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      ]
    },
    {
      "page": "cache_write",
      "title": "Cache Save and Load (Write and Read)",
      "concept": [
        "Cache"
      ],
      "topics": [
        "cache_clear",
        "cache_exists",
        "cache_pipe",
        "cache_read",
        "cache_write"
      ]
    },
    {
      "page": "cal_split",
      "title": "Split ICS File",
      "concept": [
        "Tools"
      ],
      "topics": [
        "cal_split"
      ]
    },
    {
      "page": "categ_reducer",
      "title": "Reduce categorical values",
      "concept": [
        "Data Wrangling"
      ],
      "topics": [
        "categ_reducer"
      ]
    },
    {
      "page": "checks",
      "title": "Validate inputs (attributions, options, ...)",
      "concept": [
        "Checks"
      ],
      "topics": [
        "are_binary",
        "are_constant",
        "are_id",
        "check_attr",
        "check_opts",
        "is_even",
        "is_ip",
        "is_odd",
        "is_url"
      ]
    },
    {
      "page": "chr2num",
      "title": "Check character values for date/numeric/logical and change datatype",
      "concept": [
        "Tools"
      ],
      "topics": [
        "chr2date",
        "chr2logical",
        "chr2num"
      ]
    },
    {
      "page": "ci_lower",
      "title": "Lower/Upper Confidence Intervals",
      "concept": [
        "Confidence"
      ],
      "topics": [
        "ci_lower",
        "ci_upper"
      ]
    },
    {
      "page": "ci_var",
      "title": "Confidence Intervals on Dataframe",
      "concept": [
        "Confidence"
      ],
      "topics": [
        "ci_var"
      ]
    },
    {
      "page": "clean_text",
      "title": "Clean text strings automatically",
      "concept": [
        "Data Wrangling",
        "Text Mining"
      ],
      "topics": [
        "cleanNames",
        "cleanText"
      ]
    },
    {
      "page": "clusterKmeans",
      "title": "Automated K-Means Clustering + PCA/t-SNE",
      "concept": [
        "Clusters"
      ],
      "topics": [
        "clusterKmeans"
      ]
    },
    {
      "page": "clusterOptimalK",
      "title": "Visualize K-Means Clusters for Several K Methods",
      "concept": [
        "Clusters"
      ],
      "topics": [
        "clusterOptimalK"
      ]
    },
    {
      "page": "clusterVisualK",
      "title": "Visualize K-Means Clusters for Several K",
      "concept": [
        "Clusters"
      ],
      "topics": [
        "clusterVisualK"
      ]
    },
    {
      "page": "conf_mat",
      "title": "Confussion Matrix",
      "concept": [
        "Machine Learning",
        "Model metrics"
      ],
      "topics": [
        "conf_mat"
      ]
    },
    {
      "page": "corr",
      "title": "Correlation table",
      "concept": [
        "Calculus",
        "Correlations"
      ],
      "topics": [
        "corr"
      ]
    },
    {
      "page": "corr_cross",
      "title": "Ranked cross-correlation across all variables",
      "concept": [
        "Calculus",
        "Correlations"
      ],
      "topics": [
        "corr_cross"
      ]
    },
    {
      "page": "corr_var",
      "title": "Correlation between variable and dataframe",
      "concept": [
        "Correlations",
        "Exploratory"
      ],
      "topics": [
        "corr_var",
        "plot.corr_var"
      ]
    },
    {
      "page": "cran_logs",
      "title": "Download and plot daily downloads of CRAN packages",
      "topics": [
        "cran_logs"
      ]
    },
    {
      "page": "crosstab",
      "title": "Weighted Cross Tabulation",
      "concept": [
        "Exploratory"
      ],
      "topics": [
        "crosstab"
      ]
    },
    {
      "page": "dalex_local",
      "title": "DALEX Local",
      "concept": [
        "Interpretability"
      ],
      "topics": [
        "dalex_local"
      ]
    },
    {
      "page": "dalex_residuals",
      "title": "DALEX Residuals",
      "concept": [
        "Interpretability"
      ],
      "topics": [
        "dalex_residuals"
      ]
    },
    {
      "page": "dalex_variable",
      "title": "DALEX Partial Dependency Plots (PDP)",
      "concept": [
        "Interpretability"
      ],
      "topics": [
        "dalex_variable"
      ]
    },
    {
      "page": "date_cuts",
      "title": "Convert Date into Year + Cut",
      "concept": [
        "Data Wrangling"
      ],
      "topics": [
        "date_cuts"
      ]
    },
    {
      "page": "date_feats",
      "title": "One Hot Encoding for Date/Time Variables (Dummy Variables)",
      "concept": [
        "Data Wrangling",
        "Feature Engineering",
        "One Hot Encoding"
      ],
      "topics": [
        "date_feats"
      ]
    },
    {
      "page": "db_download",
      "title": "Download/Import Dropbox File by File's Name",
      "concept": [
        "Credentials",
        "Dropbox",
        "Tools"
      ],
      "topics": [
        "db_download"
      ]
    },
    {
      "page": "db_upload",
      "title": "Upload Local Files to Dropbox",
