How to implement guide with multiindex dataframe slicing - advanced patterns while filtering rows
I'm trying to implement I'm writing unit tests and I'm stuck on something that should probably be simple... Hey everyone, I'm running into an issue that's driving me crazy. I'm working with a strange scenario while trying to slice a MultiIndex DataFrame in pandas. I have a DataFrame with a MultiIndex containing two levels: 'Category' and 'Subcategory'. After performing some operations, I'm attempting to filter rows based on the 'Subcategory' level, but the results are not what I expected. Here's the relevant part of my code: ```python import pandas as pd # Sample MultiIndex DataFrame arrays = [ ['Fruits', 'Fruits', 'Vegetables', 'Vegetables'], ['Apples', 'Oranges', 'Carrots', 'Lettuce'] ] index = pd.MultiIndex.from_arrays(arrays, names=('Category', 'Subcategory')) data = { 'Sales': [100, 150, 200, 250] } df = pd.DataFrame(data, index=index) # Attempting to filter using .loc filtered = df.loc[(slice(None), 'Apples')] print(filtered) ``` I expected to get a DataFrame with only the sales data for 'Apples', but instead, I receive an empty DataFrame: ``` Empty DataFrame Columns: [Sales] Index: [] ``` I've tried using different approaches, including: - Using `df.xs('Apples', level='Subcategory')`, but that also returns an empty DataFrame. - Checking my index levels with `df.index.levels` to confirm that 'Apples' is indeed part of the 'Subcategory' level. When I run `print(df.index)`, I see: ``` MultiIndex([('Fruits', 'Apples'), ('Fruits', 'Oranges'), ('Vegetables', 'Carrots'), ('Vegetables', 'Lettuce')], names=['Category', 'Subcategory']) ``` This confirms that 'Apples' exists, so I'm puzzled why my filtering isn't working. I am using pandas version 1.4.2. Could someone please guide to understand what I'm doing wrong here and how to properly filter the DataFrame? Any insights would be greatly appreciated! This is part of a larger API I'm building. For context: I'm using Python on Ubuntu. How would you solve this? Cheers for any assistance! I'd be grateful for any help.