dataprp库本地参数

To help users quickly manage the parameters, currently, we defined four global parameters. Global parameter applies to all the plots which has that parameter.

Global Parameter	Description
width	Change the plots’ width in plot(df, col1), plot(df, col1, col2), plot(df, col1, col2, col3), plot_correlation() and plot_missing().
height	Change the plots’ height in plot(df, col1), plot(df, col1, col2) and plot(df, col1, col2, col3), plot_correlation() and plot_missing().
bins	Apply to bins for Histogram, KDE Plot, Box Plot, Word Length, Line Chart, Spectrum.
ngroups	Apply to bars and slices for the Bar Chart and Pie Chart.

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 plots

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.

plot()

Local Parameter	Type	Default	Description
`hist.bins`	int	50	Maximum number of bins to display in the `Histogram`
hist.yscale`	str	“linear”	Y-axis scale (“linear” or “log”) for the `Histogram
bar.bars	int	10	Maximum number of bars to display in the Bar Chart
bar.sort_descending	bool	True	Whether to sort the bars in descending order in the Bar Chart`
bar.color	str	“#1f77b4”	Color of the bars in the Bar Chart
insight.duplicates.threshold	int	1	Warn if the percent of duplicated values is above this threshold in the Insights`
insight.uniform.threshold	float	0.999	The p-value threshold for chi-square test in the Insights
insight.missing.threshold	int	1	Warn if the percent of missing values is above this threshold in the Insights
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
insight.infinity.threshold	int	1	Warn if the percent of infinites is above this threshold in the Insights
insight.zeros.threshold	int	5	Warn if the percent of zeros is above this threshold in the Insights
insight.negatives.threshold	int	1	Warn if the percent of megatives is above this threshold in the Insights
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
insight.high_cardinality.threshold	int	50	The threshold for unique values count, count larger than threshold yields high cardinality in the Insights
insight.constant.threshold	int	1	The threshold for unique values count, count equals to threshold yields constant value in the Insights
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`
insight.attribution.threshold	float	0.5	The threshold for the attribution insight, measures the percentage of the top 2 categories in the Insights
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
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
insight.outlier.threshold	int	0	The threshold for the outlier count for the Insights in the Box Plot`
kde.yscale`	str	“linear”	Y-axis scale (“linear” or “log”) for the `KDE Plot
kde.hist_color	str	“#aec7e8”	Color of the histogram in the KDE Plot
kde.line_color	str	“#d62728”	Color of the line in the KDE Plot
box.ngroups`	int	15	Maximum number of groups for categorical column to display in the `Box Plot
box.bins`	int	50	Maximum number of bins for numerical column to display in the `Box Plot
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
box.sort_descending`	bool	True	Whether to sort the boxes in descending order of frequency in the `Box Plot
box.color	str	“#d62728”	Color of the Box Plot
value_table.ngroups		int	10
pie.slices`	int	10	Maximum number of pie slices to display in the `Pie Chart`
wordcloud.top_words`	int	30	Maximum number of most frequent words to display in the `Word Cloud`
wordlen.bins`	int	50	Maximum number of bins in the `Word Length`
line.bins`	int	50	Maximum number of bins to display in the `Line Chart`
line.sort_descending`	bool	True	Whether to sort the groups in descending order of frequency in the `Line Chart
line.yscale`	str	“linear”	Y-axis scale (“linear” or “log”) for the `Line Chart
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
line.agg`	str	“mean”	Specify the aggregate to use when aggregating over a numeric column in the `Line Chart
scatter.sample_size`	int	1000	Number of points to randomly sample per partition in the `Scatter Plot
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
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.
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
stacked.ngroups`	int	10	Maximum number of most frequent values from the first column to display in the `Stacked Bar Chart
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
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
stacked.sort_descending`	bool	True	Whether to sort the groups in descending order of frequency in the `Stacked Bar Chart
heatmap.ngroups`	int	10	Maximum number of most frequent values from the first column to display in the `Heat Map
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

plot_missing()

Local Parameter	Type	Default	Description
spectrum.bins	int	20	Maximum number of bins to display in the Spectrum
PDF.sample_size	int	100	Number of evenly spaced samples between the minimum and maximum values to compute the PDF at
CDF.sample_size	int	100	Number of evenly spaced samples between the minimum and maximum values to compute the CDF at

plot_correlation()

Local Parameter	Type	Default	Description
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

create_report()

Local Parameter	Type	Default	Description
bar.bars	int	10	Maximum number of bars to display in the Bar Chart
bar.sort_descending	bool	True	Whether to sort the bars in descending order in the Bar Chart`
`bar.yscale	str	“linear”	Y-axis scale (“linear” or “log”) for the Bar Chart
pie.slices`	int	10	Maximum number of pie slices to display in the `Pie Chart`
`pie.sort_descending`	bool	True	Whether to sort the slices in descending order of frequency in the `Pie Chart`
`wordcloud.top_words`	int	30	Maximum number of most frequent words to display in the `Word Cloud`
`wordcloud.stopword`	bool	True	Whether to remove stopwords in the `Word Cloud`
`wordcloud.lemmatize`	bool	False	Whether to lemmatize the words in the `Word Cloud`
`wordcloud.stem`	bool	False	Whether to apply Potter Stem on the words in the `Word Cloud`
`wordfreq.top_words`	int	30	Maximum number of most frequent words to display in the `Word Frequency`
`wordcloud.stopword`	bool	True	Whether to remove stopwords in the `Word Frequency`
`wordcloud.lemmatize`	bool	False	Whether to lemmatize the words in the `Word Frequency`
`wordcloud.stem`	bool	False	Whether to apply Potter Stem on the words in the `Word Frequency`
`wordlen.bins`	int	50	Maximum number of bins in the `Word Length`
`wordlen.yscale`	str	“linear”	Y-axis scale (“linear” or “log”) for the `Word Length`
`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
`kde.bins`	int	50	Maximum number of bins in the `KDE Plot`
kde.yscale`	str	“linear”	Y-axis scale (“linear” or “log”) for the `KDE Plot
box.sort_descending`	bool	True	Whether to sort the boxes in descending order of frequency in the `Box Plot
spectrum.bins	int	20	Maximum number of bins to display in the Spectrum

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原文地址：https://blog.csdn.net/weixin_41168869/article/details/133613380