Given a 2D list, write a Python program to find the most common element in each column of the 2D list.

**Examples:**

Input :[[1, 1, 3], [2, 3, 3], [3, 2, 2], [2, 1, 3]]Output :[2, 1, 3]Input :[['y', 'y'], ['y', 'x'], ['x', 'x']]Output :['y', 'x']

**Method #1 :** Using *most_common()* from *collections* module

*most_common()* return a list of the *n* most common elements and their counts from the most common to the least. Thus, we can easily find the most common elements in each column using list comprehension.

`# Python3 program to find most common ` `# element in each column in a 2D list` `from` `collections ` `import` `Counter` ` ` `def` `mostCommon(lst):` ` ` ` ` `return` `[Counter(col).most_common(` `1` `)[` `0` `][` `0` `] ` `for` `col ` `in` `zip` `(` `*` `lst)]` ` ` `# Driver code` `lst ` `=` `[[` `1` `, ` `1` `, ` `3` `],` ` ` `[` `2` `, ` `3` `, ` `3` `],` ` ` `[` `3` `, ` `2` `, ` `2` `],` ` ` `[` `2` `, ` `1` `, ` `3` `]]` `print` `(mostCommon(lst))` |

**Output:**

[2, 1, 3]

**Method #3 :** Using *mode()* from *statistics* module

`# Python3 program to find most common ` `# element in each column in a 2D list` `from` `scipy.stats ` `import` `mode` `import` `numpy as np` ` ` `def` `mostCommon(lst):` ` ` ` ` `val, count ` `=` `mode(lst, axis ` `=` `0` `)` ` ` `return` `val.ravel().tolist()` ` ` `# Driver code` `lst ` `=` `[[` `1` `, ` `1` `, ` `3` `],` ` ` `[` `2` `, ` `3` `, ` `3` `],` ` ` `[` `3` `, ` `2` `, ` `2` `],` ` ` `[` `2` `, ` `1` `, ` `3` `]]` `print` `(mostCommon(lst))` |

**Output:**

[2, 1, 3]

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