title: Python Outlier Detection in Customer Sales (preferbly by pyod)
body: <p>I have a big Sales transaction dataset that has multiple customers and each customer buys multiple products. I am struggling to find outliers for each customer and all products at the same time. </p>
  
  <p>Please help. My dataset sample is as below. I am fine with basic methods.
  I have one master dataset and I like to see multiple the result via multiple datasets. Thank you.</p>
  
  <p>Sample Dataset:</p>
  
  <pre><code>   df1 = pd.DataFrame(
          {
              "Customer": [
                  "A0",
                  "A0",
                  "A0",
                  "A0",
                  "A1",
                  "A1",
                  "A1",
                  "A1",
                  "A2",
                  "A2",
                  "A2",
                  "A2",
              ],
              "Date": [1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4,],
              "Eggs": [1, 1, 2, 10, 3, 3, 4, 10, 10, 11, 12, 22],
              "Bread": [66, 10, 20, 11, 3, 3, 4, 10, 44, 11, 12, 22],
          },
      )
  </code></pre>
  
  <p>Result Dataset 1:</p>
  
  <pre><code>result1 = pd.DataFrame(
      {"Customer": ["A0", "A1", "A2",], "Date": [4, 4, 4,], "Eggs": [10, 10, 22],},
  )
  </code></pre>
  
  <p>Result Dataset 2:</p>
  
  <pre><code>result2 = pd.DataFrame(
      {"Customer": ["A0", "A1", "A2",], "Date": [1, 4, 1,], "Bread": [66, 10, 44],},
  )
  </code></pre>