按指定外部月份顺序排序Pandas DataFrame行遇问题求助

Hey there! Let's work through this sorting issue with your nudf DataFrame together— I’ve run into similar headaches before, so let’s break it down step by step.

First, let’s rule out the most common culprits that mess up DataFrame sorting:

1. Make sure your date column is actually a datetime type #

Looking at your sample data, the date column looks like timestamps, but if it’s stored as a string (object dtype in pandas), sorting will use lexicographical order instead of chronological order— that’s a super common gotcha.

First check the dtype:

print(nudf['date'].dtype)

If it returns object, convert it to a proper datetime type (and handle that invalid 2017-09-31 date while we’re at it— September only has 30 days!):

nudf['date'] = pd.to_datetime(nudf['date'], errors='coerce')

The errors='coerce' flag turns invalid dates into NaT (Not a Time), which we can clean up later.

2. Verify your level_1 column is numeric #

Same idea— if level_1 is stored as a string instead of int/float, sorting won’t behave like you expect. Check its dtype:

print(nudf['level_1'].dtype)

If it’s object, convert to numeric:

nudf['level_1'] = pd.to_numeric(nudf['level_1'], errors='coerce')

3. Run the correct sorting command #

Once your columns are properly typed, sorting should work as expected. To sort by date ascending (oldest to newest):

nudf_sorted = nudf.sort_values(by='date', ascending=True)

If you want to sort by date first, then level_1:

nudf_sorted = nudf.sort_values(by=['date', 'level_1'], ascending=[True, True])

If you want to modify the original DataFrame instead of creating a new one, add inplace=True:

nudf.sort_values(by='date', ascending=True, inplace=True)

4. Clean up invalid dates (like 2017-09-31) #

That invalid September 31st date got turned into NaT earlier. If you don’t want those rows cluttering up your sorted data, drop them:

nudf = nudf.dropna(subset=['date'])

Double-check your results #

Finally, confirm the sorting worked by peeking at the first and last rows:

print(nudf_sorted.head())
print(nudf_sorted.tail())

内容的提问来源于stack exchange，提问作者Darkstarone