Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Lære The `iloc` Property | Fetching Data from DataFrames
Pandas: First Steps

bookThe `iloc` Property

The iloc property in Pandas allows us to access specific parts of a DataFrame using numerical positions.

You can use iloc to access:

  • A single element;
  • A single row;
  • A single column;
  • A range of rows;
  • A range of columns;
  • A range of rows and columns.

General Syntax

DataFrame.iloc[row_position, column_position]

You can also slice:

DataFrame.iloc[start_row:end_row, start_col:end_col]

Example

12345678910111213141516171819202122232425
import pandas as pd df = pd.DataFrame({ 'Name': ['Alice', 'Bob', 'Charlie', 'Daisy'], 'Age': [25, 30, 35, 28], 'City': ['New York', 'Paris', 'London', 'Berlin'] }) # Single element print('>> Single Element:\n', df.iloc[1, 2]) # Single row print('\n>> Single Row:\n', df.iloc[2]) # Single column print('\n>> Single Column:\n', df.iloc[:, 1]) # Range of rows print('\n>> Range of Rows:\n', df.iloc[1:3]) # Range of columns print('\n>> Range of Columns:\n', df.iloc[:, 0:2]) # Range of rows and columns print('\n>> Range of Rows & Columns:\n', df.iloc[1:3, 0:2])
copy
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 3. Kapitel 10

Spørg AI

expand

Spørg AI

ChatGPT

Spørg om hvad som helst eller prøv et af de foreslåede spørgsmål for at starte vores chat

Suggested prompts:

Spørg mig spørgsmål om dette emne

Opsummér dette kapitel

Vis virkelige eksempler

Awesome!

Completion rate improved to 2.7

bookThe `iloc` Property

Stryg for at vise menuen

The iloc property in Pandas allows us to access specific parts of a DataFrame using numerical positions.

You can use iloc to access:

  • A single element;
  • A single row;
  • A single column;
  • A range of rows;
  • A range of columns;
  • A range of rows and columns.

General Syntax

DataFrame.iloc[row_position, column_position]

You can also slice:

DataFrame.iloc[start_row:end_row, start_col:end_col]

Example

12345678910111213141516171819202122232425
import pandas as pd df = pd.DataFrame({ 'Name': ['Alice', 'Bob', 'Charlie', 'Daisy'], 'Age': [25, 30, 35, 28], 'City': ['New York', 'Paris', 'London', 'Berlin'] }) # Single element print('>> Single Element:\n', df.iloc[1, 2]) # Single row print('\n>> Single Row:\n', df.iloc[2]) # Single column print('\n>> Single Column:\n', df.iloc[:, 1]) # Range of rows print('\n>> Range of Rows:\n', df.iloc[1:3]) # Range of columns print('\n>> Range of Columns:\n', df.iloc[:, 0:2]) # Range of rows and columns print('\n>> Range of Rows & Columns:\n', df.iloc[1:3, 0:2])
copy
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 3. Kapitel 10
some-alt