# User guide Short, ready-to-copy snippets, one for each task. Find your task below, or open a section in the menu. ```{toctree} :maxdepth: 2 :hidden: Getting started Data handling Avatarization parameters Augmentation, DP and pseudonymization Processors Metrics and evaluation Jobs and results Plots and reports Reuse past runs Troubleshooting ``` ## Find a snippet by task ### Start - install the client → [Install the client and check its version](getting_started.md#how-to-install-the-client-and-check-its-version) - create an API key / log in → [Create an API key](getting_started.md#how-to-create-an-api-key), [Log in to the server](getting_started.md#how-to-log-in-to-the-server) - run a first avatarization → [Launch my first avatarization](getting_started.md#how-to-launch-my-first-avatarization) - set the seed, output format or PIA context of a run → [Set the options of a run](getting_started.md#how-to-set-the-options-of-a-run) ### Prepare the data - upload a DataFrame or a file → [Add a table from a DataFrame or a file](data_handling.md#how-to-add-a-table-from-a-dataframe-or-a-file) - force the type of a column → [Change the type of a column](data_handling.md#how-to-change-the-type-of-a-column) - remove a column → [Drop a column](data_handling.md#how-to-drop-a-column) - handle a large dataset → [Handle a large dataset](data_handling.md#how-to-handle-a-large-dataset) - anonymize linked tables → [Anonymize several linked tables (multi-table)](data_handling.md#how-to-anonymize-several-linked-tables-multi-table) - anonymize time series → [Anonymize time series](data_handling.md#how-to-anonymize-time-series) ### Tune the avatarization - start from the recommended parameters → [Get the recommended parameters](parameters.md#how-to-get-the-recommended-parameters) - know when to use `set_parameters` or `update_parameters` → [`set_parameters` or `update_parameters`?](parameters.md#set_parameters-or-update_parameters) - change k or ncp → [Set k (privacy / utility trade-off)](parameters.md#how-to-set-k-privacy--utility-trade-off), [Set ncp (number of components)](parameters.md#how-to-set-ncp-number-of-components) - preserve a variable of interest better → [Give more weight to a variable](parameters.md#how-to-give-more-weight-to-a-variable) - handle categories with many modalities → [Handle categorical variables with many modalities](parameters.md#how-to-handle-categorical-variables-with-many-modalities) - keep a column out of the modelling (freeze, similarity) → {ref}`keep-a-column-out` - handle missing values → [Choose the imputation of missing values](parameters.md#how-to-choose-the-imputation-of-missing-values), [Get avatars without missing values](parameters.md#how-to-get-avatars-without-missing-values) - reproduce a run exactly → [Reproduce a run exactly](parameters.md#how-to-reproduce-a-run-exactly) ### Augment, add DP, pseudonymize - generate more rows / rebalance a class → [Augment your dataset](processing.md#how-to-augment-your-dataset), [Rebalance a minority class](processing.md#how-to-rebalance-a-minority-class) - use differential privacy → [Use differential privacy (FastDP)](processing.md#how-to-use-differential-privacy-fastdp), [Use differential privacy (OpenDP, MST)](processing.md#how-to-use-differential-privacy-opendp-mst) - replace names, emails, IDs → [Pseudonymize PII columns (Beta)](processing.md#how-to-pseudonymize-pii-columns-beta) ### Keep business rules - keep a total equal to the sum of its parts, or `A ≤ B` → [Keep a total equal to the sum of its parts](processors.md#how-to-keep-a-total-equal-to-the-sum-of-its-parts) - keep start and end dates coherent → [Keep start and end dates coherent across records](processors.md#how-to-keep-start-and-end-dates-coherent-across-records) - group rare modalities → {ref}`group-rare-modalities` - keep a discrete variable discrete → [Keep a discrete numeric variable discrete](processors.md#how-to-keep-a-discrete-numeric-variable-discrete) - write my own processor → [Write my own processor](processors.md#how-to-write-my-own-processor) ### Evaluate - define what an attacker knows → [Define the attack scenario](metrics.md#how-to-define-the-attack-scenario) - read the metrics → [Read the metrics](metrics.md#how-to-read-the-metrics) - evaluate a synthetic dataset made elsewhere → {ref}`evaluate-existing-dataset` ### Run and get results - run only some jobs → [Run all or some of the jobs](jobs.md#how-to-run-all-or-some-of-the-jobs) - follow, debug or cancel a job → [Follow a job](jobs.md#how-to-follow-a-job), [Read the error of a failed job](jobs.md#how-to-read-the-error-of-a-failed-job), [Cancel jobs](jobs.md#how-to-cancel-jobs) - get the avatars → [Get the avatars](jobs.md#how-to-get-the-avatars) - show plots / download the reports → [Render plots](reporting.md#how-to-render-plots), [Download the reports](reporting.md#how-to-download-the-reports) ### Reuse - reload a past run (also from the web app) → [Reload results from a previous run](advanced.md#how-to-reload-results-from-a-previous-run) - export or replay a YAML configuration → [Export a configuration as YAML](advanced.md#how-to-export-a-configuration-as-yaml), [Launch a job from a YAML file](advanced.md#how-to-launch-a-job-from-a-yaml-file) - continue in Python a job launched in the web app → [Continue in Python a job launched in the web app](advanced.md#how-to-continue-in-python-a-job-launched-in-the-web-app) Something does not work? See {doc}`troubleshooting`.