[PYTHON] Somehow I tried using jupyter notebook


Somehow I tried using jupyter notebook


Famous as a tutorial for kaggle Use data from Titanic passengers

The environment construction was based on the following http://qiita.com/mix_dvd/items/29dfb8d47a596b4df36d

Put the required libraries

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

Read csv and plunge into dataframe

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

Display the first 5 lines

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

Put the library required for drawing

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

Count by gender

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

output_10_2.png

If it is less than 16, it is a function that returns the gender otherwise.

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

Add the result of the function to the person column

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

Make sure the person column has been added

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

Draw Pclass (room class, 1st class, 2nd class, 3rd class) layered

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

output_17_2.png

For the time being, I tried using jupyter, but it's convenient It's nice to be able to leave the code and the result together

Let's do the survival analysis of kaggle's Titanic passengers next time.

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