      "concept": [
        "Credentials",
        "Dropbox",
        "Tools"
      ],
      "topics": [
        "db_upload"
      ]
    },
    {
      "page": "df_str",
      "title": "Dataset columns and rows structure",
      "concept": [
        "Exploratory"
      ],
      "topics": [
        "df_str"
      ]
    },
    {
      "page": "dfr",
      "title": "Results for AutoML Predictions",
      "concept": [
        "Dataset"
      ],
      "topics": [
        "dfr"
      ]
    },
    {
      "page": "dft",
      "title": "Titanic Dataset",
      "concept": [
        "Dataset"
      ],
      "topics": [
        "dft"
      ]
    },
    {
      "page": "dist2d",
      "title": "Distance from specific point to line",
      "concept": [
        "Calculus"
      ],
      "topics": [
        "dist2d"
      ]
    },
    {
      "page": "distr",
      "title": "Compare Variables with their Distributions",
      "concept": [
        "Exploratory",
        "Visualization"
      ],
      "topics": [
        "distr"
      ]
    },
    {
      "page": "dont_sleep",
      "title": "Prevent Computer from Sleeping by Simulating Mouse Activity",
      "concept": [
        "Tools"
      ],
      "topics": [
        "dont_sleep",
        "dont_sleep_time"
      ]
    },
    {
      "page": "encrypt_file",
      "title": "File Encryption and Decryption (AES-256-CBC)",
      "concept": [
        "Credentials"
      ],
      "topics": [
        "encrypt_file",
        "hex_to_raw",
        "raw_to_hex",
        "read_encrypted",
        "write_encrypted"
      ]
    },
    {
      "page": "errors",
      "title": "Calculate Continuous Values Errors",
      "concept": [
        "Model metrics"
      ],
      "topics": [
        "errors",
        "mae",
        "mape",
        "mse",
        "rmse",
        "rsq",
        "rsqa"
      ]
    },
    {
      "page": "etf_sector",
      "title": "ETF's Sectors Breakdown",
      "concept": [
        "Investment"
      ],
      "topics": [
        "etf_sector"
      ]
    },
    {
      "page": "export_plot",
      "title": "Export ggplot2, gridExtra, or any plot object into rendered file",
      "concept": [
        "Tools"
      ],
      "topics": [
        "export_plot"
      ]
    },
    {
      "page": "export_results",
      "title": "Export h2o_automl's Results",
      "concept": [
        "Machine Learning",
        "Tools"
      ],
      "topics": [
        "export_results"
      ]
    },
    {
      "page": "fb_accounts",
      "title": "Facebook Ad Accounts",
      "concept": [
        "API",
        "Meta"
      ],
      "topics": [
        "fb_accounts"
      ]
    },
    {
      "page": "fb_ads",
      "title": "Facebook Ads API",
      "concept": [
        "API",
        "Meta"
      ],
      "topics": [
        "fb_ads"
      ]
    },
    {
      "page": "fb_creatives",
      "title": "Facebook Creatives API",
      "concept": [
        "API",
        "Meta"
      ],
      "topics": [
        "fb_creatives"
      ]
    },
    {
      "page": "fb_insights",
      "title": "Facebook Insights API",
      "concept": [
        "API",
        "Meta"
      ],
      "topics": [
        "fb_insights"
      ]
    },
    {
      "page": "fb_process",
      "title": "Paginate and Process Facebook's API Results",
      "concept": [
        "API",
        "Meta"
      ],
      "topics": [
        "fb_process"
      ]
    },
    {
      "page": "fb_report_check",
      "title": "Facebook API Report Status Check",
      "concept": [
        "API",
        "Meta"
      ],
      "topics": [
        "fb_report_check"
      ]
    },
    {
      "page": "fb_rf",
      "title": "Facebook Reach and Frequency API",
      "concept": [
        "API",
        "Meta"
      ],
      "topics": [
        "fb_rf"
      ]
    },
    {
      "page": "fb_token",
      "title": "Facebook's Long-Life User API Token",
      "concept": [
        "API",
        "Meta"
      ],
      "topics": [
        "fb_token"
      ]
    },
    {
      "page": "file_name",
      "title": "Extract file raw name and type from file names",
      "concept": [
        "Data Wrangling"
      ],
      "topics": [
        "file_name",
        "file_type"
      ]
    },
    {
      "page": "files_functions",
      "title": "List all functions used in R script files by package",
      "concept": [
        "Tools"
      ],
      "topics": [
        "files_functions"
      ]
    },
    {
      "page": "filesGD",
      "title": "Google Drive Files (API v4)",
      "concept": [
        "Google",
        "Scrapper"
      ],
      "topics": [
        "filesGD"
      ]
    },
    {
      "page": "font_exists",
      "title": "Check if Font is Installed",
      "concept": [
        "Tools"
      ],
      "topics": [
        "font_exists"
      ]
    },
    {
      "page": "forecast_arima",
      "title": "ARIMA Forecast",
      "concept": [
        "Forecast"
      ],
      "topics": [
        "forecast_arima"
      ]
    },
    {
      "page": "formatColoured",
