{"id":1936,"date":"2023-08-10T23:52:35","date_gmt":"2023-08-11T06:52:35","guid":{"rendered":"https:\/\/gantovnik.com\/bio-tips\/?p=1936"},"modified":"2023-08-10T23:52:35","modified_gmt":"2023-08-11T06:52:35","slug":"382-dot-plot-with-several-variables-using-seaborn-library","status":"publish","type":"post","link":"https:\/\/gantovnik.com\/bio-tips\/2023\/08\/382-dot-plot-with-several-variables-using-seaborn-library\/","title":{"rendered":"#382 Dot plot with several variables using seaborn library"},"content":{"rendered":"<p><a href=\"https:\/\/gantovnik.com\/bio-tips\/2023\/08\/382-dot-plot-with-several-variables-using-seaborn-library\/ex382\/\" rel=\"attachment wp-att-1937\"><img data-recalc-dims=\"1\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex382.png?resize=1080%2C864&#038;ssl=1\" alt=\"\" width=\"1080\" height=\"864\" class=\"alignnone size-full wp-image-1937\" srcset=\"https:\/\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex382.png 1250w, https:\/\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex382-980x784.png 980w, https:\/\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex382-480x384.png 480w\" sizes=\"(min-width: 0px) and (max-width: 480px) 480px, (min-width: 481px) and (max-width: 980px) 980px, (min-width: 981px) 1250px, 100vw\" \/><\/a><\/p>\n<pre class=\"brush: python; title: ; notranslate\" title=\"\">\r\n#Overlapping densities ridge plot using seaborn library\r\nimport matplotlib.pyplot as plt\r\n#conda install -c anaconda seaborn\r\nimport seaborn as sns\r\nsns.set_theme(style=&quot;whitegrid&quot;)\r\n\r\n\r\ndef main():\r\n    # Load the dataset\r\n    crashes = sns.load_dataset(&quot;car_crashes&quot;)\r\n\r\n    # Make the PairGrid\r\n    g = sns.PairGrid(crashes.sort_values(&quot;total&quot;, ascending=False),\r\n                     x_vars=crashes.columns&#x5B;:-3], y_vars=&#x5B;&quot;abbrev&quot;],\r\n                     height=10, aspect=.25)\r\n\r\n    # Draw a dot plot using the stripplot function\r\n    g.map(sns.stripplot, size=10, orient=&quot;h&quot;, jitter=False,\r\n          palette=&quot;flare_r&quot;, linewidth=1, edgecolor=&quot;w&quot;)\r\n\r\n    # Use the same x axis limits on all columns and add better labels\r\n    g.set(xlim=(0, 25), xlabel=&quot;Crashes&quot;, ylabel=&quot;&quot;)\r\n\r\n    # Use semantically meaningful titles for the columns\r\n    titles = &#x5B;&quot;Total crashes&quot;, &quot;Speeding crashes&quot;, &quot;Alcohol crashes&quot;,\r\n              &quot;Not distracted crashes&quot;, &quot;No previous crashes&quot;]\r\n\r\n    for ax, title in zip(g.axes.flat, titles):\r\n        # Set a different title for each axes\r\n        ax.set(title=title)\r\n\r\n        # Make the grid horizontal instead of vertical\r\n        ax.xaxis.grid(False)\r\n        ax.yaxis.grid(True)\r\n\r\n    sns.despine(left=True, bottom=True)\r\n    plt.savefig(&quot;ex382.png&quot;, dpi=100)\r\n    plt.show()\r\n\r\nif __name__ == '__main__':\r\n    main()\r\n<\/pre>\n","protected":false},"excerpt":{"rendered":"<p>#Overlapping densities ridge plot using seaborn library import matplotlib.pyplot as plt #conda install -c anaconda seaborn import seaborn as sns sns.set_theme(style=&quot;whitegrid&quot;) def main(): # Load the dataset crashes = sns.load_dataset(&quot;car_crashes&quot;) # Make the PairGrid g = sns.PairGrid(crashes.sort_values(&quot;total&quot;, ascending=False), x_vars=crashes.columns&#x5B;:-3], y_vars=&#x5B;&quot;abbrev&quot;], height=10, aspect=.25) # Draw a dot plot using the stripplot function