Drop -Spalte für Index in Polaren ⇐ Python

[Anonymous]

Ich muss die erste Spalte in einem Polars -Datenframe fallen lassen.

Code: Select all

result = df.select([col for idx, col in enumerate(df.columns) if idx != 1])
< /code>
Es sieht lang und ungeschickt für eine so einfache Aufgabe aus? < /p>
Ich habe es auch versucht: < /p>
df.select(pl.exclude(pl.nth(1)))
< /code>
Aber das fehlte < /p>
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[20], line 1
----> 1 df.select(pl.exclude(pl.nth(1)))

File \.venv\Lib\site-packages\polars\functions\lazy.py:1855, in exclude(columns, *more_columns)
1785 def exclude(
1786     columns: str | PolarsDataType | Collection[str] | Collection[PolarsDataType],
1787     *more_columns: str | PolarsDataType,
1788 ) -> Expr:
1789     """
1790     Represent all columns except for the given columns.
1791
(...)   1853
1854     """
-> 1855     return F.col("*").exclude(columns, *more_columns)

File \.venv\Lib\site-packages\polars\expr\expr.py:851, in Expr.exclude(self, columns, *more_columns)
768 def exclude(
769     self,
770     columns: str | PolarsDataType | Collection[str] | Collection[PolarsDataType],
771     *more_columns: str | PolarsDataType,
772 ) -> Expr:
773     """
774     Exclude columns from a multi-column expression.
775
(...)    849     └──────┘
850     """
--> 851     return self.meta.as_selector().exclude(columns, *more_columns).as_expr()

File .venv\Lib\site-packages\polars\selectors.py:571, in Selector.exclude(self, columns, *more_columns)
566     else:
567         msg = (
568             "invalid input for `exclude`"
569             f"\n\nExpected one or more `str` or `DataType`; found {item!r} instead."
570         )
--> 571         raise TypeError(msg)
573 if exclude_cols and exclude_dtypes:
574     msg = "cannot exclude by both column name and dtype; use a selector instead"

TypeError: invalid input for `exclude`

Expected one or more `str` or `DataType`; found  instead.