Doris Lee

The initialization should be set as a dictionary for both series and frame. The `recommendation` property is meant to be a key-value dictionary where the keys are the names of...

Hi @willeppy, Thanks for raising this issue! I have definitely noticed that the JSON serialization time is a huge bottleneck when I was profiling the code in the past. This...

Yeah I think we would have to measure the exact memory footprint and expected performance improvement by implementing the caching. Labelling this as an Epic so that we can revisit...

Hey @exactlyallan, Thanks for the suggestions! We're open to contributions and areas of improvement with a cuDF backend. This would likely involve extending a new plotting backend for Lux that...


Adding support for complementary filter operations in commit [5d2e2c](https://github.com/lux-org/lux/commit/5d2e2c42ef1f91bda1561cfca57a15dacd5e47d9). Example:  Remaining TODO: auto-binned range for equality case (e.g., MilesPerGal=15).

Thanks @jinimukh!! Can we file a follow-up issue to delegate boxplot calculations to the Pandas and SQL Executor? This will help with performance by bringing down the rendering speed from...

I'm wondering if ordinal data types have to be a subset of nominal data? Apart from the documentation and within the actions logic (`enhance` and `univariate`), is there anything in...

Here's some examples that I was playing around with: ```python df = pd.read_csv("https://raw.githubusercontent.com/lux-org/lux-datasets/master/data/aug_test.csv") df =df.dropna(subset=['education_level',"company_size"]) df.set_data_type({'education_level': "ordinal"}, order={'education_level': ['Primary School', 'High School', 'Masters','Graduate', 'Phd']}) df["education_level"] df.set_data_type({'company_size': "ordinal"}, order={'company_size': [ '

Hi @Tobolder, Thanks for your suggestions on exporting to PDF! As you mentioned the current approach is to right-click and save on individual plots. For exporting the PDF for the...