g.map(sns.stripplot, size=10, orient=&quot;h&quot;, jitter=False, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","_lmt_disableupdate":"yes","_lmt_disable":"","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[91,2,92],"tags":[],"class_list":["post-1936","post","type-post","status-publish","format-standard","hentry","category-plot","category-python","category-seaborn"],"modified_by":"gantovnik","jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p8bH0k-ve","jetpack_likes_enabled":true,"jetpack-related-posts":[{"id":1919,"url":"https:\/\/gantovnik.com\/bio-tips\/2023\/08\/375-regression-fit-over-a-strip-plot-using-seaborn-library\/","url_meta":{"origin":1936,"position":0},"title":"#375 Regression fit over a strip plot using seaborn library","author":"gantovnik","date":"2023-08-10","format":false,"excerpt":"[code language=\"python\"] #Regression fit over a strip plot import matplotlib.pyplot as plt #conda install -c anaconda seaborn import seaborn as sns sns.set_theme() def main(): mpg = sns.load_dataset(\"mpg\") sns.catplot( data=mpg, x=\"cylinders\", y=\"acceleration\", hue=\"weight\", native_scale=True, zorder=1 ) sns.regplot( data=mpg, x=\"cylinders\", y=\"acceleration\", scatter=False, truncate=False, order=2, color=\".2\", ) plt.savefig(\"ex375.png\", dpi=100) plt.show() if __name__ ==\u2026","rel":"","context":"In &quot;plot&quot;","block_context":{"text":"plot","link":"https:\/\/gantovnik.com\/bio-tips\/category\/plot\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/11\/ex394.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/11\/ex394.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/11\/ex394.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":1938,"url":"https:\/\/gantovnik.com\/bio-tips\/2023\/08\/383-horizontal-bar-plot-using-seaborn-library\/","url_meta":{"origin":1936,"position":1},"title":"#383 Horizontal bar plot using seaborn library","author":"gantovnik","date":"2023-08-11","format":false,"excerpt":"[code language=\"python\"] #Horizontal bar plot using seaborn library import matplotlib.pyplot as plt #conda install -c anaconda seaborn import seaborn as sns sns.set_theme(style=\"whitegrid\") def main(): # Initialize the matplotlib figure f, ax = plt.subplots(figsize=(6, 15)) # Load the example car crash dataset crashes = sns.load_dataset(\"car_crashes\").sort_values(\"total\", ascending=False) # Plot the total crashes\u2026","rel":"","context":"In &quot;plot&quot;","block_context":{"text":"plot","link":"https:\/\/gantovnik.com\/bio-tips\/category\/plot\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex383.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex383.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex383.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":1917,"url":"https:\/\/gantovnik.com\/bio-tips\/2023\/08\/374-hexbin-plot-with-marginal-distributions-using-seaborn-library\/","url_meta":{"origin":1936,"position":2},"title":"#374 Hexbin plot with marginal distributions using seaborn library","author":"gantovnik","date":"2023-08-10","format":false,"excerpt":"[code language=\"python\"] import numpy as np import matplotlib.pyplot as plt #conda install -c anaconda seaborn import seaborn as sns sns.set_theme(style=\"ticks\") def main(): rs = np.random.RandomState(11) x = rs.gamma(2, size=1000) y = -.5 * x + rs.normal(size=1000) sns.jointplot(x=x, y=y, kind=\"hex\", color=\"#4CB323\") plt.savefig(\"ex374.png\", dpi=100) plt.show() if __name__ == '__main__': main() [\/code]","rel":"","context":"In &quot;plot&quot;","block_context":{"text":"plot","link":"https:\/\/gantovnik.com\/bio-tips\/category\/plot\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex374.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex374.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex374.png?