title: merging train and test datasets into one using tensorflow
body: <p>I am working with the classic titanic dataset and trying to apply NNs. My data comes already split into train and dev sets. However, I want to merge the datasets together for many things (for example, my own splitting, etc..)</p>
  <p>Is there a way I can merge both datasets?
  I have looked around and only found information about how to split a dataset, but I was unable to find how to merge them back together.
  Any help?</p>
  <p>A MWE is provided below!</p>
  <pre><code>from __future__ import absolute_import,division,print_function,unicode_literals
  import numpy as np 
  import pandas as pd
  import matplotlib
  import matplotlib.pyplot as plt
  %matplotlib inline
  
  from IPython.display import clear_output
  from six.moves import urllib
  import tensorflow.compat.v2.feature_column as fc 
  import tensorflow as tf 
  import seaborn as sns
  
  # URL address of data
  TRAIN_DATA_URL = &quot;https://storage.googleapis.com/tf-datasets/titanic/train.csv&quot;
  TEST_DATA_URL = &quot;https://storage.googleapis.com/tf-datasets/titanic/eval.csv&quot;
  
  # Downloading data
  train_file_path = tf.keras.utils.get_file(&quot;train.csv&quot;, TRAIN_DATA_URL)
  test_file_path  = tf.keras.utils.get_file(&quot;eval.csv&quot;, TEST_DATA_URL)
  # Reading data
  data_train = pd.read_csv(train_file_path)
  data_test  = pd.read_csv(test_file_path)
  
  MY_DATA= MERGE HERE????? # merge(data_train,data_test)??
  
  </code></pre>