seaborn의 count plot 사용하기

In [1]:
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
In [5]:
import pandas as pd

train = pd.read_csv('data/train.csv')

train
Out[5]:
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked
0 1 0 3 Braund, Mr. Owen Harris male 22.0 1 0 A/5 21171 7.2500 NaN S
1 2 1 1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 0 PC 17599 71.2833 C85 C
2 3 1 3 Heikkinen, Miss. Laina female 26.0 0 0 STON/O2. 3101282 7.9250 NaN S
3 4 1 1 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 0 113803 53.1000 C123 S
4 5 0 3 Allen, Mr. William Henry male 35.0 0 0 373450 8.0500 NaN S
... ... ... ... ... ... ... ... ... ... ... ... ...
886 887 0 2 Montvila, Rev. Juozas male 27.0 0 0 211536 13.0000 NaN S
887 888 1 1 Graham, Miss. Margaret Edith female 19.0 0 0 112053 30.0000 B42 S
888 889 0 3 Johnston, Miss. Catherine Helen "Carrie" female NaN 1 2 W./C. 6607 23.4500 NaN S
889 890 1 1 Behr, Mr. Karl Howell male 26.0 0 0 111369 30.0000 C148 C
890 891 0 3 Dooley, Mr. Patrick male 32.0 0 0 370376 7.7500 NaN Q

891 rows × 12 columns

성별별로 나누어 사망자, 생존자 수 카운트

In [10]:
sns.catplot(data = train, x = 'Survived', hue = 'Sex', kind = 'count')
Out[10]:
<seaborn.axisgrid.FacetGrid at 0x188f81025c8>

Pclass 별로 나누어 사망자, 생존자 수 카운트

In [9]:
sns.catplot(data = train, x = 'Survived', hue = 'Pclass', kind = 'count')
Out[9]:
<seaborn.axisgrid.FacetGrid at 0x188f80a9788>

선착장 별로 나누어 사망자, 생존자 수 카운트

In [11]:
sns.catplot(data = train, x = 'Survived', hue = 'Embarked', kind = 'count')
Out[11]:
<seaborn.axisgrid.FacetGrid at 0x188f81f8f48>

나이 별로 나누어 사망자, 생존자 수 카운트

In [12]:
sns.catplot(data = train, x = 'Survived', hue = 'Age', kind = 'count')
Out[12]:
<seaborn.axisgrid.FacetGrid at 0x188f827bc08>
In [ ]: