecting Data
2. Dealing With Conditions
3. Extracting Data
4. Aggregating Data
5. Preprocessing Data

book
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.
Oppgave

Swipe to start coding

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

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 1. Kapittel 6
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book
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.
Oppgave

Swipe to start coding

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

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 1. Kapittel 6
Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
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