When using the
iloc function in Pandas, there are some common mistakes that people often make. Here are a few examples along with code samples to illustrate these mistakes:
1. Misusing `iloc` with incorrect index positions:
In the below example, the code attempts to use
iloc with index position 3 to select a row. However, the valid index positions in the DataFrame are 0, 1, and 2. This will result in an
IndexError because there is no row at index position 3.
To correct this mistake, you should use the appropriate index positions based on the DataFrame’s size.
2. Mixing up row and column index positions:
In the above example, the code attempts to use
iloc with row index position 0 and column label ‘Age’ to select a specific value. However,
iloc expects integer-based index positions for both rows and columns.
To correct this mistake, you should use integer-based index positions for both rows and columns.
3. Using a single integer instead of a list or array-like object:
Another mistake is passing a single integer to
iloc instead of a list or array-like object.
iloc expects a sequence of integers for indexing multiple rows or columns. Here’s an example: