Polars Backend Tests for `pytimetk` v0.2.0

[mdancho84]

Need help with someone to convert the docstring examples into pytests. The backends that @JustinKurland and the team are working on are listed here: https://github.com/business-science/pytimetk/issues/77#issuecomment-1763539878

[JustinKurland]

Adding this as a running checklist for tracking what pytests have been completed and by whom. @samuelmacedo83

Polars Backend Function Pytests

Wrangling Pandas Time Series DataFrames

• [x] summarize_by_time
• [ ] apply_by_time
• [ ] pad_by_time
• [ ] future_frame

Anomaly Detection

• [ ] anomalize

Adding Features to Time Series DataFrames (Augmenting)

• [x] augment_timeseries_signature
• [ ] augment_holiday_signature
• [x] augment_lags
• [x] augment_leads
• [x] augment_rolling
• [ ] augment_rolling_apply
• [x] augment_expanding
• [ ] augment_expanding_apply

TS Features

• [ ] ts_features
• [ ] ts_summary

Finance Module

• [ ] augment_ewn

Time Series for Pandas Series

• [ ] make_future_timeseries
• [x] make_weekday_sequence
• [x] make_weekend_sequence
• [x] get_date_summary
• [x] get_frequency_summary @samuelmacedo83
• [ ] get_diff_summary
• [ ] get_frequency
• [ ] get_seasonal_frequency
• [ ] get_trend_frequency
• [x] get_timeseries_signature
• [ ] get_holiday_signature

Date Utilities

• [x] floor_date
• [ ] ceil_date
• [x] is_holiday
• [x] week_of_month
• [x] time_series_unit_frequency_table
• [x] time_scale_template

Extra Pandas Helpers

• [x] glimpse
• [ ] parallel_apply
• [ ] progress_apply
• [ ] flatten_multiindex_column_names

13 Datasets

• [x] get_available_datasets
• [x] load_dataset