Python | Manipulating data using the axis argument in python

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The axis argument

The axis argument is used in pandas to specify whether an operation should be performed along rows or columns of a DataFrame.

In pandas, the axis parameter takes a value of 0 or 'index' to operate along the rows, and a value of 1 or 'columns' to operate along the columns.

For example, let's say you have a DataFrame df with columns 'A', 'B', and 'C' and you want to calculate the sum of each row. To do this, you would use the sum() method along the columns, which means you would set axis=1:

row_sum = df.sum(axis=1)

On the other hand, if you want to calculate the sum of each column, you would set axis=0:

col_sum = df.sum(axis=0)

The axis parameter can also be used with other methods such as mean(), max(), min(), std(), var(), idxmax(), idxmin(), etc.

In addition, axis can be used in conjunction with other pandas functions such as drop(), concat(), merge(), pivot(), pivot_table(), groupby(), and apply() to perform operations along either the rows or columns of a DataFrame, depending on what you want to do.

For example, if you have a DataFrame df with a column 'A' and you want to drop it, you can use drop() along the columns by setting axis=1:

df = df.drop('A', axis=1)

In summary, the axis argument is an important parameter in pandas that controls whether an operation is performed along rows or columns of a DataFrame, and it is used in conjunction with many pandas methods and functions.