      "title": "Print Coloured Messages",
      "concept": [
        "Tools"
      ],
      "topics": [
        "formatColoured"
      ]
    },
    {
      "page": "format_string",
      "title": "Format a string text as markdown/HTML",
      "concept": [
        "Data Wrangling",
        "Tools"
      ],
      "topics": [
        "formatHTML",
        "formatNum"
      ]
    },
    {
      "page": "freqs",
      "title": "Frequencies Calculations and Plot",
      "concept": [
        "Exploratory",
        "Frequency",
        "Visualization"
      ],
      "topics": [
        "freqs"
      ]
    },
    {
      "page": "freqs_df",
      "title": "Plot for All Frequencies on Dataframe",
      "concept": [
        "Exploratory",
        "Frequency",
        "Visualization"
      ],
      "topics": [
        "freqs_df"
      ]
    },
    {
      "page": "freqs_list",
      "title": "Frequencies on Lists and UpSet Plot",
      "concept": [
        "Exploratory",
        "Frequency",
        "Visualization"
      ],
      "topics": [
        "freqs_list"
      ]
    },
    {
      "page": "freqs_plot",
      "title": "Combined Frequencies Plot for Categorical Features",
      "concept": [
        "Exploratory",
        "Frequency",
        "Visualization"
      ],
      "topics": [
        "freqs_plot"
      ]
    },
    {
      "page": "gain_lift",
      "title": "Cumulative Gain, Lift and Response",
      "concept": [
        "Machine Learning",
        "Model metrics"
      ],
      "topics": [
        "gain_lift"
      ]
    },
    {
      "page": "gemini_ask",
      "title": "Gemini API Interaction with R",
      "concept": [
        "API",
        "Gemini",
        "LLM"
      ],
      "topics": [
        "gemini_ask",
        "gemini_image"
      ]
    },
    {
      "page": "get_credentials",
      "title": "Load Credentials from a YML File",
      "concept": [
        "Credentials"
      ],
      "topics": [
        "get_credentials",
        "get_creds"
      ]
    },
    {
      "page": "get_currency",
      "title": "Download Historical Currency Exchange Rate",
      "concept": [
        "Currency"
      ],
      "topics": [
        "get_currency"
      ]
    },
    {
      "page": "get_tweets",
      "title": "Get Tweets",
      "concept": [
        "Credentials",
        "Twitter"
      ],
      "topics": [
        "get_tweets"
      ]
    },
    {
      "page": "gg_fill_customs",
      "title": "Custom fill, colour and text colours for ggplot2",
      "concept": [
        "Themes"
      ],
      "topics": [
        "gg_colour_customs",
        "gg_fill_customs",
        "gg_text_customs",
        "gg_vals"
      ]
    },
    {
      "page": "glued",
      "title": "Interpolate a string [glue wrapper]",
      "concept": [
        "Tools"
      ],
      "topics": [
        "glued"
      ]
    },
    {
      "page": "gpt_ask",
      "title": "ChatGPT API Interaction with R",
      "concept": [
        "API",
        "ChatGPT",
        "LLM"
      ],
      "topics": [
        "gpt_ask",
        "gpt_classify",
        "gpt_convert",
        "gpt_extract",
        "gpt_format",
        "gpt_history",
        "gpt_table",
        "gpt_tag",
        "gpt_translate"
      ]
    },
    {
      "page": "gpt_prompter",
      "title": "Structured Prompt Builder for LLM (ChatGPT)",
      "concept": [
        "ChatGPT",
        "LLM"
      ],
      "topics": [
        "gpt_prompter"
      ]
    },
    {
      "page": "grepl_letters",
      "title": "Pattern Matching for Letters considering Blanks",
      "topics": [
        "grepl_letters"
      ]
    },
    {
      "page": "grepm",
      "title": "Pattern Matching for Any or All Multiple Matches",
      "concept": [
        "Tools"
      ],
      "topics": [
        "grepm"
      ]
    },
    {
      "page": "google_trends",
      "title": "Google Trends: Related and Time Plots",
      "concept": [
        "Google",
        "Scrapper"
      ],
      "topics": [
        "gtrends_related",
        "gtrends_time",
        "trendsRelated",
        "trendsTime"
      ]
    },
    {
      "page": "h2o_automl",
      "title": "Automated H2O's AutoML",
      "concept": [
        "Machine Learning"
      ],
      "topics": [
        "h2o_automl",
        "plot.h2o_automl",
        "print.h2o_automl"
      ]
    },
    {
      "page": "h2o_explainer",
      "title": "DALEX Explainer for H2O",
      "concept": [
        "Interpretability"
      ],
      "topics": [
        "dalex_explainer",
        "h2o_explainer"
      ]
    },
    {
      "page": "h2o_predict",
      "title": "Calculate predictions of h2o Models",
      "concept": [
        "H2O",
        "Machine Learning"
      ],
      "topics": [
        "h2o_predict_API",
        "h2o_predict_binary",
        "h2o_predict_model",
        "h2o_predict_MOJO"
      ]
    },
    {
      "page": "h2o_results",
      "title": "Automated H2O's AutoML Results",
      "topics": [
        "h2o_results"
      ]
    },
    {
      "page": "h2o_selectmodel",
      "title": "Select Model from h2o_automl's Leaderboard",
