<jupyter_start><jupyter_text>This is how you drop columns you dont need.Dropping PassengerId, Name and ticket for now.But there may be useful information there.<jupyter_code>trainset = trainset.drop(['PassengerId','Name','Ticket'],axis=1)
trainset.info()
trainset.describe()
trainset.Embarked = trainset.Embarked.fillna("S")

sns.factorplot('Embarked','Survived', data=trainset,size=4,aspect=3)
fig, (axis1,axis2,axis3) = plt.subplots(1,3,figsize=(15,5))
sns.countplot(x='Embarked', data=trainset, ax=axis1)
sns.countplot(x='Survived', hue="Embarked", data=trainset, order=[1,0], ax=axis2)

# group by embarked, and get the mean for survived passengers for each value in Embarked

embark_perc = trainset[["Embarked", "Survived"]].groupby(['Embarked'],as_index=False).mean()
sns.barplot(x='Embarked', y='Survived', data=embark_perc,order=['S','C','Q'],ax=axis3)<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '242036', 'license': 'MIT', 'n_tokens_mistral': 342, 'n_tokens_neox': 335, 'n_words': 60, 'path': 'Titanic/Saving Jack.ipynb', 'repo_name': 'srungta/deep-learning-scripts-by-a-beginner', 'size': '890'}