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dataframedictionaryiterationpython-polars

Polars column from conditioned look up of dictionary values


I want to map a key in one Polars DataFrame to another Polars DF base on the relationships between columns. This is just a sample, the full DF1 and DF2 is much larger (2.5 million and 1.5 million rows respectively.

DF1 = pl.DataFrame({
'chr' : ["GL000008.2", "GL000008.2", "GL000008.2", "GL000008.2","GL000008.2", "GL000008.2"], 
'start': [14516,17380,17381,20177,22254,24357], 
'end': [14534,17399,17399,20195,22274,24377]
})

DF2 = pl.DataFrame({ 
'key' : [1,2,3,4,5,6],
'chrom' : ["GL000008.2", "GL000008.2", "GL000008.2", "GL000008.2","GL000008.2", "GL000008.2"], 
'start': [14516,15377,17376,20177,22254, 24357], 
'end': [14534,15403,17399,20195,22274,24377]})

What I want is:

DF1 = pl.DataFrame({
'chr' : ["GL000008.2", "GL000008.2", "GL000008.2", "GL000008.2","GL000008.2", "GL000008.2"], 
'start': [14516,17380,17381,20177,22254,24357], 
'end': [14534,17399,17399,20195,22274,24377],
'key': [1,3,3,4,5,6]
})

I'd like to assign the key from DF2 to DF1 when chrom matches chr and the start and end in DF1 are contained within the begin and end in DF2.

I first attempted to iterate through the rows of DF1, looking up the matching entry in DF2:

sz = len(DF1[:,0])

for i in range(sz):
    DF1[i,"key"] = DF2.filter(
        (pl.col("chrom") == DF1[i,"chr"])
        & (pl.col("begin") <= DF1[i,"start"])
        & (pl.col("end") >= DF1[i,"end"])
        ).select('key')[0,0]

Row iteration through a DF is incredibly slow. This takes about 10 hours.

I also tried using a np.array instead of directly into the df. thats a little faster, but still very slow.

I'm looking for a way to accomplish this using the native Polars data structure. I don't have key to join on so the join and join_asof strategies don't seem to work.


Solution

  • join and filter should give you what you need:

    (
        df1.join(df2, left_on="chr", right_on="chrom")
        .filter(
            (pl.col("start") >= pl.col("start_right"))
            & (pl.col("end") <= pl.col("end_right"))
        )
        .drop(["start_right", "end_right"])
    )
    
    shape: (6, 4)
    ┌────────────┬───────┬───────┬─────┐
    │ chr        ┆ start ┆ end   ┆ key │
    │ ---        ┆ ---   ┆ ---   ┆ --- │
    │ str        ┆ i64   ┆ i64   ┆ i64 │
    ╞════════════╪═══════╪═══════╪═════╡
    │ GL000008.2 ┆ 14516 ┆ 14534 ┆ 1   │
    │ GL000008.2 ┆ 17380 ┆ 17399 ┆ 3   │
    │ GL000008.2 ┆ 17381 ┆ 17399 ┆ 3   │
    │ GL000008.2 ┆ 20177 ┆ 20195 ┆ 4   │
    │ GL000008.2 ┆ 22254 ┆ 22274 ┆ 5   │
    │ GL000008.2 ┆ 24357 ┆ 24377 ┆ 6   │
    └────────────┴───────┴───────┴─────┘