I have a pandas DataFrame that looks like this:
╔═══╦════════════╦═════════════╗
║ ║ VENDOR ID ║ DATE ║
╠═══╬════════════╬═════════════╣
║ 1 ║ 33
I get a bit different output:
df['DATE'] = pd.to_datetime(df['DATE'])
df['GAP'] = df.groupby('VENDOR ID')['DATE'].diff().dt.days
print (df)
VENDOR ID DATE GAP
1 33 2018-01-12 NaN
2 33 2018-03-12 59.0
3 12 2018-01-08 NaN
4 12 2018-01-15 7.0
5 12 2018-01-23 8.0
6 33 2018-05-12 61.0
7 89 2018-01-12 NaN
Explanation:
timedeltas
s to days