seaborn.stripplot

A strip plot is a scatter plot where one of the variables is categorical. They can be combined with other plots to provide additional information. For example, a boxplot with an overlaid strip plot becomes more similar to a violin plot because some additional information about how the underlying data is distributed becomes visible.

dataset:



In [66]:

    
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
plt.rcParams['figure.figsize'] = (20.0, 10.0)
plt.rcParams['font.family'] = "serif"



In [67]:

    
from sklearn import datasets
iris_data = datasets.load_iris()



In [68]:

    
df = pd.DataFrame(data=np.column_stack([iris_data['data'],iris_data['target']]),
                  columns=iris_data['feature_names'] + ['species'])



In [69]:

    
df['species'] = iris_data['target_names'][df.species.astype(int)]

Basic plot



In [126]:

    
p = sns.stripplot(data=df, x='species',y='sepal length (cm)',jitter=1,marker='^',hue='species')
handles,labels = p.get_legend_handles_labels()
for l in labels[:3]:
    
    l += " Sepal Length"
    print(l)
for l in labels[:3]:
    print(l)
plt.legend(handles, labels)
# sns.stripplot(data=df, x='species',y='sepal width (cm)',palette='magma',jitter=1,marker='s',hue='species')
# handles,labels = p.get_legend_handles_labels()
# # for h in handles[:2]:
# #     h.set_label(h.get_label() + " Sepal Length")
# # for h in handles[2:]:
# #     h.set_label(h.get_label() + " Sepal Width")

# for l in labels[2:]:
#     l+= " Sepal Width"
# plt.legend(handles, labels)









    



setosa Sepal Length
versicolor Sepal Length
virginica Sepal Length
setosa
versicolor
virginica






    Out[126]:





<matplotlib.legend.Legend at 0x7fdfcda1d7b8>



In [89]:

    
#ns.stripplot(data=df, x='species',y='sepal length (cm)',jitter=1,marker='^',hue='species')
#sns.stripplot(data=df, x='species',y='sepal width (cm)',palette='magma',jitter=1,marker='^',hue='species')



In [150]:

    
fig, ax = plt.subplots(1,1)
p = sns.stripplot(data=df, x='species',y='sepal length (cm)',jitter=1,marker='^',hue='species',ax = ax)
handles,labels = ax.get_legend_handles_labels()
new_labels = []
for l in labels:
    new_labels.append(l.capitalize() + " Sepal Length")
plt.legend(handles, new_labels)









    Out[150]:





<matplotlib.legend.Legend at 0x7fdfcd034780>



In [143]:

    
for i in labels:
    i=0
print(labels)









    



['setosa', 'versicolor', 'virginica']



In [109]:

    
plt.show()



In [100]:

    
dir(h[0])









    Out[100]:





['_A',
 '__class__',
 '__delattr__',
 '__dict__',
 '__dir__',
 '__doc__',
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 '_original_facecolor',
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 '_prop_order',
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 'axes',
 'callbacksSM',
 'changed',
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 'clipbox',
 'cmap',
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 'contains',
 'convert_xunits',
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 'draw',
 'eventson',
 'figure',
 'findobj',
 'format_cursor_data',
 'get_agg_filter',
 'get_alpha',
 'get_animated',
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 'get_clip_box',
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 'get_clip_path',
 'get_cmap',
 'get_contains',
 'get_cursor_data',
 'get_dashes',
 'get_datalim',
 'get_edgecolor',
 'get_edgecolors',
 'get_facecolor',
 'get_facecolors',
 'get_figure',
 'get_fill',
 'get_gid',
 'get_hatch',
 'get_label',
 'get_linestyle',
 'get_linestyles',
 'get_linewidth',
 'get_linewidths',
 'get_offset_position',
 'get_offset_transform',
 'get_offsets',
 'get_path_effects',
 'get_paths',
 'get_picker',
 'get_pickradius',
 'get_rasterized',
 'get_sizes',
 'get_sketch_params',
 'get_snap',
 'get_transform',
 'get_transformed_clip_path_and_affine',
 'get_transforms',
 'get_url',
 'get_urls',
 'get_visible',
 'get_window_extent',
 'get_zorder',
 'have_units',
 'hitlist',
 'is_figure_set',
 'is_transform_set',
 'mouseover',
 'norm',
 'pchanged',
 'pick',
 'pickable',
 'properties',
 'remove',
 'remove_callback',
 'set',
 'set_agg_filter',
 'set_alpha',
 'set_animated',
 'set_antialiased',
 'set_antialiaseds',
 'set_array',
 'set_axes',
 'set_clim',
 'set_clip_box',
 'set_clip_on',
 'set_clip_path',
 'set_cmap',
 'set_color',
 'set_contains',
 'set_dashes',
 'set_edgecolor',
 'set_edgecolors',
 'set_facecolor',
 'set_facecolors',
 'set_figure',
 'set_gid',
 'set_hatch',
 'set_label',
 'set_linestyle',
 'set_linestyles',
 'set_linewidth',
 'set_linewidths',
 'set_lw',
 'set_norm',
 'set_offset_position',
 'set_offsets',
 'set_path_effects',
 'set_paths',
 'set_picker',
 'set_pickradius',
 'set_rasterized',
 'set_sizes',
 'set_sketch_params',
 'set_snap',
 'set_transform',
 'set_url',
 'set_urls',
 'set_visible',
 'set_zorder',
 'stale',
 'stale_callback',
 'sticky_edges',
 'to_rgba',
 'update',
 'update_dict',
 'update_from',
 'update_scalarmappable',
 'zorder']



In [102]:

    
h[3].get_label()









    Out[102]:





'setosa'



In [ ]: