I have this dataframe:

    age 
0   48  
1   7   
2   62 
3   48 
4   51

This code:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.read_csv("df2.csv",header=0,sep=",")
def normalizar(x):
  # Convert x to a numpy array to allow for vectorized operations.
  x = np.array(x)
  # Calculate the minimum and maximum values of x.
  xmin = x.min()
  xmax = x.max()
  # Normalize the array x using vectorized operations.
  return (x - xmin) / (xmax - xmin)
df["age_n"]=df["age"].apply(normalizar)
df

and I get:

    age     age_n
0   48  NaN
1   7   NaN
2   62  NaN
3   48  NaN
4   51  NaN 

How can I solve this issue?

The expected result would be values between [0,1]