implementing MultiIndex DataFrame Column Renaming and Data Loss in Pandas 1.5.3
I'm migrating some code and I'm experimenting with I'm maintaining legacy code that I'm having trouble with I've been struggling with this for a few days now and could really use some help..... I'm stuck on something that should probably be simple. I'm currently working with a scenario with renaming columns in a MultiIndex DataFrame using Pandas version 1.5.3. I have a DataFrame structured like this: ```python import pandas as pd arrays = [["A", "A", "B", "B"], ["one", "two", "one", "two"]] index = pd.MultiIndex.from_arrays(arrays, names=("letters", "numbers")) df = pd.DataFrame({"value": [1, 2, 3, 4]}, index=index) print(df) ``` This produces the following output: ``` value letters numbers A one 1 two 2 B one 3 two 4 ``` I want to rename the inner index from `one` to `first` and `two` to `second`. I used the following code: ```python df.rename(index={('A', 'one'): ('A', 'first'), ('A', 'two'): ('A', 'second')}, level=[0, 1], inplace=True) ``` However, when I run this, I get a `KeyError` indicating that the keys I provided for renaming do not exist. I did verify that the keys are indeed present in the DataFrame. Additionally, I noticed that after attempting the rename, some of the data seems to be lost; accessing `df.loc['A']` returns a DataFrame without any entries. Is there a more reliable way of renaming the levels of a MultiIndex and ensuring that data integrity is maintained? I've tried using `set_names` as well, but it did not yield the expected results. Any guidance would be appreciated! For context: I'm using Python on Windows. Am I missing something obvious? How would you solve this? Thanks, I really appreciate it! The stack includes Python and several other technologies. I appreciate any insights! Has anyone dealt with something similar? What would be the recommended way to handle this?