Create more user friendly aliases from `col`
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评估
调研方向
该 issue 将 col(...) 和 .alias() 确定为相关的 Python 入口,示例显示 AVG(?table?.has_parking) 是不需要的输出。首先定位它们的实现和现有测试;当默认的 ?table? 被移除,同时 Area 和 Percentage of buildings with parking 等显式别名仍能正常工作时,即视为完成。
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描述
Is your feature request related to a problem or challenge? Please describe what you are trying to do.
This is a user enhancement request to make the python interface remove the default ?table? on columns.
Describe the solution you'd like
I have not yet reviewed the applicable code to offer a best solution yet. I'm adding this feature request to track.
Describe alternatives you've considered
User adds an .alias() command as below, which may be tedious.
Additional context
See the below example from @datapythonista that includes the desired use case
import datafusion
from datafusion import col, lit, functions as f
import pyarrow
# something like this would be implemented internally, so users can call `datafusion.read_*`
def _read_parquet(*args, **kwargs):
ctx = datafusion.SessionContext()
return ctx.read_parquet(*args, **kwargs)
datafusion.read_parquet = _read_parquet # creating an alias of `read_*` functions so users don't need to know about `SessionContext` when the defaults are fine
df = (datafusion.read_parquet("buildings.parquet")
.filter( # `.filter()` accepting multiple conditions (which will be an AND) instead of having to use `&` with its operator precedence problems
col("is_offplan") == False,
col("rooms") >= 2, # `.lit(2)` not being required, and Python literals working with operators
)
.aggregate(
[col("area_name_en")],
[f.mean(col("has_parking").cast(float))], # `.cast()` accepting Python types, which would be internally converted to the PyArrow equivalent
)
.select(
col("area_name_en").alias("Area"),
col("AVG(has_parking)").alias("Percentage of buildings with parking"), # removing the default `?table?` in column names, the column name was "AVG(?table?.has_parking)"
)
)
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