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":1940,"url":"https:\/\/gantovnik.com\/bio-tips\/2023\/08\/384-linear-regression-with-marginal-distributions-using-seaborn-library\/","url_meta":{"origin":1936,"position":3},"title":"#384 Linear regression with marginal distributions using seaborn library","author":"gantovnik","date":"2023-08-11","format":false,"excerpt":"[code language=\"python\"] #Linear regression with marginal distributions using seaborn library import matplotlib.pyplot as plt #conda install -c anaconda seaborn import seaborn as sns sns.set_theme(style=\"darkgrid\") def main(): tips = sns.load_dataset(\"tips\") g = sns.jointplot(x=\"total_bill\", y=\"tip\", data=tips, kind=\"reg\", truncate=False, xlim=(0, 60), ylim=(0, 12), color=\"m\", height=7) plt.savefig(\"ex384.png\", dpi=100) plt.show() if __name__ == '__main__': main()\u2026","rel":"","context":"In &quot;plot&quot;","block_context":{"text":"plot","link":"https:\/\/gantovnik.com\/bio-tips\/category\/plot\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex384.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex384.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex384.png?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex384.png?resize=700%2C400&ssl=1 2x"},"classes":[]},{"id":1933,"url":"https:\/\/gantovnik.com\/bio-tips\/2023\/08\/381-overlapping-densities-ridge-plot-using-seaborn-library\/","url_meta":{"origin":1936,"position":4},"title":"#381 Overlapping densities ridge plot using seaborn library","author":"gantovnik","date":"2023-08-10","format":false,"excerpt":"[code language=\"python\"] #Overlapping densities ridge plot using seaborn library import matplotlib.pyplot as plt import pandas as pd import numpy as np #conda install -c anaconda seaborn import seaborn as sns sns.set_theme(style=\"white\", rc={\"axes.facecolor\": (0, 0, 0, 0)}) def main(): # Create the data rs = np.random.RandomState(1979) x = rs.randn(500) g =\u2026","rel":"","context":"In &quot;plot&quot;","block_context":{"text":"plot","link":"https:\/\/gantovnik.com\/bio-tips\/category\/plot\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex381.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex381.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex381.png?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex381.png?resize=700%2C400&ssl=1 2x"},"classes":[]},{"id":1943,"url":"https:\/\/gantovnik.com\/bio-tips\/2023\/08\/385-scatterplot-matrix-using-seaborn-library\/","url_meta":{"origin":1936,"position":5},"title":"#385 Scatterplot matrix using seaborn library","author":"gantovnik","date":"2023-08-13","format":false,"excerpt":"[code language=\"python\"] #Scatterplot matrix using seaborn library import matplotlib.pyplot as plt #conda install -c anaconda seaborn import seaborn as sns sns.set_theme(style=\"ticks\") def main(): df = sns.load_dataset(\"penguins\") sns.pairplot(df, hue=\"species\") plt.savefig(\"ex385.png\", dpi=100) plt.show() if __name__ == '__main__': main() [\/code]","rel":"","context":"In &quot;plot&quot;","block_context":{"text":"plot","link":"https:\/\/gantovnik.com\/bio-tips\/category\/plot\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex385.png?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex385.png?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex385.png?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex385.png?resize=700%2C400&ssl=1 2x, https:\/\/i0.wp.com\/gantovnik.com\/bio-tips\/wp-content\/uploads\/2023\/08\/ex385.png?resize=1050%2C600&ssl=1 3x"},"classes":[]}],"_links":{"self":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts\/1936","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/comments?post=1936"}],"version-history":[{"count":0,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/posts\/1936\/revisions"}],"wp:attachment":[{"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/media?parent=1936"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/categories?post=1936"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/gantovnik.com\/bio-tips\/wp-json\/wp\/v2\/tags?post=1936"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}