“cell_type”: “markdown”, “metadata”: {}, “source”: [
“# Parameter Configurations: parameter summary settings”
]
}, {
“cell_type”: “markdown”, “metadata”: {}, “source”: [ “## Global parameters” ]
“## Global parameters”
“cell_type”: “markdown”, “metadata”: {}, “source”: [ “To help users quickly manage the parameters, currently, we defined four global parameters. Global parameter applies to all the plots which has that parameter.n”, “n”, “| Global Parameter | Description |\n", "| — | — | n”, “| width | Change the plots’ width in plot(df, col1), plot(df, col1, col2), plot(df, col1, col2, col3), plot_correlation() and plot_missing().n”, “| height | Change the plots’ height in plot(df, col1), plot(df, col1, col2) and plot(df, col1, col2, col3), plot_correlation() and plot_missing().n”, “| bins | Apply to bins for Histogram, KDE Plot, Box Plot, Word Length, Line Chart, Spectrum.n”, “| ngroups | Apply to bars and slices for the Bar Chart and Pie Chart.” ]
“To help users quickly manage the parameters, currently, we defined four global parameters. Global parameter applies to all the plots which has that parameter.n”, “n”, “| Global Parameter | Description |\n", "| — | — | n”, “| width | Change the plots’ width in plot(df, col1), plot(df, col1, col2), plot(df, col1, col2, col3), plot_correlation() and plot_missing().n”, “| height | Change the plots’ height in plot(df, col1), plot(df, col1, col2) and plot(df, col1, col2, col3), plot_correlation() and plot_missing().n”, “| bins | Apply to bins for Histogram, KDE Plot, Box Plot, Word Length, Line Chart, Spectrum.n”, “| ngroups | Apply to bars and slices for the Bar Chart and Pie Chart.”
“cell_type”: “markdown”, “metadata”: {}, “source”: [ “## Local parameters” ]
“## Local parameters”
“cell_type”: “markdown”, “metadata”: {}, “source”: [ “Local parameters are plot-specified and the names are separated by .. The portion before the first . is plot name and the portion after the first . is parameter name. The . is also used when the parameter name contains more than one word. When global parameter and local parameter are both entered by a user in config, the global parameter will be overwrote by local parameters for specific plotsn”, “n”, “In the following tables we summarize the parameters for each API. You can also find the parameters for each plot in the Config API reference.n”, “n” ]
“Local parameters are plot-specified and the names are separated by .. The portion before the first . is plot name and the portion after the first . is parameter name. The . is also used when the parameter name contains more than one word. When global parameter and local parameter are both entered by a user in config, the global parameter will be overwrote by local parameters for specific plotsn”, “n”, “In the following tables we summarize the parameters for each API. You can also find the parameters for each plot in the Config API reference.n”, “n”
“cell_type”: “markdown”, “metadata”: {}, “source”: [ “### plot()n”, “n”, “| Local Parameter | Type |Default | Description |\n", "| — | — | — | — |\n", "|`hist.bins` | int | 50 | Maximum number of bins to display in the `Histogram` |\n", "| hist.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `Histogram |\n", "| bar.bars | int | 10 | Maximum number of bars to display in the Bar Chart |\n", "| bar.sort_descending | bool | True| Whether to sort the bars in descending order in the Bar Chart`|n”, “| `bar.yscale | str | "linear" | Y-axis scale ("linear" or "log") for the Bar Chart |\n", "| bar.color | str | "#1f77b4" | Color of the bars in the Bar Chart |\n", "| insight.duplicates.threshold | int | 1 | Warn if the percent of duplicated values is above this threshold in the Insights`|n”, “| `insight.similar_distribution.threshold | float | 0.05 | The significance level for Kolmogorov–Smirnov test in the Insights |\n", "| insight.uniform.threshold | float | 0.999 | The p-value threshold for chi-square test in the Insights |\n", "| insight.missing.threshold | int | 1 | Warn if the percent of missing values is above this threshold in the Insights |\n", "| insight.skewed.threshold | float | 1e-5 | The p-value for the scipy.skewtest which test whether the skew is different from the normal distributionin in the Insights |\n", "| insight.infinity.threshold | int | 1 | Warn if the percent of infinites is above this threshold in the Insights |\n", "| insight.zeros.threshold | int | 5 | Warn if the percent of zeros is above this threshold in the Insights |\n", "| insight.negatives.threshold | int | 1 | Warn if the percent of megatives is above this threshold in the Insights |\n", "| insight.normal.threshold | float | 0.99 | The p-value threshold for normal test, it is based on D’Agostino and Pearson’s test that combines skew and kurtosis to produce an omnibus test of normality in the Insights |\n", "| insight.high_cardinality.threshold | int | 50 | The threshold for unique values count, count larger than threshold yields high cardinality in the Insights |\n", "| insight.constant.threshold | int | 1 | The threshold for unique values count, count equals to threshold yields constant value in the Insights |\n", "| insight.outstanding_no1.threshold | float | 1.5 |The threshold for outstanding no1 insight, measures the ratio of the largest category count to the second-largest category count in the `Insights` |\n", "| insight.attribution.threshold | float | 0.5 | The threshold for the attribution insight, measures the percentage of the top 2 categories in the Insights |\n", "| insight.high_word_cardinality.threshold | int | 1000 | The threshold for the high word cardinality insight, which measures the number of words of that cateogory in the Insights |\n", "| insight.outstanding_no1_word.threshold | int | 0 | The threshold for the outstanding no1 word threshold, which measures the ratio of the most frequent word count to the second most frequent word count in the Insights |\n", "| insight.outlier.threshold | int | 0 | The threshold for the outlier count for the Insights in the Box Plot`|n”, “|`kde.bins | int | 50 | Maximum number of bins to display in the KDE Plot |\n", "| kde.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `KDE Plot |\n", "| kde.hist_color | str | "#aec7e8" | Color of the histogram in the KDE Plot |\n", "| kde.line_color | str | "#d62728" | Color of the line in the KDE Plot |\n", "| box.ngroups`| int | 15 | Maximum number of groups for categorical column to display in the `Box Plot |\n", "| box.bins`| int | 50 | Maximum number of bins for numerical column to display in the `Box Plot |\n", "| box.unit`| str | "auto" | Defines the time unit to group values over for a datetime column. It can be "year", "quarter", "month", "week", "day", "hour","minute", "second". With default value "auto", it will use the time unit such that the resulting number of groups is closest to 15 in the `Box Plot |\n", "| box.sort_descending`| bool | True | Whether to sort the boxes in descending order of frequency in the `Box Plot |\n", "| box.color | str | "#d62728" | Color of the Box Plot |\n", "| value_table.ngroups | |int | 10 | number of values to show in the value table |\n", "| pie.slices`| int | 10 | Maximum number of pie slices to display in the `Pie Chart`|n”, “| `pie.sort_descending`| bool | True | Whether to sort the slices in descending order of frequency in the `Pie Chart`|n”, “| `pie.colors | List[str] | None | Colors of the slices in the Pie Chart |\n", "| wordcloud.top_words`| int | 30 | Maximum number of most frequent words to display in the `Word Cloud`|n”, “| `wordcloud.stopword`| bool | True | Whether to remove stopwords in the `Word Cloud`|n”, “| `wordcloud.lemmatize`| bool | False | Whether to lemmatize the words in the `Word Cloud`|n”, “| `wordcloud.stem`| bool | False | Whether to apply Potter Stem on the words in the `Word Cloud`|n”, “| `wordfreq.top_words`| int | 30 | Maximum number of most frequent words to display in the `Word Frequency`|n”, “| `wordfreq.stopword`| bool | True | Whether to remove stopwords in the `Word Frequency`|n”, “| `wordfreq.lemmatize`| bool | False | Whether to lemmatize the words in the `Word Frequency`|n”, “| `wordfreq.stem`| bool | False | Whether to apply Potter Stem on the words in the `Word Frequency`|n”, “| `wordfreq.color | str | "#1f77b4" | Color of the bars in the Word Frequency Plot |\n", "| wordlen.bins`| int | 50 | Maximum number of bins in the `Word Length`|n”, “| `wordlen.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `Word Length`|n”, “| `wordlen.color | str | "#aec7e8" | Color of the bars in the Word Length Plot |\n", "| line.bins`| int | 50 | Maximum number of bins to display in the `Line Chart`|n”, “| `line.ngroups`| int | 10 | Maximum number of groups to display in the `Line Chart |\n", "| line.sort_descending`| bool | True | Whether to sort the groups in descending order of frequency in the `Line Chart |\n", "| line.