What's the [0] at the end is for?

Currently I’m learning and working with pandas DataFrame and had to solve a problem where I need to fill the NaN values with mode with respective series, this is working but I can’t figure out what’s the [0] at the end is for. Also is it possible to perform same on the whole DataFrame in one go?

df[‘col1’] = df[‘col1’].fillna(df[‘col1’].mode()[0])

import pandas as pd
import numpy as np
data = {'birds': ['Cranes', 'Cranes', 'plovers', 'spoonbills', 'spoonbills', 'Cranes', 'plovers', 'Cranes', 'spoonbills', 'spoonbills', 'Cranes'], 
        'age': [3.5, 4, 1.5, np.nan, 6, 3, 5.5, np.nan, 8, 4, 3.5], 'visits': [2, 4, 3, 4, 3, 4, 2, 2, 3, 2, 2], 
        'priority': ['yes', 'yes', 'no', np.nan, 'no', 'no', 'no', 'yes', 'no', 'no','yes']}
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k']
df = pd.DataFrame(data)
df.rename(index = {0:'a', 1:'b', 2:'c', 3:'d', 4:'e', 5:'f', 6:'g', 7:'h', 8:'i', 9:'j', 10:'k'})
df.iloc[::2]

**df['age'] = df['age'].fillna(df['age'].mode()[0])
df**

>Solution :

mode() returns a Series (a type of pandas DataFrame), not a single value. This is because there can technically be multiple modes in a dataset. By indexing with [0], you are selecting the first mode in the dataset.

Also, for doing this for the whole dataset you can use:

df = df.apply(lambda x: x.fillna(x.mode()[0]) if x.dtype.name == 'object' else x)