application_vnd.jupyter.stderr_output_1.png
import os

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import seaborn as sns

import numpy as np
import pandas as pd
import seaborn as sns
import os
train_data = pd.read_csv('../input/train.csv')
test_data = pd.read_csv('../input/test.csv')

Survials_By_Age = train_data.groupby('Age')['Survived'].sum().reset_index()
Survials_By_Age_Segment = []
age_difference = 5
max_age = 70
for i in range(max_age // age_difference):
    s = Survials_By_Age.loc['Age', i * age_difference:(i + 1) * age_difference]['Survived'].sum()
    Survials_By_Age_Segment.append(s)

boolean_Survivals = train_data['Survived'] == 1
Survivals = train_data[boolean_Survivals]
sns.barplot(y='title', x='average_rating', data=ayu)