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `Line Chart |\n", "| line.unit`| str | "auto" | Defines the time unit to group values over for a datetime column. It can be "year", "quarter", "month", "week", "day", "hour", "minute", "second". With default value "auto", it will use the time unit such that the resulting number of groups is closest to 15 in the `Line Chart |\n", "| line.agg`| str | "mean" | Specify the aggregate to use when aggregating over a numeric column in the `Line Chart |\n", "| scatter.sample_size`| int | 1000 | Number of points to randomly sample per partition in the `Scatter Plot |\n", "| scatter.sample_rate`| float | "None" | Defines the sample rate per partition in the `Scatter Plot. Cannot be used with sample_size. Set it to 1.0 for no sampling |\n", "| hexbin.tile_size | float | "auto" | The size of the tile in the hexbin plot. Measured from the middle of a hexagon to its left or right corner in the Hexbin Plot.|n”, “| nested.ngroups`| int | 10 | Maximum number of most frequent values from the first column to display in the `Nested Bar Chart |\n", "| nested.nsubgroups`| int | 5 | Maximum number of most frequent values from the second column to display (computed on the filtered data consisting of the most frequent values from the first column) in the `Nested Bar Chart |\n", "| stacked.ngroups`| int | 10 | Maximum number of most frequent values from the first column to display in the `Stacked Bar Chart |\n", "| stacked.nsubgroups`| int | 5 | Maximum number of most frequent values from the second column to display (computed on the filtered data consisting of the most frequent values from the first column) in the `Stacked Bar Chart |\n", "| stacked.unit`| str | "auto" | Defines the time unit to group values over for a datetime column. It can be "year", "quarter", "month", "week", "day", "hour", "minute", "second". With default value "auto", it will use the time unit such that the resulting number of groups is closest to 15 in the `Stacked Bar Chart |\n", "| stacked.sort_descending`| bool | True | Whether to sort the groups in descending order of frequency in the `Stacked Bar Chart |\n", "| heatmap.ngroups`| int | 10 | Maximum number of most frequent values from the first column to display in the `Heat Map |\n", "| heatmap.nsubgroups`| int | 5 | Maximum number of most frequent values from the second column to display (computed on the filtered data consisting of the most frequent values from the first column)in the `Heat Map |n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”, “n” ]
“### plot()n”, “n”, “| Local Parameter | Type |Default | Description |\n", "| — | — | — | — |\n", "|`hist.bins` | int | 50 | Maximum number of bins to display in the `Histogram` |\n", "| hist.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `Histogram |\n", "| bar.bars | int | 10 | Maximum number of bars to display in the Bar Chart |\n", "| bar.sort_descending | bool | True| Whether to sort the bars in descending order in the Bar Chart`|n”, “| `bar.yscale | str | "linear" | Y-axis scale ("linear" or "log") for the Bar Chart |\n", "| bar.color | str | "#1f77b4" | Color of the bars in the Bar Chart |\n", "| insight.duplicates.threshold | int | 1 | Warn if the percent of duplicated values is above this threshold in the Insights`|n”, “| `insight.similar_distribution.threshold | float | 0.05 | The significance level for Kolmogorov–Smirnov test in the Insights |\n", "| insight.uniform.threshold | float | 0.999 | The p-value threshold for chi-square test in the Insights |\n", "| insight.missing.threshold | int | 1 | Warn if the percent of missing values is above this threshold in the Insights |\n", "| insight.skewed.threshold | float | 1e-5 | The p-value for the scipy.skewtest which test whether the skew is different from the normal distributionin in the Insights |\n", "| insight.infinity.threshold | int | 1 | Warn if the percent of infinites is above this threshold in the Insights |\n", "| insight.zeros.threshold | int | 5 | Warn if the percent of zeros is above this threshold in the Insights |\n", "| insight.negatives.threshold | int | 1 | Warn if the percent of megatives is above this threshold in the Insights |\n", "| insight.normal.threshold | float | 0.99 | The p-value threshold for normal test, it is based on D’Agostino