A KeyError is a dictionary lookup that missed: the code asked for data["name"] and the dictionary has no key "name". The key in the message is printed in quotes, so KeyError: ‘name’ tells you exactly which key failed. The fix is always about reconciling what the code expects with what the dictionary actually holds.
print(data.keys()). Nine times out of ten the expected key differs in case ("Name"), spelling, or is nested one level deeper than assumed (data["user"]["name"]).data.get("name") returns None instead of raising; data.get("name", "Unknown") supplies a default. Reserve hard [] lookups for keys that must exist.df.columns.tolist() and compare exactly, including stray spaces some CSVs carry.If the key exists in your printout but the error persists, you’re probably looking at two different dictionaries — a copy made earlier, before the key was added. Print the full object at the failing line to see the one the code actually has.
What’s the difference between KeyError and IndexError? Same idea, different container: KeyError is a missing dictionary key; IndexError is a list position that doesn’t exist.
Should I wrap lookups in try/except KeyError? When absence is an expected case (user input, optional API fields), .get() with a default is cleaner. try/except fits when the whole block should be skipped on a miss.