<jupyter_start><jupyter_text>Data Exploration-I<jupyter_code># Questions?
# Size of dataset, N features, missing data, data type, distribution/correlations
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
df = pd.read_csv('data/titanic-train.csv')
type(df)
df.head()
df.info()
df.describe()
df.iloc[3]
df.loc[0:4, 'Ticket']
df['Ticket'].head()
df[['Ticket', 'Embarked']].head()
df[df['Age'] > 70]
df.query("Age > 70")
df[(df['Age'] == 11) & (df['SibSp'] == 5)] 
df[(df.Age == 11) | (df.SibSp == 5)]
df.query('(Age == 11) | (SibSp == 5)')
df.Embarked.unique()
df['Embarked'].unique()
df.sort_values('Age', ascending=False).head()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.2145922746781116, 'fraction_numerical': 0.022889842632331903, 'mean_word_length': 6.291666666666667, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 7, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, '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': '495518', 'license': 'MIT', 'n_tokens_mistral': 307, 'n_tokens_neox': 284, 'n_words': 59, 'path': 'data_exploration1.ipynb', 'repo_name': 'ssozuer/pandas', 'size': '699'}