and Pearson’s test that combines skew and kurtosis to produce an omnibus test of normality in the Insights |\n", "| insight.high_cardinality.threshold | int | 50 | The threshold for unique values count, count larger than threshold yields high cardinality in the Insights |\n", "| insight.constant.threshold | int | 1 | The threshold for unique values count, count equals to threshold yields constant value in the Insights |\n", "| insight.outstanding_no1.threshold | float | 1.5 |The threshold for outstanding no1 insight, measures the ratio of the largest category count to the second-largest category count in the `Insights` |\n", "| insight.attribution.threshold | float | 0.5 | The threshold for the attribution insight, measures the percentage of the top 2 categories in the Insights |\n", "| insight.high_word_cardinality.threshold | int | 1000 | The threshold for the high word cardinality insight, which measures the number of words of that cateogory in the Insights |\n", "| insight.outstanding_no1_word.threshold | int | 0 | The threshold for the outstanding no1 word threshold, which measures the ratio of the most frequent word count to the second most frequent word count in the Insights |\n", "| insight.outlier.threshold | int | 0 | The threshold for the outlier count for the Insights in the Box Plot`|n”, “|`kde.bins | int | 50 | Maximum number of bins to display in the KDE Plot |\n", "| kde.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `KDE Plot |\n", "| kde.hist_color | str | "#aec7e8" | Color of the histogram in the KDE Plot |\n", "| kde.line_color | str | "#d62728" | Color of the line in the KDE Plot |\n", "| box.ngroups`| int | 15 | Maximum number of groups for categorical column to display in the `Box Plot |\n", "| box.bins`| int | 50 | Maximum number of bins for numerical column to display in the `Box Plot |\n", "| box.unit`| str | "auto" | Defines the time unit to group values over for a datetime column. It can be "year", "quarter", "month", "week", "day", "hour","minute", "second". With default value "auto", it will use the time unit such that the resulting number of groups is closest to 15 in the `Box Plot |\n", "| box.sort_descending`| bool | True | Whether to sort the boxes in descending order of frequency in the `Box Plot |\n", "| box.color | str | "#d62728" | Color of the Box Plot |\n", "| value_table.ngroups | |int | 10 | number of values to show in the value table |\n", "| pie.slices`| int | 10 | Maximum number of pie slices to display in the `Pie Chart`|n”, “| `pie.sort_descending`| bool | True | Whether to sort the slices in descending order of frequency in the `Pie Chart`|n”, “| `pie.colors | List[str] | None | Colors of the slices in the Pie Chart |\n", "| wordcloud.top_words`| int | 30 | Maximum number of most frequent words to display in the `Word Cloud`|n”, “| `wordcloud.stopword`| bool | True | Whether to remove stopwords in the `Word Cloud`|n”, “| `wordcloud.lemmatize`| bool | False | Whether to lemmatize the words in the `Word Cloud`|n”, “| `wordcloud.stem`| bool | False | Whether to apply Potter Stem on the words in the `Word Cloud`|n”, “| `wordfreq.top_words`| int | 30 | Maximum number of most frequent words to display in the `Word Frequency`|n”, “| `wordfreq.stopword`| bool | True | Whether to remove stopwords in the `Word Frequency`|n”, “| `wordfreq.lemmatize`| bool | False | Whether to lemmatize the words in the `Word Frequency`|n”, “| `wordfreq.stem`| bool | False | Whether to apply Potter Stem on the words in the `Word Frequency`|n”, “| `wordfreq.color | str | "#1f77b4" | Color of the bars in the Word Frequency Plot |\n", "| wordlen.bins`| int | 50 | Maximum number of bins in the `Word Length`|n”, “| `wordlen.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `Word Length`|n”, “| `wordlen.color | str | "#aec7e8" | Color of the bars in the Word Length Plot |\n", "| line.bins`| int | 50 | Maximum number of bins to display in the `Line Chart`|n”, “| `line.ngroups`| int | 10 | Maximum number of groups to display in the `Line Chart |\n", "| line.sort_descending`| bool | True | Whether to sort the groups in descending order of frequency in the `Line Chart |\n", "| line.