How is .iloc different from .loc?

.iloc and .loc are both accessors used in pandas for selecting data from a DataFrame, but they differ in how they reference the data:

1. .iloc:

   • Primarily integer-based indexing.
   • Uses integer positions to select rows and columns.
   • Syntax: df.iloc[row_index, column_index]
   • Example: df.iloc[0:5, 1:3] selects the first 5 rows and the 2nd and 3rd columns.

2. .loc:

   • Label-based indexing.
   • Uses the actual labels of the rows and columns to select data.
   • Syntax: df.loc[row_label, column_label]
   • Example: df.loc[0:4, 'Column1':'Column3'] selects rows with labels from 0 to 4 and columns from 'Column1' to 'Column3'.

In summary, use .iloc for positional indexing and .loc for label-based indexing.