How to use a polars column with offset string to add to another date column
Question:
Suppose you have
df=pl.DataFrame(
{
"date":["2022-01-01", "2022-01-02"],
"hroff":[5,2],
"minoff":[1,2]
}).with_column(pl.col('date').str.strptime(pl.Date,"%Y-%m-%d"))
and you want to make a new column that adds the hour and min offsets to the date column. The only thing I saw was the dt.offset_by
method. I made an extra column
df=df.with_column((pl.col('hroff')+"h"+pl.col('minoff')+"m").alias('offset'))
and then tried
df.with_column(pl.col('date')
.cast(pl.Datetime).dt.with_time_zone('UTC')
.dt.offset_by(pl.col('offset')).alias('newdate'))
but that doesn’t work because dt.offset_by
only takes a fixed string, not another column.
What’s the best way to do that?
Answers:
Use pl.duration
:
import polars as pl
df = pl.DataFrame({
"date": pl.Series(["2022-01-01", "2022-01-02"]).str.strptime(pl.Datetime(time_zone="UTC"), "%Y-%m-%d"),
"hroff": [5, 2],
"minoff": [1, 2]
})
print(df.select(
pl.col("date") + pl.duration(hours=pl.col("hroff"), minutes=pl.col("minoff"))
))
shape: (2, 1)
┌─────────────────────┐
│ date │
│ --- │
│ datetime[μs] │
╞═════════════════════╡
│ 2022-01-01 05:01:00 │
├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ 2022-01-02 02:02:00 │
└─────────────────────┘
Suppose you have
df=pl.DataFrame(
{
"date":["2022-01-01", "2022-01-02"],
"hroff":[5,2],
"minoff":[1,2]
}).with_column(pl.col('date').str.strptime(pl.Date,"%Y-%m-%d"))
and you want to make a new column that adds the hour and min offsets to the date column. The only thing I saw was the dt.offset_by
method. I made an extra column
df=df.with_column((pl.col('hroff')+"h"+pl.col('minoff')+"m").alias('offset'))
and then tried
df.with_column(pl.col('date')
.cast(pl.Datetime).dt.with_time_zone('UTC')
.dt.offset_by(pl.col('offset')).alias('newdate'))
but that doesn’t work because dt.offset_by
only takes a fixed string, not another column.
What’s the best way to do that?
Use pl.duration
:
import polars as pl
df = pl.DataFrame({
"date": pl.Series(["2022-01-01", "2022-01-02"]).str.strptime(pl.Datetime(time_zone="UTC"), "%Y-%m-%d"),
"hroff": [5, 2],
"minoff": [1, 2]
})
print(df.select(
pl.col("date") + pl.duration(hours=pl.col("hroff"), minutes=pl.col("minoff"))
))
shape: (2, 1)
┌─────────────────────┐
│ date │
│ --- │
│ datetime[μs] │
╞═════════════════════╡
│ 2022-01-01 05:01:00 │
├╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ 2022-01-02 02:02:00 │
└─────────────────────┘