组合Pandas DataFrame中的datetime和timezone列(tz_localize从列) 、、、 如前所述(),Pandas提供了本地化datetime列(tz_localize)和将时区(tz_convert)转换为预定义时区的方法。例如:但是,这两个函数都接受时区本身作为参数如果时区来自同一数据帧中的另一列,怎么办?是否有一种简单的方 浏览7提问于2022-04-11得...
The test failure seems to be because that to_pandas of polars requires pyarrow as well: https://docs.pola.rs/api/python/stable/reference/dataframe/api/polars.DataFrame.to_pandas.html, should we just skip the tests of polars when pyarrow is not installed, or try find a workaround? adrinjal...
Also, I don't know if this is useful information but it seems to happen with every data type in the source dataframe (int, float, datetime, etc...) Expected behavior merge operation successfully completed Installed versions ---Version info--- Polars: 1.19.0 Index type: UInt32 Platform: W...
nan_to_null=True stops converting nans to nulls after the dataframe grows to a certain size. This did not happen in polars==0.20.10 Expected behavior nan_to_null=True should behave exactly as pl.from_pandas().with_columns(cs.float().fill_nan(None)) Installed versions ---Version info...
Converting to Lance importlanceimportpandasaspdimportpyarrowaspaimportpyarrow.datasetdf=pd.DataFrame({"a": [5],"b": [10]})uri="/tmp/test.parquet"tbl=pa.Table.from_pandas(df)pa.dataset.write_dataset(tbl,uri,format='parquet')parquet=pa.dataset.dataset(uri,format='parquet')lance.write_dataset...
It means you can mix and match tools. If you start using this library with polars but find some functionality is missing such as geospatial functions you can keep the existing logic in polars and pass the dataframe to a tool such as duckdb to perform the geospatial elements of your processin...
When you want to pin to a specific version, prefer a stable release. Converting to Lance import lance import pandas as pd import pyarrow as pa import pyarrow.dataset df = pd.DataFrame({"a": [5], "b": [10]}) uri = "/tmp/test.parquet" tbl = pa.Table.from_pandas(df) pa.dataset...