Add index feature

[GloriaWYY]

PR #30

Due to difference in the functions used in Python and R, I need to modify several index names. e.g. tidymodels has to be changed to scikit-learn. And there are some cases when there is no one-to-one match for functions, so some index entries are combined into a single entry.

Below, I will document the index entries that I have changed for easier tracking:

classification1

• glimpse -> info
• DELETE: \index{factor!as_factor}, \index{levels}\index{factor!levels}
• group_by -> groupby, summarize -> count
• mutate -> assign
• \index{tidymodels}\index{parsnip} -> scikit-learn
• tidymodels!model specification -> scikit-learn; model instance
• tidymodels!engine -> scikit-learn; KNeighborsClassifier
• tidymodels!model formula -> scikit-learn; X & y
• tidymodels!predict -> scikit-learn; predict
• recipe -> pipeline
• recipe!step_scale, recipe!step_center -> scikit-learn; StandardScaler
• ADD: scikit-learn; ColumnTransformer
• tidymodels!prep -> scikit-learn; fit
• tidymodels!bake -> scikit-learn; transform
• DELETE: \index{recipe!all_predictors}
• recipe!step_upsample -> scikit-learn; resample
• DELETE: tidymodels!add_recipe, tidymodels!add_model

classification 2

• \index{seed!set.seed} -> seed; numpy.random.seed
• \index{sample!function} -> sample; numpy.random.choice
• tidymodels -> scikit-learn
• \index{tidymodels!initial_split} -> scikit-learn; train_test_split
• glimpse -> info
• \index{tidymodels!vfold_cv}\index{cross-validation!vfold_cv} -> cross-validation; cross_validate, scikit-learn; cross_validate
• DELETE tidymodels!fit_resamples
• DELETE \index{tidymodels!collect_metrics}\index{cross-validation!collect_metrics}

regression 1

• DELETE \index{seed!set.seed}
• \index{ggplot!geom_point} -> altair; mark_circle
• \index{slice_sample} -> pandas.DataFrame; sample
• \index{mutate}\index{slice}\index{arrange}\index{abs} -> pandas.DataFrame; assign, head, pandas.DataFrame; sort_values, abs
• \index{tidymodels}\index{recipe}\index{workflow} -> scikit-learn, scikit-learn; pipeline, scikit-learn; make_pipeline, scikit-learn; make_column_transformer
• DELETE \index{cross-validation!collect_metrics} -> ADD scikit-learn; GridSearchCV

regression 2

• tidymodels -> scikit-learn
• \index{seed!set.seed} -> scikit-learn; random_state
• \index{regression!multivariable linear}\index{regression!multivariable linear equation|see{plane equation}} ->
  regression; multivariable linear, regression; multivariable linear equation
  see: multivariable linear equation; plane equation

inference

• DELETE \index{seed!set.seed}
• \index{pull}\index{sum}\index{nrow} -> pandas.DataFrame; df[], count, len
• \index{rep_sample_n} -> pandas.DataFrame; sample
• DELETE \index{infer}
• DELETE \index{rep_sample_n!reps argument}\index{rep_sample_n!size argument}
• \index{bootstrap!in R}\index{rep_sample_n!bootstrap} -> bootstrap; in Python, scikit-learn; resample (bootstrap)
• \index{quantile} -> numpy; percentile
• \index{pull}\index{select} -> pandas.DataFrame; df[]

wrangling

• ADD pandas; data frame,
• DELETE \index{vector}\index{atomic vector|see{vector}}\index{c function}
  \index{data types}\index{character}\index{chr|see{character}}\index{integer}\index{int|see{integer}}\index{double}\index{dbl|see{double}}\index{logical}\index{lgl|see{logical}}\index{factor}\index{fct|see{factor}} -> data types, string, integer, floating point number, boolean, list, set, dictionary, tuple, none
• class -> type
• DELETE \index{tibble}
• \index{pivot_longer} -> pandas.DataFrame; melt
• \index{pivot_wider} -> pandas.DataFrame; pivot
• \index{separate} -> pandas.Series; str.split
• DELETE \index{select!helpers}
• \index{select!starts_with} -> pandas.Series; str.startswith
• \index{select!contains} -> pandas.Series; str.contains
• \index{mutate} -> pandas.DataFrame; df[]
• DELETE \index{pipe}\index{aaapipesymb@\vert{}>|see{pipe}}
• ADD chaining methods
• \index{NA|see{missing data}} -> see: NaN; missing data
• \index{group_by} -> pandas.DataFrame; groupby
• DELETE \index{across} \index{map} \index{map!map_* functions}
• ADD pandas.DataFrame; apply
• DELETE \index{rowwise}

