How to fix - Overflow in int64 addition

Question

I am trying to calculate future dates by adding a column with number of days df['num_days'] to another column df["sampling_date"] but getting Overflow in int64 addition. Source code-

df['sampling_date']=pd.to_datetime(df['sampling_date'], errors='coerce')
df['future_date'] = df['sampling_date'] + pd.to_timedelta(df['num_days'], unit='D')
df['future_date'] = pd.to_datetime(df['future_date']).dt.strftime('%Y-%m-%d')
df['future_date'] = df['future_date'].astype(np.str)
df['future_date'] = np.where(df['num_days']<=0,0, df['future_date'])

for column df['num_days'], the values are as follows [0, 866, 729, 48357555, 567, 478]

I am trying to run this in unix server. Please help me resolving it.

Answer 1

The issue is this value: 48357555

You can create a simple function as shown below to return NaT if error is thrown:

import numpy as np
import pandas as pd

# Here is an example df
df = pd.DataFrame({
    'sampling_date': ['2022-01-01', '2022-02-01', '2022-03-01', '2022-04-01', '2022-05-01', '2022-06-01'],
    'num_days': [0, 866, 729, 48357555, 567, 478]
})

df['sampling_date'] = pd.to_datetime(df['sampling_date'], errors='coerce')

def calculate_future_date(row):
    try:
        return row['sampling_date'] + pd.to_timedelta(row['num_days'], unit='D')
    except:
        return pd.NaT

# Apply the function to each row
df['future_date'] = df.apply(calculate_future_date, axis=1)
df['future_date'] = np.where(df['num_days'] <= 0, df['sampling_date'], df['future_date'])
df['future_date'] = df['future_date'].dt.strftime('%Y-%m-%d').replace(pd.NaT, '0').astype(str)
print(df)


  sampling_date  num_days future_date
0    2022-01-01         0  2022-01-01
1    2022-02-01       866  2024-06-16
2    2022-03-01       729  2024-02-28
3    2022-04-01  48357555           0
4    2022-05-01       567  2023-11-19
5    2022-06-01       478  2023-09-22