      "concept": [
        "Machine Learning",
        "Tools"
      ],
      "topics": [
        "h2o_selectmodel"
      ]
    },
    {
      "page": "h2o_shap",
      "title": "SHAP values for H2O Models",
      "concept": [
        "SHAP"
      ],
      "topics": [
        "h2o_shap",
        "plot.h2o_shap"
      ]
    },
    {
      "page": "haveInternet",
      "title": "Internet Connection Check",
      "concept": [
        "Tools"
      ],
      "topics": [
        "haveInternet"
      ]
    },
    {
      "page": "holidays",
      "title": "Holidays in your Country",
      "concept": [
        "Data Wrangling",
        "Feature Engineering",
        "One Hot Encoding",
        "Scrapper"
      ],
      "topics": [
        "holidays"
      ]
    },
    {
      "page": "image_metadata",
      "title": "Get Meta Data from Image Files",
      "concept": [
        "Tools"
      ],
      "topics": [
        "image_metadata"
      ]
    },
    {
      "page": "importxlsx",
      "title": "Import Excel File with All Its Tabs",
      "concept": [
        "Tools"
      ],
      "topics": [
        "importxlsx"
      ]
    },
    {
      "page": "impute",
      "title": "Impute Missing Values (using MICE)",
      "concept": [
        "Data Wrangling",
        "Machine Learning",
        "Missing Values"
      ],
      "topics": [
        "impute"
      ]
    },
    {
      "page": "install_recommended",
      "title": "Install/Update Additional Recommended Libraries",
      "topics": [
        "install_recommended"
      ]
    },
    {
      "page": "ip_data",
      "title": "Scrap data based on IP address",
      "concept": [
        "Scrapper",
        "Tools"
      ],
      "topics": [
        "ip_data"
      ]
    },
    {
      "page": "iter_seeds",
      "title": "Iterate Seeds on AutoML",
      "concept": [
        "Machine Learning"
      ],
      "topics": [
        "iter_seeds"
      ]
    },
    {
      "page": "json2vector",
      "title": "Convert Python JSON string to R vector (data.frame with 1 row)",
      "concept": [
        "Tools"
      ],
      "topics": [
        "json2vector"
      ]
    },
    {
      "page": "lares",
      "title": "Lean Analytics and Robust Exploration Sidekick",
      "topics": [
        "lares-package",
        "lares"
      ]
    },
    {
      "page": "lares_logo",
      "title": "Print lares R library Logo",
      "topics": [
        "lares_logo"
      ]
    },
    {
      "page": "lares_pal",
      "title": "Personal Colours Palette",
      "concept": [
        "Themes"
      ],
      "topics": [
        "lares_pal"
      ]
    },
    {
      "page": "lares-exports",
      "title": "Pipe operator",
      "topics": [
        "%>%",
        "lares-exports"
      ]
    },
    {
      "page": "lasso_vars",
      "title": "Most Relevant Features Using Lasso Regression",
      "concept": [
        "Exploratory",
        "Machine Learning"
      ],
      "topics": [
        "lasso_vars"
      ]
    },
    {
      "page": "left_right",
      "title": "Left or Right N characters of a string",
      "concept": [
        "Data Wrangling"
      ],
      "topics": [
        "left",
        "right"
      ]
    },
    {
      "page": "list_cats",
      "title": "List categorical values for data.frame",
      "concept": [
        "Tools"
      ],
      "topics": [
        "list_cats"
      ]
    },
    {
      "page": "listfiles",
      "title": "List files in a directory",
      "concept": [
        "Tools"
      ],
      "topics": [
        "listfiles"
      ]
    },
    {
      "page": "loglossBinary",
      "title": "Logarithmic Loss Function for Binary Models",
      "concept": [
        "Model metrics"
      ],
      "topics": [
        "loglossBinary"
      ]
    },
    {
      "page": "mail_send",
      "title": "Send Emails with Attachments (POST)",
      "concept": [
        "Credentials",
        "Tools"
      ],
      "topics": [
        "mail_send"
      ]
    },
    {
      "page": "markdown2df",
      "title": "Convert markdown string tables to data.frame",
      "concept": [
        "Tools"
      ],
      "topics": [
        "markdown2df"
      ]
    },
    {
      "page": "maze_solve",
      "title": "Maze Solver, inspired by Micromouse competitions",
      "concept": [
        "Games"
      ],
      "topics": [
        "maze_gridsearch",
        "maze_solve",
        "print.maze_solve"
      ]
    },
    {
      "page": "missingness",
      "title": "Calculate and Visualize Missingness",
      "concept": [
        "Exploratory",
        "Missing Values"
      ],
      "topics": [
        "missingness"
      ]
    },
    {
      "page": "model_metrics",
      "title": "Model Metrics and Performance",
      "concept": [
        "Calculus",
        "Machine Learning",
        "Model metrics"
      ],
      "topics": [
        "model_metrics"
      ]
    },
    {
      "page": "model_preprocess",
      "title": "Automate Data Preprocess for Modeling",
      "concept": [
        "Machine Learning"
      ],
