Pandas subtract dates to get a surgery patient length of stay - pandas

Question

I have a dataframe of surgical activity with admission dates (ADMIDATE) and discharge dates (DISDATE). It is 600k rows by 78 columns but I have filtered it for a particular surgery. I want to calculate the length of stay and add it as a further column.
Usually I use
df["los"] = (df["DISDATE"] - df["ADMIDATE"]).dt.days
I recently had to clean the data and must have done it in a different way to previously because I am now getting a negative los, eg.
DISDATE.
. ADMIDATE.
. los.
2019-12-24
2019-12-08
-43805.
2019-05-15
. 2019-03-26
50.
2019-10-11
. 2019-10-07
4.
2019-06-20
2019-06-16
4
2019-04-11
2019-04-08
3
df.info()
df.info()
<class '`pandas`.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 78 columns):
5 ADMIDATE 5 non-null datetime64[ns]
28 DISDATE 5 non-null datetime64[ns]
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 78 columns):
5 ADMIDATE 5 non-null datetime64[ns]
28 DISDATE 5 non-null datetime64[ns]
I am not sure how to ask the right questions to the problem, - and why its only affecting some rows. In cleansing the data some of the DISDATES had to be populated from another column (also a date column) becuase they were incomplete, and I wonder if it is these which are negative due to some retention of the orig data soemhow even though printing the new DISDATE looks ok.

Answer 1

Your sample works well with the right output (16 days for the first row)
Can you try that and check if the problem persists:
import io
data = df[['DISDATE', 'ADMIDATE']].to_csv()
test = pd.read_csv(io.StringIO(data), index_col=0,
parse_dates=['DISDATE', 'ADMIDATE'])
print(test['DISDATE'].sub(test['ADMIDATE']).dt.days)
Output:
0 16
1 50
2 4
3 4
4 3
dtype: int64
Update
To debug your bad dates, try:
df.loc[pd.to_datetime(df['ADMIDATE'], errors='coerce').isna(), 'ADMIDATE']
You should see rows where values are not a right date.