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Please enable JavaScript in your browser settings or update your browser.Lære Challenge: Average Metrics Across Taxi Types | Working with Dates and Times in pandas
Dealing with Dates and Times in Python

bookChallenge: Average Metrics Across Taxi Types

Great! As for now, we have our dataset cleared from abnormally long rides and rides with ending time preceded starting. As we investigated, it happened because of misusage of 12 and 24-hour formats.

Let's try to find out some interesting insights from this dataset.

Oppgave

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  1. Apply .total_seconds() function to duration column using map and lambda functions.
  2. Group observations by taxi type (vendor_id column). Then, choose columns dist_meters, duration, and calculate mean. Then apply function avg_m to dist_meters and avg_dur to duration. The functions are defined in the code.

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Seksjon 4. Kapittel 8
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bookChallenge: Average Metrics Across Taxi Types

Sveip for å vise menyen

Great! As for now, we have our dataset cleared from abnormally long rides and rides with ending time preceded starting. As we investigated, it happened because of misusage of 12 and 24-hour formats.

Let's try to find out some interesting insights from this dataset.

Oppgave

Swipe to start coding

  1. Apply .total_seconds() function to duration column using map and lambda functions.
  2. Group observations by taxi type (vendor_id column). Then, choose columns dist_meters, duration, and calculate mean. Then apply function avg_m to dist_meters and avg_dur to duration. The functions are defined in the code.

Løsning

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Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 4. Kapittel 8
single

single

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