      "topics": [
        "model_preprocess"
      ]
    },
    {
      "page": "move_files",
      "title": "Move files from A to B",
      "concept": [
        "Tools"
      ],
      "topics": [
        "move_files"
      ]
    },
    {
      "page": "mp3_get",
      "title": "Download MP3 from URL",
      "concept": [
        "Audio",
        "Scrapper"
      ],
      "topics": [
        "mp3_get"
      ]
    },
    {
      "page": "mp3_trim",
      "title": "Trim MP3 Audio File",
      "concept": [
        "Audio"
      ],
      "topics": [
        "mp3_trim"
      ]
    },
    {
      "page": "mp3_update_tags",
      "title": "Update MP3 Metadata Tags",
      "concept": [
        "Audio"
      ],
      "topics": [
        "mp3_update_tags"
      ]
    },
    {
      "page": "mplot_conf",
      "title": "Confussion Matrix Plot",
      "concept": [
        "ML Visualization"
      ],
      "topics": [
        "mplot_conf"
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    },
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      "page": "mplot_cuts",
      "title": "Cuts by quantiles for score plot",
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        "ML Visualization"
      ],
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        "mplot_cuts"
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    },
    {
      "page": "mplot_cuts_error",
      "title": "Cuts by quantiles on absolute and percentual errors plot",
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        "ML Visualization"
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    {
      "page": "mplot_density",
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      ],
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        "mplot_density"
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    },
    {
      "page": "mplot_full",
      "title": "MPLOTS Score Full Report Plots",
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        "ML Visualization"
      ],
      "topics": [
        "mplot_full"
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    },
    {
      "page": "mplot_gain",
      "title": "Cumulative Gain Plot",
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        "ML Visualization"
      ],
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        "mplot_gain"
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    },
    {
      "page": "mplot_importance",
      "title": "Variables Importances Plot",
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      ],
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        "mplot_importance"
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    },
    {
      "page": "mplot_lineal",
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    {
      "page": "mplot_metrics",
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        "mplot_metrics"
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    },
    {
      "page": "mplot_response",
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      ],
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        "mplot_response"
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    },
    {
      "page": "mplot_roc",
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        "mplot_roc"
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    {
      "page": "mplot_splits",
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      ],
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        "mplot_splits"
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    },
    {
      "page": "mplot_topcats",
      "title": "Top Hit Ratios for Multi-Classification Models",
      "concept": [
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      ],
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        "mplot_topcats"
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    {
      "page": "msplit",
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        "Tools"
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        "msplit"
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      "page": "myip",
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      ],
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        "myip"
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    {
      "page": "ngrams",
      "title": "Build N-grams and keep most frequent",
      "concept": [
        "Text Mining"
      ],
      "topics": [
        "ngrams"
      ]
    },
    {
      "page": "noPlot",
      "title": "Plot Result with Nothing to Plot",
      "concept": [
        "Visualization"
      ],
      "topics": [
        "noPlot"
      ]
    },
    {
      "page": "normalize",
      "title": "Normalize Vector",
      "concept": [
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      ],
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        "normalize"
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    },
    {
      "page": "num_abbr",
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        "Data Wrangling"
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      "topics": [
        "num_abbr"
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    },
    {
      "page": "ohe_commas",
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        "One Hot Encoding"
      ],
      "topics": [
        "ohe_commas"
      ]
    },
    {
      "page": "ohse",
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        "Feature Engineering",
        "One Hot Encoding"
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      "topics": [
        "ohse"
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    },
    {
      "page": "outlier_tukey",
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        "Outliers"
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        "outlier_tukey",
        "outlier_turkey"
      ]
    },
    {
      "page": "outlier_zscore",
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        "Outliers"
      ],
      "topics": [
        "outlier_zscore"
      ]
    },
    {
      "page": "outlier_zscore_plot",
      "title": "Outliers: Z-score method plot",
      "concept": [
        "Outliers"
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      "topics": [
        "outlier_zscore_plot"
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    },
    {
      "page": "plot_cats",
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        "Exploratory"
      ],
      "topics": [
        "plot_cats"
      ]
    },
    {
      "page": "plot_chord",
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        "Visualization"
      ],
      "topics": [
        "plot_chord"
      ]
    },
    {
      "page": "plot_df",
      "title": "Plot Summary of Numerical and Categorical Features",
      "concept": [
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      ],
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        "plot_df"
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    },
    {
      "page": "plot_nums",
      "title": "Plot All Numerical Features (Boxplots)",
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        "plot_nums"
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    },
    {
      "page": "plot_palette",
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        "plot_palette"
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    {
      "page": "plot_survey",
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        "plot_survey"
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    },
    {
      "page": "plot_timeline",
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        "plot_timeline"
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    },
    {
      "page": "prophesize",
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        "prophesize"
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      "page": "quants",
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      "page": "queryDB",
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        "Database"
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      "page": "replacefactor",
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    },
    {
      "page": "robyn_modelselector",
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    },
    {
      "page": "robyn_crossmmm",
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    },
    {
      "page": "ROC",
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    {
      "page": "rtistry_sphere",
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      "page": "scale_x_comma",
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      "page": "sentimentBreakdown",
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    },
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      "page": "shap_var",
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      "page": "slackSend",
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        "Credentials"
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      "page": "stocks_plots",
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    },
    {
      "page": "spread_list",
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      "page": "stocks_hist",
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      "page": "sudoku_solver",
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    {
      "page": "target_set",
      "title": "Set Target Value in Target Variable",
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      ]
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      "page": "textCloud",
      "title": "Wordcloud Plot",
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      ],
      "topics": [
        "textCloud"
      ]
    },
    {
      "page": "textFeats",
      "title": "Create features out of text",
      "concept": [
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        "Text Mining"
      ],
      "topics": [
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      ]
    },
    {
      "page": "textTokenizer",
