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Lære Types Conversion | Data Validation
Preprocessing Data
course content

Kursusindhold

Preprocessing Data

Preprocessing Data

1. Data Exploration
2. Data Cleaning
3. Data Validation
4. Normalization & Standardization
5. Data Encoding

book
Types Conversion

You can discover that data can be stored in the dataset in the wrong format or type. The most common cases are:

  • storing integer or float values as string variables.
  • storing date and time values as strings.
  • storing values in a form that can be converted to a more suitable one.

Let's explore the dataset exercise containing info about diet, pulse, time, and kind of different exercises. There is sample data:

unnamediddietpulsetimekind
3512low fat10430 minwalking
6422low fat10415 minrunning
104low fat8215 minrest
187no fat871 minrest
4817no fat1031 minwalking

It makes sense to modify the time column data: all rows contain the duration in minutes, so info about time units (min, sec, ot hours) is useless. We're gonna remove the extra symbols and store only numerical values, which additionally will be converted to int.

Opgave

Swipe to start coding

Apply the type conversion to the time column. Remove the last 4 symbols which are equal to min and convert the rest to int. Check the sample.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 3. Kapitel 1
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book
Types Conversion

You can discover that data can be stored in the dataset in the wrong format or type. The most common cases are:

  • storing integer or float values as string variables.
  • storing date and time values as strings.
  • storing values in a form that can be converted to a more suitable one.

Let's explore the dataset exercise containing info about diet, pulse, time, and kind of different exercises. There is sample data:

unnamediddietpulsetimekind
3512low fat10430 minwalking
6422low fat10415 minrunning
104low fat8215 minrest
187no fat871 minrest
4817no fat1031 minwalking

It makes sense to modify the time column data: all rows contain the duration in minutes, so info about time units (min, sec, ot hours) is useless. We're gonna remove the extra symbols and store only numerical values, which additionally will be converted to int.

Opgave

Swipe to start coding

Apply the type conversion to the time column. Remove the last 4 symbols which are equal to min and convert the rest to int. Check the sample.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 3. Kapitel 1
Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Vi beklager, at noget gik galt. Hvad skete der?
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