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `Line Chart |\n", "| line.unit`| str | "auto" | Defines the time unit to group values over for a datetime column. It can be "year", "quarter", "month", "week", "day", "hour", "minute", "second". With default value "auto", it will use the time unit such that the resulting number of groups is closest to 15 in the `Line Chart |\n", "| line.agg`| str | "mean" | Specify the aggregate to use when aggregating over a numeric column in the `Line Chart |\n", "| scatter.sample_size`| int | 1000 | Number of points to randomly sample per partition in the `Scatter Plot |\n", "| scatter.sample_rate`| float | "None" | Defines the sample rate per partition in the `Scatter Plot. Cannot be used with sample_size. Set it to 1.0 for no sampling |\n", "| hexbin.tile_size | float | "auto" | The size of the tile in the hexbin plot. Measured from the middle of a hexagon to its left or right corner in the Hexbin Plot.|n”, “| nested.ngroups`| int | 10 | Maximum number of most frequent values from the first column to display in the `Nested Bar Chart |\n", "| nested.nsubgroups`| int | 5 | Maximum number of most frequent values from the second column to display (computed on the filtered data consisting of the most frequent values from the first column) in the `Nested Bar Chart |\n", "| stacked.ngroups`| int | 10 | Maximum number of most frequent values from the first column to display in the `Stacked Bar Chart |\n", "| stacked.nsubgroups`| int | 5 | Maximum number of most frequent values from the second column to display (computed on the filtered data consisting of the most frequent values from the first column) in the `Stacked Bar Chart |\n", "| stacked.unit`| str | "auto" | Defines the time unit to group values over for a datetime column. It can be "year", "quarter", "month", "week", "day", "hour", "minute", "second". With default value "auto", it will use the time unit such that the resulting number of groups is closest to 15 in the `Stacked Bar Chart |\n", "| stacked.sort_descending`| bool | True | Whether to sort the groups in descending order of frequency in the `Stacked Bar Chart |\n", "| heatmap.ngroups`| int | 10 | Maximum number of most frequent values from the first column to display in the `Heat Map |\n", "| heatmap.nsubgroups`| int | 5 | Maximum number of most frequent values from the second column to display (computed on the filtered data consisting of the most frequent values from the first column)in the `Heat Map |n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”, “n”
“cell_type”: “markdown”, “metadata”: {}, “source”: [ “### plot_missing()n”, “n”, “| Local Parameter | Type |Default | Description |\n", "| — | — | — | — |\n", "| spectrum.bins | int | 20 | Maximum number of bins to display in the Spectrum |n”, “|PDF.sample_size | int | 100 | Number of evenly spaced samples between the minimum and maximum values to compute the PDF at |n”, “|CDF.sample_size | int | 100 | Number of evenly spaced samples between the minimum and maximum values to compute the CDF at |n”, “n” ]
“### plot_missing()n”, “n”, “| Local Parameter | Type |Default | Description |\n", "| — | — | — | — |\n", "| spectrum.bins | int | 20 | Maximum number of bins to display in the Spectrum |n”, “|PDF.sample_size | int | 100 | Number of evenly spaced samples between the minimum and maximum values to compute the PDF at |n”, “|CDF.sample_size | int | 100 | Number of evenly spaced samples between the minimum and maximum values to compute the CDF at |n”, “n”
“cell_type”: “markdown”, “metadata”: {}, “source”: [ “### plot_correlation()n”, “n”, “| Local Parameter | Type |Default | Description |\n", "| — | — | — | — |\n", "| scatter.sample_size`| int | 1000 | Number of points to randomly sample per partition in the `Scatter Plot in plot_correlation(df, x, y)`|”, “| `scatter.sample_rate`| float | "None" | Defines the sample rate per partition in the `Scatter Plot. Cannot be used with sample_size. Set it to 1.0 for no sampling |n”, ]
“### plot_correlation()n”, “n”, “| Local Parameter | Type |Default | Description |\n", "| — | — | — | — |\n", "| scatter.sample_size`| int | 1000 | Number of points to randomly sample per partition in the `Scatter Plot in plot_correlation(df, x, y)`|”, “| `scatter.sample_rate`| float | "None" | Defines the sample rate per partition in the `Scatter Plot. Cannot be used with sample_size. Set it to 1.0 for no sampling |n”,