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        "Text Mining"
      ],
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        "textTokenizer"
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    {
      "page": "theme_lares",
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        "theme_lares"
      ]
    },
    {
      "page": "tic",
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        "Tools"
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        "toc"
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    },
    {
      "page": "toon_reduction",
      "title": "Calculate Character Reduction from R Object to TOON Format",
      "topics": [
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    {
      "page": "topics_rake",
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      "page": "tree_var",
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      "page": "try_require",
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      "page": "updateLares",
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      "page": "vector2text",
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        "vector2text"
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      "page": "what_size",
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      "page": "year_month",
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        "year_week"
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  "_vignettes": [
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      "source": "api-integrations.Rmd",
      "filename": "api-integrations.html",
      "title": "API Integrations",
      "author": "Bernardo Lares",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Credential Management",
        "Setup Credentials Securely",
        "ChatGPT Integration",
        "Basic Usage",
        "Structured Prompts",
        "Specialized Functions",
        "Classification",
        "Data Extraction",
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        "Google Sheets Integration",
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        "Database Queries",
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        "Search Trends Over Time",
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        "1. Secure Your Credentials",
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        "3. Rate Limiting",
        "4. Cache Results",
        "5. Monitor Costs",
        "Environment Variables",
        "Troubleshooting",
        "API Key Issues",
        "Network Issues",
        "Rate Limit Errors",
        "Complete Example: Data Analysis with AI",
        "Further Reading",
        "API Documentation",
        "Blog Posts & Tutorials",
        "Next Steps"
      ],
      "created": "2025-11-24 17:09:49",
      "modified": "2026-04-23 17:23:30",
      "commits": 4
    },
    {
      "source": "data-wrangling.Rmd",
      "filename": "data-wrangling.html",
      "title": "Data Wrangling & Visualization",
      "author": "Bernardo Lares",
      "engine": "knitr::rmarkdown",
      "headings": [
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        "Quick Start with Built-in Data",
        "Frequency Analysis",
        "Basic Frequencies",
        "Multi-variable Frequencies",
        "Visual Frequencies",
        "Dataframe-wide Frequencies",
        "Correlation Analysis",
        "Correlation Matrix",
        "Correlate One Variable with All Others",
        "Cross-Correlations",
        "Data Transformation",
        "Categorical Reduction",
        "Normalization",
        "One-Hot Encoding",
        "Date Manipulation",
        "Visualization with theme_lares",
        "Custom ggplot2 Theme",
        "Distribution Plots",
        "Number Formatting",
        "Custom Scales",
        "Text and Vector Utilities",
        "Vector to Text",
        "Putting It All Together",
        "Further Reading",
        "Package Resources",
        "Blog Posts & Tutorials",
        "Next Steps"
      ],
      "created": "2025-11-24 17:09:49",
      "modified": "2026-04-23 17:23:30",
      "commits": 4
    },
    {
      "source": "games.Rmd",
      "filename": "games.html",
      "title": "Games & Puzzles",
      "author": "Bernardo Lares",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Wordle",
        "Basic Wordle Validation",
        "Get Wordle Hints",
        "Wordle Simulation",
        "Wordle Dictionary",
        "Scrabble",
        "Find Highest-Scoring Words",
        "With Board Constraints",
        "Calculate Word Scores",
        "Multi-Language Support",
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        "Simple Sudoku",
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        "Maze Solver",
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        "Micromouse Competition Maze",
        "Advanced Options",
        "Combining Games & Data Science",
        "Further Reading",
        "Package Resources",
        "Game References",
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