Dataset to pandas dataframe and back to dataset

Beginners
1

I have code as below. I am converting a dataset to a dataframe and then back to dataset. I am repeating the process once with shuffled data and once with unshuffled data. When I compare data in case of shuffled data, I get false. But when I compare data in case of unshuffled data, I get True. Why is there this kind of discrepancy

import pandas as pd

import datasets





import numpy as np



import os

train_data, test_data = datasets.load_dataset('imdb', split =['train', 'test'], 

                                             cache_dir='/media/data_files/github/website_tutorials/data')

train_data_s1, test_data_s1 = datasets.load_dataset('imdb', split =['train[0:500]', 'test[0:500]'], 

                                             cache_dir='/media/data_files/github/website_tutorials/data')

print (type (train_data_s1))

print (type (test_data_s1))

#shuffling adn taking first 500 from train_data and test_data

# Create a list in a range of 10-20

l1=[*range(0,499,1)]

  

# Print the list

print(l1)

train_data_s1_shuffled=train_data.shuffle(seed=2).select(l1)

test_data_s1_shuffled=test_data.shuffle(seed=3).select(l1)

print (type (train_data_s1_shuffled))

print (type (test_data_s1_shuffled))

Why do i get False below when I compare data but in the next block I get True

from datasets import Dataset

import pandas as pd

#dataset_from_pandas = Dataset.from_pandas(df_pandas)

#https://discuss.huggingface.co/t/how-to-create-custom-classlabels/13650# "basic_sentiment holds values [-1,0,1]

from datasets import ClassLabel

x1=pd.DataFrame(train_data_s1_shuffled)

x2=Dataset.from_pandas(x1).cast_column("label", ClassLabel(num_classes=2, names=['neg', 'pos'], names_file=None, id=None))

print (x2.data==train_data_s1_shuffled.data)#returns false

print (x2.features==train_data_s1_shuffled.features)

#not sure why data matches in this case but not in earlier case?

x11=pd.DataFrame(train_data)

#print (x11.head())

x21=Dataset.from_pandas(x11).cast_column("label", ClassLabel(num_classes=2, names=['neg', 'pos'], names_file=None, id=None))

print (x21.data==train_data.data)

print (x21.features==train_data.features)