1

Im trying to filter a dataframe by date. But filter it with expressions like this would be really cumbersome for a date like "2019-11-01 10:15:00".

My goal is to do something like the python version:

use polars::export::chrono::NaiveDateTime;
use polars::prelude::*;
fn main() -> Result<(), Box<dyn std::error::Error>> {
    let df = LazyCsvReader::new(path)
        .with_parse_dates(true)
        .has_header(true)
        .finish()?
        .collect()?;

    let dt = NaiveDateTime::parse_from_str("2019-11-01 10:15:00", "%Y-%m-%d %H:%M:%S")?;

    //This will not compile!
    let filtered = df.filter(col("time") < dt); 
}

However I'm having a really hard time to filter the dateframe in-place or just creating a boolean mask.

nklsla
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1 Answers1

1

After more time than I dare to admit I finally solved it by using the eager API, there is probably a better solution in the Lazy-API but this works for now!

use polars::export::chrono::NaiveDateTime;
use polars::prelude::*;
fn main() -> Result<(), Box<dyn std::error::Error>> {

    let df = LazyCsvReader::new(path)
        .with_parse_dates(true)
        .has_header(true)
        .finish()?
        .collect()?;

// Set date to filter by
    let dt = NaiveDateTime::parse_from_str("2019-11-01 10:15:00", "%Y-%m-%d %H:%M:%S")?;

// Create boolean mask
    let mask = df["time"]
        .datetime()?
        .as_datetime_iter()
        .map(|x| x.unwrap() < dt)
        .collect();

// New filtered df
    let filtered_df = df.filter(&mask)?;
}

To get a date value from the "time" column and parse it to as a NaiveDateTime:

fn main() -> Result<(), Box<dyn std::error::Error>> {

    // Lets take the last date from a series of datetime[µs]
    let date: Vec<Option<NaiveDateTime>> = df["time"]
        .tail(Some(1))
        .datetime()?
        .as_datetime_iter()
        .collect();

    // Create new NaiveDateTime, can be used as filter/condition in map-function
    let dt2 = NaiveDateTime::parse_from_str(&date[0].unwrap().to_string(), "%Y-%m-%d %H:%M:%S")?;
}
nklsla
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