Here’s the rules, subsequent override: All operations generate a copy If inplace=True is provided, it will modify in-place; only some operations support this An indexer that sets, e.g. .loc/.iloc/.iat/.at will set inplace. An indexer that gets on a single-dtyped object is almost always a view (depending on the memory layout it may not be that’s … Read more
This expands on Paul’s answer. In Pandas, indexing a DataFrame returns a reference to the initial DataFrame. Thus, changing the subset will change the initial DataFrame. Thus, you’d want to use the copy if you want to make sure the initial DataFrame shouldn’t change. Consider the following code: df = DataFrame({‘x’: [1,2]}) df_sub = df[0:1] … Read more
How to add a new column to an existing DataFrame?
The SettingWithCopyWarning was created to flag potentially confusing “chained” assignments, such as the following, which does not always work as expected, particularly when the first selection returns a copy. [see GH5390 and GH5597 for background discussion.] df[df[‘A’] > 2][‘B’] = new_val # new_val not set in df The warning offers a suggestion to rewrite as … Read more