Parsing datetime strings

You're a London transport analyst tasked with understanding summertime bike-sharing demand patterns. The dataset contains hourly rental data from July, but the time column is stored as strings in "MM-DD-YYYY HH:MM" format. To analyze when demand peaks, you first need to convert it to a proper Datetime dtype.

polars is loaded as pl. The DataFrame bikes is available with columns time, rentals, and temp.

Bu egzersiz

Data Transformation with Polars

kursunun bir parçasıdır

Kursu Görüntüle

Egzersiz talimatları

Parse the time column to a Datetime dtype using the format "%m-%d-%Y %H:%M".

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Parse the time column to Datetime
bikes.with_columns(
    pl.col("time").____.____(pl.____, "%m-%d-%Y %H:%M")
)

Kodu Düzenle ve Çalıştır