Here is the code I have so far:
import pandas as pd
df = pd.read_csv('/content/drive/MyDrive/Colab Datasets/KickstarterRevised.csv')
df['deadline'] = pd.to_datetime(df['deadline'])
df['launched'] = pd.to_datetime(df['launched'])
df['difference'] = df['deadline'].sub(df['launched'], axis=0)
df['difference']
0 58 days 23:24:00
1 45 days 00:00:00
2 30 days 01:00:00
3 55 days 16:25:00
4 35 days 00:00:00
...
4994 40 days 00:00:00
4995 8 days 10:50:00
4996 38 days 18:53:00
4997 30 days 00:00:00
4998 30 days 00:00:00
Name: difference, Length: 4999, dtype: timedelta64[ns]
CodePudding user response:
As you see from your code, df['difference']
is a Series with dtype: timedelta64[ns]
. To get the days, just use .astype("timedelta64[D]")
, see below
df['difference'] = df['deadline'].sub(df['launched'], axis=0).astype('timedelta64[D]')