{"id":3469,"date":"2026-06-10T10:29:30","date_gmt":"2026-06-10T10:29:30","guid":{"rendered":"https:\/\/www.mhtechin.com\/support\/?p=3469"},"modified":"2026-06-10T10:29:30","modified_gmt":"2026-06-10T10:29:30","slug":"how-box-plot-works","status":"publish","type":"post","link":"https:\/\/www.mhtechin.com\/support\/how-box-plot-works\/","title":{"rendered":"How Box Plot Works"},"content":{"rendered":"\n

How Box Plot<\/strong> Works<\/h2>\n\n\n\n

A Box Plot<\/strong> (or Box-and-Whisker Plot) is used to summarize the distribution of numerical data and detect outliers.<\/p>\n\n\n\n

Components of a Box Plot<\/h3>\n\n\n\n
Component<\/th>Meaning<\/th><\/tr><\/thead>
Minimum<\/strong><\/td>Smallest value (excluding outliers)<\/td><\/tr>
Q1 (First Quartile)<\/strong><\/td>25% of the data lies below this value<\/td><\/tr>
Median (Q2)<\/strong><\/td>Middle value (50th percentile)<\/td><\/tr>
Q3 (Third Quartile)<\/strong><\/td>75% of the data lies below this value<\/td><\/tr>
Maximum<\/strong><\/td>Largest value (excluding outliers)<\/td><\/tr>
Outliers<\/strong><\/td>Unusually high or low values shown as separate points<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Example<\/h3>\n\n\n\n

Dataset:<\/p>\n\n\n\n

10, 12, 15, 18, 20, 22, 25, 28, 30, 60<\/code><\/pre>\n\n\n\n
Statistic<\/th>Value<\/th><\/tr><\/thead>
Minimum<\/td>10<\/td><\/tr>
Q1<\/td>15<\/td><\/tr>
Median<\/td>21<\/td><\/tr>
Q3<\/td>28<\/td><\/tr>
Maximum<\/td>30<\/td><\/tr>
Outlier<\/td>60<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
How it works<\/h3>\n\n\n\n
    \n
  1. Sort the data.<\/li>\n\n\n\n
  2. Find the median.<\/li>\n\n\n\n
  3. Find Q1 and Q3.<\/li>\n\n\n\n
  4. Draw a box from Q1 to Q3.<\/li>\n\n\n\n
  5. Draw a line inside the box for the median.<\/li>\n\n\n\n
  6. Extend “whiskers” to the minimum and maximum non-outlier values.<\/li>\n\n\n\n
  7. Plot any outliers as separate points.<\/li>\n<\/ol>\n\n\n\n
    Uses:<\/strong><\/p>\n\n\n\n
      \n
    • Detecting outliers<\/li>\n\n\n\n
    • Comparing distributions<\/li>\n\n\n\n
    • Understanding spread and central tendency<\/li>\n<\/ul>\n\n\n\n
      \n\n\n\n
      How Heatmap<\/strong> Works<\/h1>\n\n\n\n
      A Heatmap<\/strong> displays values using colors. Larger or stronger values are shown with one color intensity, while smaller values are shown with another.<\/p>\n\n\n\n
      Example: Correlation Matrix<\/h3>\n\n\n\n
      Variable<\/th>Age<\/th>Salary<\/th>Experience<\/th><\/tr><\/thead>
      Age<\/strong><\/td>1.00<\/td>0.72<\/td>0.81<\/td><\/tr>
      Salary<\/strong><\/td>0.72<\/td>1.00<\/td>0.89<\/td><\/tr>
      Experience<\/strong><\/td>0.81<\/td>0.89<\/td>1.00<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      In a heatmap:<\/p>\n\n\n\n
        \n
      • Dark\/strong color<\/strong> \u2192 High value or strong correlation<\/li>\n\n\n\n
      • Light color<\/strong> \u2192 Low value or weak correlation<\/li>\n<\/ul>\n\n\n\n
        How it works<\/h3>\n\n\n\n
          \n
        1. Arrange data into a matrix (rows and columns).<\/li>\n\n\n\n
        2. Each cell contains a numerical value.<\/li>\n\n\n\n
        3. Seaborn maps each value to a color based on a color scale.<\/li>\n\n\n\n
        4. Similar values appear with similar colors, making patterns easy to spot.<\/li>\n<\/ol>\n\n\n\n
          Real-life uses<\/h3>\n\n\n\n
          Field<\/th>Example<\/th><\/tr><\/thead>
          Data Science<\/td>Feature correlation analysis<\/td><\/tr>
          Finance<\/td>Stock correlation matrix<\/td><\/tr>
          Education<\/td>Student performance analysis<\/td><\/tr>
          Healthcare<\/td>Disease occurrence by region<\/td><\/tr>
          Business<\/td>Sales performance across products and months<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
          Difference between Box Plot and Heatmap<\/h3>\n\n\n\n
          Box Plot<\/th>Heatmap<\/th><\/tr><\/thead>
          Shows distribution of one numerical variable<\/td>Shows values in a matrix using colors<\/td><\/tr>
          Detects outliers<\/td>Detects patterns and correlations<\/td><\/tr>
          Uses quartiles and median<\/td>Uses color intensity<\/td><\/tr>
          Best for comparing distributions<\/td>Best for comparing many variables simultaneously<\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"
          How Box Plot Works A Box Plot (or Box-and-Whisker Plot) is used to summarize the distribution of numerical data and detect outliers. Components of a Box Plot Component Meaning Minimum Smallest value (excluding outliers) Q1 (First Quartile) 25% of the data lies below this value Median (Q2) Middle value (50th percentile) Q3 (Third Quartile) 75% […]<\/p>\n","protected":false},"author":73,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-3469","post","type-post","status-publish","format-standard","hentry","category-support"],"_links":{"self":[{"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/posts\/3469","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/users\/73"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/comments?post=3469"}],"version-history":[{"count":1,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/posts\/3469\/revisions"}],"predecessor-version":[{"id":3470,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/posts\/3469\/revisions\/3470"}],"wp:attachment":[{"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/media?parent=3469"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/categories?post=3469"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.mhtechin.com\/support\/wp-json\/wp\/v2\/tags?post=3469"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}