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.
Latihan ini adalah bagian dari kursus
Data Transformation with Polars
Petunjuk latihan
- Parse the
timecolumn to a Datetime dtype using the format"%m-%d-%Y %H:%M".
Latihan interaktif praktis
Cobalah latihan ini dengan menyelesaikan kode contoh berikut.
# Parse the time column to Datetime
bikes.with_columns(
pl.col("time").____.____(pl.____, "%m-%d-%Y %H:%M")
)