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なんとなくjupyter notebook使ってみた

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kaggleのチュートリアル的として有名な
タイタニック号乗客のデータを使う

環境構築は以下を参考にした
http://qiita.com/mix_dvd/items/29dfb8d47a596b4df36d

必要なライブラリを入れる

import pandas as pd
from pandas import DataFrame,Series
import numpy as np

csv読み込んでデータフレームに突っ込む

titanic_df = pd.read_csv('train.csv')

先頭５行表示

titanic_df.head()

	ssengerId	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

描画に必要なライブラリを入れる

import matplotlib.pyplot as plt
import seaborn as sns
% matplotlib inline

性別でカウント

sns.countplot('Sex',data = titanic_df)

16未満であれば、子供　それ以外は性別を返す関数

def male_female_child(passenger):
    age, sex  = passenger
    if age < 16:
        return 'child'
    else:
        return sex  

関数の結果をperson列に追加

titanic_df['person'] = titanic_df[['Age','Sex']].apply(male_female_child,axis = 1)

person列が追加されていることを確認

titanic_df.head(10)

	ssengerId	Survived	Pclass	Name	Sex	Age	SibSp	Parch	Ticket	Fare	Cabin	Embarked	person
0	1	0	3	Braund, Mr. Owen Harris	male	22.0	1	0	A/5 21171	7.2500	NaN	S	male
1	2	1	1	Cumings, Mrs. John Bradley (Florence Briggs Th...	female	38.0	1	0	PC 17599	71.2833	C85	C	female
2	3	1	3	Heikkinen, Miss. Laina	female	26.0	0	0	STON/O2. 3101282	7.9250	NaN	S	female
3	4	1	1	Futrelle, Mrs. Jacques Heath (Lily May Peel)	female	35.0	1	0	113803	53.1000	C123	S	female
4	5	0	3	Allen, Mr. William Henry	male	35.0	0	0	373450	8.0500	NaN	S	male
5	6	0	3	Moran, Mr. James	male	NaN	0	0	330877	8.4583	NaN	Q	male
6	7	0	1	McCarthy, Mr. Timothy J	male	54.0	0	0	17463	51.8625	E46	S	male
7	8	0	3	Palsson, Master. Gosta Leonard	male	2.0	3	1	349909	21.0750	NaN	S	child
8	9	1	3	Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)	female	27.0	0	2	347742	11.1333	NaN	S	female
9	10	1	2	Nasser, Mrs. Nicholas (Adele Achem)	female	14.0	1	0	237736	30.0708	NaN	C	child

　Pclass(客室のクラス、一等、二等、三等)を層別に描画

sns.countplot('Pclass',data = titanic_df ,hue = 'person')

とりあえず、jupyter使ってみたけど便利
コードと結果が一緒に残せるのがいい

kaggleのタイタニック号乗客の生存分析については次回しっかりやっていこう。