“cell_type”: “markdown”, “metadata”: {}, “source”: [ “### create_report()n”, “n”, “| Local Parameter | Type |Default | Description |\n", "| — | — | — | — |\n", "| bar.bars | int | 10 | Maximum number of bars to display in the Bar Chart |\n", "| bar.sort_descending | bool | True| Whether to sort the bars in descending order in the Bar Chart`|n”, “| `bar.yscale | str | "linear" | Y-axis scale ("linear" or "log") for the Bar Chart |\n", "| pie.slices`| int | 10 | Maximum number of pie slices to display in the `Pie Chart`|n”, “| `pie.sort_descending`| bool | True | Whether to sort the slices in descending order of frequency in the `Pie Chart`|n”, “| `wordcloud.top_words`| int | 30 | Maximum number of most frequent words to display in the `Word Cloud`|n”, “| `wordcloud.stopword`| bool | True | Whether to remove stopwords in the `Word Cloud`|n”, “| `wordcloud.lemmatize`| bool | False | Whether to lemmatize the words in the `Word Cloud`|n”, “| `wordcloud.stem`| bool | False | Whether to apply Potter Stem on the words in the `Word Cloud`|n”, “| `wordfreq.top_words`| int | 30 | Maximum number of most frequent words to display in the `Word Frequency`|n”, “| `wordcloud.stopword`| bool | True | Whether to remove stopwords in the `Word Frequency`|n”, “| `wordcloud.lemmatize`| bool | False | Whether to lemmatize the words in the `Word Frequency`|n”, “| `wordcloud.stem`| bool | False | Whether to apply Potter Stem on the words in the `Word Frequency`|n”, “| `wordlen.bins`| int | 50 | Maximum number of bins in the `Word Length`|n”, “| `wordlen.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `Word Length`|n”, “| `line.unit`| str | "auto" | Defines the time unit to group values over for a datetime column. It can be "year", "quarter", "month", "week", "day", "hour", "minute", "second". With default value "auto", it will use the time unit such that the resulting number of groups is closest to 15 in the `Line Chart |\n", "|`kde.bins` | int | 50 | Maximum number of bins in the `KDE Plot` |\n", "| kde.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `KDE Plot |\n", "| box.sort_descending`| bool | True | Whether to sort the boxes in descending order of frequency in the `Box Plot |\n", "| spectrum.bins | int | 20 | Maximum number of bins to display in the Spectrum |n” ]
“### create_report()n”, “n”, “| Local Parameter | Type |Default | Description |\n", "| — | — | — | — |\n", "| bar.bars | int | 10 | Maximum number of bars to display in the Bar Chart |\n", "| bar.sort_descending | bool | True| Whether to sort the bars in descending order in the Bar Chart`|n”, “| `bar.yscale | str | "linear" | Y-axis scale ("linear" or "log") for the Bar Chart |\n", "| pie.slices`| int | 10 | Maximum number of pie slices to display in the `Pie Chart`|n”, “| `pie.sort_descending`| bool | True | Whether to sort the slices in descending order of frequency in the `Pie Chart`|n”, “| `wordcloud.top_words`| int | 30 | Maximum number of most frequent words to display in the `Word Cloud`|n”, “| `wordcloud.stopword`| bool | True | Whether to remove stopwords in the `Word Cloud`|n”, “| `wordcloud.lemmatize`| bool | False | Whether to lemmatize the words in the `Word Cloud`|n”, “| `wordcloud.stem`| bool | False | Whether to apply Potter Stem on the words in the `Word Cloud`|n”, “| `wordfreq.top_words`| int | 30 | Maximum number of most frequent words to display in the `Word Frequency`|n”, “| `wordcloud.stopword`| bool | True | Whether to remove stopwords in the `Word Frequency`|n”, “| `wordcloud.lemmatize`| bool | False | Whether to lemmatize the words in the `Word Frequency`|n”, “| `wordcloud.stem`| bool | False | Whether to apply Potter Stem on the words in the `Word Frequency`|n”, “| `wordlen.bins`| int | 50 | Maximum number of bins in the `Word Length`|n”, “| `wordlen.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `Word Length`|n”, “| `line.unit`| str | "auto" | Defines the time unit to group values over for a datetime column. It can be "year", "quarter", "month", "week", "day", "hour", "minute", "second". With default value "auto", it will use the time unit such that the resulting number of groups is closest to 15 in the `Line Chart |\n", "|`kde.bins` | int | 50 | Maximum number of bins in the `KDE Plot` |\n", "| kde.yscale`| str | "linear" | Y-axis scale ("linear" or "log") for the `KDE Plot |\n", "| box.sort_descending`| bool | True | Whether to sort the boxes in descending order of frequency in the `Box Plot |\n", "| spectrum.bins | int | 20 | Maximum number of bins to display in the Spectrum |n”
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