Python polars:在pl.DataFrame列中为每个唯一值创建行,为另一列创建列,为第三列创建值

在Polars中,可以通过使用枢轴操作来获得所需的结果。以下是针对特定DataFrame的操作方法:

import polars as pl

d = {
    'id': ['N/A', 'N/A', '1', '1', '2'],
    'type': ['red', 'blue', 'yellow', 'green', 'yellow'],
    'area': [0, 0, 3, 4, 5]
}

dp = pl.DataFrame(d)

# Remove rows with 'N/A' in the 'id' column
dp = dp.filter(pl.col("id") != "N/A")

# Perform the pivot operation
dp = dp.pivot('id', 'type', 'area', aggfn='first')

# Fill missing values with 0
dp = dp.fill_null(0)

print(dp)

输出:

shape: (2, 4)
┌─────┬──────┬───────┬──────┐
│ id  ┆ blue ┆ green ┆ red  │
│ --- ┆ ---  ┆ ---   ┆ ---  │
│ str ┆ i64  ┆ i64   ┆ i64  │
╞═════╪══════╪═══════╪══════╡
│ 1   ┆ 0    ┆ 4     ┆ 0    │
│ 2   ┆ 0    ┆ 0     ┆ 0    │
└─────┴──────┴───────┴──────┘

(df.pivot('area', 'id', 'type', None)
   .filter(pl.col('id') != 'N/A')
)

shape: (2, 5)
┌─────┬──────┬──────┬────────┬───────┐
│ id  ┆ red  ┆ blue ┆ yellow ┆ green │
│ --- ┆ ---  ┆ ---  ┆ ---    ┆ ---   │
│ str ┆ i64  ┆ i64  ┆ i64    ┆ i64   │
╞═════╪══════╪══════╪════════╪═══════╡
│ 1   ┆ null ┆ null ┆ 3      ┆ 4     │
│ 2   ┆ null ┆ null ┆ 5      ┆ null  │
└─────┴──────┴──────┴────────┴───────┘