intro

• \index{library} -> import
• \index{tidyverse} -> pandas
• \index{filter}\index{select} -> pandas.DataFrame; df[], pandas.DataFrame; loc[]
• \index{arrange}\index{slice} -> pandas.DataFrame; sort_values, pandas.DataFrame; iloc[]
• \index{ggplot} -> altair
• \index{aaaplussymb@$+$|see{ggplot (add layer)}} -> see: .; chaining methods
• \index{plot!layers} -> plot; labels
• \index{reorder} -> altair; sort
• \index{aaaquestionmark@?|see{documentation}}\index{help|see{documentation}}\index{documentation} ->
  documentation
  see: help; documentation
  see: doc; documentation
• tidyverse -> pandas
• \index{warning} -> Error
• \index{read function!skip argument} -> read function; skiprows argument
• \index{read function!delim argument} -> read function; sep argument
• \index{rename} -> pandas.DataFrame; rename
• \index{read function!col_names argument} -> read function; names argument
• DELETE \index{readxl}
• Add SQLAlchemy, SQLAlchemy; create_engine, database; SQLAlchemy
• \index{database!tbl} -> database; select, SQLAlchemy; select
• \index{database!collect} -> database; fetchall, SQLAlchemy; fetchall
• \index{database!show_query} -> database; show query, SQLAlchemy; query.compile
• filter -> database; filter data, SQLAlchemy; where
• \index{nrow} -> pandas.DataFrame; shape
• \index{tail} -> pandas.DataFrame; tail
• \index{write function!write_csv} -> write function; to_csv, pandas.DataFrame; to_csv

clustering

• \index{seed!set.seed} -> seed; numpy.random.seed
• DELETE \index{mutate}
• \index{ggplot}\index{ggplot!geom_point} -> altair; altair, mark_circle
• ADD scikit-learn; KMeans
• DELETE \index{broom}\index{broom}\index{augment}
• ADD K-means; inertia_, K-means; cluster_centers_, K-means; labels_, K-means; predict
• \index{K-means!restart, nstart} -> K-means; init argument
  \index{WSSD!total} -> WSSD; total, K-means; inertia_
  see: WSSD; K-means inertia
• mutate -> pandas.DataFrame; assign
• DELETE \index{rowwise}\index{glance}
• ADD pandas.DataFrame; iloc[]

viz

• ggplot -> altair
• \index{ggplot!aesthetic mapping}\index{ggplot!geometric object} -> altair; geometric object, altair; geometric encoding, geometric object, geometric encoding
• DELETE \index{ggplot!aes}\index{ggplot!geom_point}
• \index{ggplot!geom_line} -> altair; mark_line
• \index{ggplot!xlab,ylab}\index{ggplot!theme} -> altair; alt.X, altair; alt.Y, altair; configure_axis
• \index{ggplot!scales} -> altair; alt.Scale
• \index{ggplot!geom_point} -> altair; mark_circle
• filter -> pandas.DataFrame; loc[]
• \index{ggplot!logarithmic scaling} -> altair; logarithmic scaling
• \index{mutate}\index{select} -> pandas.DataFrame; assign, pandas.DataFrame; [[]]
• DELETE \index{color palette}
• \index{ggplot!reorder} -> altair; sort
• \index{ggplot!geom_vline} -> altair; mark_rule
• \index{factor}\index{factor!usage in ggplot} -> nominal, altair; :N
• \index{ggplot!facet_grid} -> altair; facet
• \index{ggplot!add layer} -> altair; +

[GloriaWYY]

Changes in citations

classification 1

• [@parsnip][@recipes] -> {cite:p}scikit-learn

classification 2

• [@wickham2016r] -> {cite:p}mckinney2012python

regression 2

• Need to replace Modern Dive [@moderndive]; see issue regression2 #20

wrangling

• DELETE [@dplyr] [@tidyselect] [@wickham2016r]
• ADD {cite:p}mckinney2012python

intro

• [@tidyverse; @wickham2019tidverse] -> {cite:p}reback2020pandas,mckinney-proc-scipy-2010
• [@tidyversestyleguide] -> {cite:p}pep8-style-guide

reading

• The content from this section on is not edited (still in R version), since Trevor said the instructor team will decide whether these will be kept or not in later stages.
• [@wickham2016r] -> {cite:p}mckinney2012python
• DELETE [readr documentation] [@here] [readxl documentation][@rio]
• ADD pandas documentation

viz

• [@ggplot] -> {cite:p}altair
• DELETE [@wickham2016r]
• ADD {cite:p}mckinney2012python

[trevorcampbell]

This issue is done in PR #30 -- but I'll leave it open for now as a checklist for when we review/edit in detail.