{"id":9997,"date":"2023-11-08T03:22:13","date_gmt":"2023-11-08T03:22:13","guid":{"rendered":"https:\/\/support.divominer.com\/en\/docs\/divominer-user-manual\/statistical-analysis\/biaxial-graph\/"},"modified":"2025-12-19T09:45:06","modified_gmt":"2025-12-19T09:45:06","slug":"biaxial-graph","status":"publish","type":"docs","link":"https:\/\/support.divominer.com\/en\/docs\/divominer-user-manual\/statistical-analysis\/biaxial-graph\/","title":{"rendered":"Biaxial Chart"},"content":{"rendered":"\n<p>When there is a significant difference between two sets of data, it can be challenging to clearly visualize the small values on a chart. In this case, a biaxial chart can be used. A biaxial chart refers to a data chart with multiple (\u22652) Y-axes, often combining bar and line graphs, resulting in a more intuitive representation. Apart from being suitable for analyzing two significantly different sets of data, biaxial charts are also ideal in scenarios involving different data trends and analysis of data on a month-to-month or year-on-year basis.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"1022\" height=\"496\" src=\"https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2023\/11\/Snipaste_2023-11-08_11-25-00-1024x550-1.png\" alt=\"\" class=\"wp-image-10060\" srcset=\"https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2023\/11\/Snipaste_2023-11-08_11-25-00-1024x550-1.png 1022w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2023\/11\/Snipaste_2023-11-08_11-25-00-1024x550-1-300x146.png 300w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2023\/11\/Snipaste_2023-11-08_11-25-00-1024x550-1-768x373.png 768w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2023\/11\/Snipaste_2023-11-08_11-25-00-1024x550-1-50x24.png 50w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2023\/11\/Snipaste_2023-11-08_11-25-00-1024x550-1-920x446.png 920w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2023\/11\/Snipaste_2023-11-08_11-25-00-1024x550-1-600x291.png 600w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2023\/11\/Snipaste_2023-11-08_11-25-00-1024x550-1-320x155.png 320w\" sizes=\"(max-width: 1022px) 100vw, 1022px\" \/><\/figure>\n","protected":false},"featured_media":0,"parent":573,"menu_order":23,"comment_status":"open","ping_status":"closed","template":"","doc_tag":[],"_links":{"self":[{"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/9997"}],"collection":[{"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs"}],"about":[{"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/types\/docs"}],"replies":[{"embeddable":true,"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/comments?post=9997"}],"version-history":[{"count":5,"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/9997\/revisions"}],"predecessor-version":[{"id":10061,"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/9997\/revisions\/10061"}],"up":[{"embeddable":true,"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/573"}],"next":[{"title":"Pie chart","link":"https:\/\/support.divominer.com\/en\/docs\/divominer-user-manual\/statistical-analysis\/pie-chart\/","href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/643"}],"prev":[{"title":"Percentage  area stacked chart","link":"https:\/\/support.divominer.com\/en\/docs\/divominer-user-manual\/statistical-analysis\/percentage-area-stacked-chart\/","href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/641"}],"wp:attachment":[{"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/media?parent=9997"}],"wp:term":[{"taxonomy":"doc_tag","embeddable":true,"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/doc_tag?post=9997"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}