<jupyter_start><jupyter_text>[Titanic Data Set](https://www.kaggle.com/c/titanic/data)   Data Set Information:The titanic data frame describes the survival status of individual passengers on the Titanic.The titanic data frame does not contain information for the crew, but it does contain actual and estimated ages for almost 80% of the passengers. Sources:Hind, Philip. Encyclopedia Titanica. Online-only resource. Retrieved 01Feb2012 fromhttp://www.encyclopedia-titanica.org/ Attribute Information:survival:    Survival PassengerId: Unique Id of a passenger. pclass:    Ticket class     sex:    Sex     Age:    Age in years     sibsp:     of siblings / spouses aboard the Titanic     parch:     of parents / children aboard the Titanic     ticket:    Ticket number     fare:    Passenger fare     cabin:    Cabin number     embarked:    Port of Embarkationtrain_df.describe()  Exploratory data analysis<jupyter_code>import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
# Getting the Data
df = pd.read_csv("../datasets/titanic/train.csv")
df.head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.06702412868632708, 'fraction_numerical': 0.0071492403932082215, 'mean_word_length': 4.0, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 1, 'lorem ipsum': 0, 'www.': 2, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '589609', 'license': 'CC0-1.0', 'n_tokens_mistral': 340, 'n_tokens_neox': 316, 'n_words': 121, 'path': 'ejercicios/titanic_dataset.ipynb', 'repo_name': 'aliciapj/intro_ml_python', 'size': '1119'}