answer:To factorize the expression x^{2}-9x, we look for common factors in each term. 1. Identify the common factor: Both terms x^{2} and -9x have x as a common factor. 2. Factor out the common factor: We take x out of each term, which gives us x(x-9). Therefore, the factorized form of x^{2}-9x is boxed{x(x-9)}.

answer:<tool_call>[{name: get_dna_sequence, arguments: {sequence_id: NM_001001366, file_format: fasta, upstream_bases: 100}}]</tool_call>

answer:Recall that csc x = frac{1}{sin x}. We know that sin 225^circ = -sin (225^circ - 180^circ) = -sin 45^circ = -frac{1}{sqrt{2}}. Therefore, csc 225^circ = frac{1}{sin 225^circ} = frac{1}{-frac{1}{sqrt{2}}} = boxed{-sqrt{2}}.The answer is: -sqrt{2}

answer:The issue is that you're trying to modify the DataFrame (`df`) while iterating over it using `iterrows()`. This is not allowed because `iterrows()` returns an iterator over the rows of the DataFrame, and modifying the DataFrame would invalidate the iterator. A better approach is to create a list of indices to drop and then drop them after the iteration is complete. Here's an alternative: ```python import pandas as pd df = pd.read_csv(data.csv) indices_to_drop = [] for index, row in df.iterrows(): if row['column_a'] == row['column_b']: indices_to_drop.append(index) df.drop(indices_to_drop, inplace=True) ``` However, a more idiomatic and efficient way to achieve the same result is to use boolean indexing: ```python df = df[df['column_a'] != df['column_b']] ``` This will create a new DataFrame that excludes the rows where `column_a` equals `column_b`. Note that this approach does not modify the original DataFrame, but instead returns a new one. If you want to modify the original DataFrame, you can assign the result back to `df`.