It is an enhanced jitter strip chart, where the width of the jitter is controlled by the density distribution of the data within each class. {usage} Parameters ---------- {common_parameters} …

It is an enhanced jitter strip chart, where the width of the jitter is controlled by the density distribution of the data within each class. {usage} Parameters ---------- {common_parameters} …

See Also -------- plotnine.geoms.geom_violin statsmodels.nonparametric.kde.KDEUnivariate statsmodels.nonparametric.kde.KDEUnivariate.fit """_aesthetics_doc="""{aesthetics_table} .. …

Parameters: filllist-likeList of colors for the strips. The default is ("#AAAAAA", "#CCCCCC") fill_range: 'cycle' | 'nocycle' | 'auto' | 'no'How to fill stripes beyond the range of scale: 'cycle' # …

classplotnine.scales.scale_color_hue(h=0.01, l=0.6, s=0.65, color_space:Literal['hls','husl']='hls', **kwargs)[source] ¶

classplotnine.themes.themeable.legend_spacing(theme_element:Any=None)[source] ¶ Bases: themeable Spacing between two adjacent legends Parameters: theme_elementfloat

This themeable exists mainly to cater for differences in how the text is aligned compared to the entry based legend. Unless you experience those alignment issues (i.e when using parameters …

plotnine.data.pageviews ¶plotnine.data.pageviews ¶

"outputs": [], "source": [ "import sys\n", "import random\n", "\n", "from plotnine import ggplot, geom_point, aes, geom_line, theme\n", "import pandas as pd\n", "import numpy as np\n", "\n", …