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 iloc with loc:
In the example below, 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 and loc uses label-based positions.
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: