Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error **cannot convert the series to** **<class ‘int’`**> **in python**. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

Table of Contents

## How cannot convert the series to <class ‘int’`> Error Occurs?

Today I get the following error **cannot convert the series to** **<class ‘int’`**> **in python**.

## How To Solve cannot convert the series to <class ‘int’`> Error ?

**How To Solve cannot convert the series to**Error ? To Solve cannot convert the series to <class 'int'`> Error Your error is line 2.

`df['intage'] = int(df['age'])`

is not valid, you can't pass a pandas series to the int function.**cannot convert the series to**To Solve cannot convert the series to <class 'int'`> Error Your error is line 2.

`df['intage'] = int(df['age'])`

is not valid, you can't pass a pandas series to the int function.

## Solution 1

Your error is line 2. `df['intage'] = int(df['age'])`

is not valid, you can’t pass a pandas series to the int function.

You need to use `astype`

if df[‘age’] is object dtype.

df['intage'] = df['age'].astype(int)

Or since you are subtracting two dates, you need to use dt accessor with the days attribute to get the number of days as an integer

df['intage'] = df['age'].dt.days

## Solution 2

Since the `dtype`

is `timedelta64[ns]`

you can either use between, specifying two `timedeltas`

as the endpoints, or you can first convert the days to a numeric type using `numpy`

.

### Setup

import pandas as pd import numpy as np df = pd.DataFrame({'age': [83, 108, 83, 63, 81]}) df['age'] = pd.to_timedelta(df.age, unit='days')

Find those between 82 and 107 days:

df[df.age.between(pd.to_timedelta(82, unit='days'), pd.to_timedelta(107, unit='days'))] # age #0 83 days #2 83 days

With `numpy`

df[(df.age/np.timedelta64(1, 'D')).between(82, 107)] # age #0 83 days #2 83 days

**Summery**

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

**Also, Read**