I was very reluctant about the polars syntax as well initally, but it has grown a lot on me.
Pandas syntax is super ergonomic for quick one-off analysis, but it becomes hard to read/maintain once your processing gets more complex.
For example, the innocent
df[arg]
can mean wildly different things - does it filter rows? Subset columns? Extract a single column as a pd.Series? There really is no way of knowing except for checking the value of arg.
In contrast, polars syntax feals clunky initially, but it's much easier for me to revisit a pipeline and quickly understand what it does.
Pandas syntax is super ergonomic for quick one-off analysis, but it becomes hard to read/maintain once your processing gets more complex.
For example, the innocent
can mean wildly different things - does it filter rows? Subset columns? Extract a single column as a pd.Series? There really is no way of knowing except for checking the value of arg.In contrast, polars syntax feals clunky initially, but it's much easier for me to revisit a pipeline and quickly understand what it does.