2주차 Day09 Flask와 EDA chap2

 

In [2]:

                                
                                # 라이브러리 불러오기

                                import
                                numpy
                                as
                                np
                                import
                                pandas
                                as
                                pd
                                import
                                matplotlib.pyplot
                                as
                                plt
                                import
                                seaborn
                                as
                                sns

                                %
                                matplotlib
                                 inline
                            

In [3]:

                                
                                # 데이터 불러오기

                                titanic_df
                                =
                                pd
                                .
                                read_csv
                                (
                                "./train.csv"
                                )
                                titanic_df
                            

Out[3]:

	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

 

3. 데이터 개별 속성 파악하기 ¶

 

I.Survived Column ¶

In [5]:

                                
                                # 생존자, 사망자 명수는?

                                titanic_df
                                [
                                'Survived'
                                ]
                                .
                                head
                                (
                                5
                                )
                            

Out[5]:

0    0
                        1    1
                        2    1
                        3    1
                        4    0
                        Name: Survived, dtype: int64

In [12]:

                                
                                # 생존자 수
                                titanic_df
                                [
                                'Survived'
                                ]
                                .
                                sum
                                ()
                                # 방법1
                                titanic_df
                                [
                                'Survived'
                                ]
                                .
                                value_counts
                                ()
                                # 방법2
                            

Out[12]:

0    549
                        1    342
                        Name: Survived, dtype: int64

In [14]:

                                
                                ## 생존자수와 사망자수를 Barplot으로 그려보기 sns.countplot()

                                sns
                                .
                                countplot
                                (
                                x
                                =
                                'Survived'
                                ,
                                data
                                =
                                titanic_df
                                )
                                plt
                                .
                                show
                                ()
                            

 

 

II.Pclass ¶

In [23]:

                                
                                # Pclass에 따른 인원파악
                                titanic_df
                                [[
                                'Pclass'
                                ,
                                'Survived'
                                ]]
                                .
                                groupby
                                ([
                                'Pclass'
                                ])
                                .
                                count
                                ()
                            

Out[23]:

	Survived
Pclass
1	216
2	184
3	491

In [29]:

                                
                                # 생존자 인원?

                                titanic_df
                                [[
                                'Pclass'
                                ,
                                'Survived'
                                ]]
                                .
                                groupby
                                ([
                                'Pclass'
                                ])
                                .
                                sum
                                ()
                            

Out[29]:

	Survived
Pclass
1	136
2	87
3	119

In [31]:

                                
                                ## 생존 비율?

                                titanic_df
                                [[
                                'Pclass'
                                ,
                                'Survived'
                                ]]
                                .
                                groupby
                                ([
                                'Pclass'
                                ])
                                .
                                mean
                                ()
                            

Out[31]:

	Survived
Pclass
1	0.629630
2	0.472826
3	0.242363

In [33]:

                                
                                #히트맵 활용

                                sns
                                .
                                heatmap
                                (
                                titanic_df
                                [[
                                'Pclass'
                                ,
                                'Survived'
                                ]]
                                .
                                groupby
                                ([
                                'Pclass'
                                ])
                                .
                                mean
                                ())
                                plt
                                .
                                show
                                ()
                            

 

 

III.Sex ¶

In [41]:

                                
                                titanic_df
                                .
                                groupby
                                ([
                                "Sex"
                                ,
                                "Survived"
                                ])[
                                'Survived'
                                ]
                                .
                                count
                                ()
                            

Out[41]:

Sex     Survived
                        female  0            81
                                1           233
                        male    0           468
                                1           109
                        Name: Survived, dtype: int64

In [42]:

                                
                                # sns.catplot

                                sns
                                .
                                catplot
                                (
                                x
                                =
                                "Sex"
                                ,
                                col
                                =
                                'Survived'
                                ,
                                kind
                                =
                                'count'
                                ,
                                data
                                =
                                titanic_df
                                )
                                plt
                                .
                                show
                                ()
                            

 

 

IV. Age ¶

Remind: 결측치 존재! ¶

In [46]:

                                
                                titanic_df
                                .
                                describe
                                ()[
                                'Age'
                                ]
                            

Out[46]:

count    714.000000
                        mean      29.699118
                        std       14.526497
                        min        0.420000
                        25%       20.125000
                        50%       28.000000
                        75%       38.000000
                        max       80.000000
                        Name: Age, dtype: float64

In [50]:

                                
                                titanic_df
                                [
                                titanic_df
                                .
                                Survived
                                ==
                                1
                                ][
                                'Age'
                                ]
                            

Out[50]:

1      38.0
                        2      26.0
                        3      35.0
                        8      27.0
                        9      14.0
                               ... 
                        875    15.0
                        879    56.0
                        880    25.0
                        887    19.0
                        889    26.0
                        Name: Age, Length: 342, dtype: float64

In [55]:

                                
                                ## Survived 1, 0과 Age의 경향성

                                # figure(어떠한 그래프 도면) -> axis(figure안에 있는 x축 y축 틀) -> plot(그려지는거)

                                fig
                                ,
                                ax
                                =
                                plt
                                .
                                subplots
                                (
                                1
                                ,
                                1
                                ,
                                figsize
                                =
                                (
                                10
                                ,
                                5
                                ))
                                sns
                                .
                                kdeplot
                                (
                                x
                                =
                                titanic_df
                                [
                                titanic_df
                                .
                                Survived
                                ==
                                1
                                ][
                                'Age'
                                ],
                                ax
                                =
                                ax
                                )
                                sns
                                .
                                kdeplot
                                (
                                x
                                =
                                titanic_df
                                [
                                titanic_df
                                .
                                Survived
                                ==
                                0
                                ][
                                'Age'
                                ],
                                ax
                                =
                                ax
                                )
                                plt
                                .
                                legend
                                ([
                                "Survived"
                                ,
                                "Dead"
                                ])
                                plt
                                .
                                show
                                ()
                            

 

 

Appendix I. Sex + Pclass vs Survived ¶

In [58]:

                                
                                # sns.catplot() 복합적인 요소를 분석할 때 많이씀
                                sns
                                .
                                catplot
                                (
                                x
                                =
                                "Pclass"
                                ,
                                y
                                =
                                "Survived"
                                ,
                                hue
                                =
                                "Sex"
                                ,
                                kind
                                =
                                "point"
                                ,
                                data
                                =
                                titanic_df
                                )
                                plt
                                .
                                show
                                ()
                                # 점은 추정치, 막대는 신뢰구간을 나타냄
                            

 

 

Appendix II. Age + Pclass ¶

In [64]:

                                
                                ### Age graph with Pclass

                                titanic_df
                                [
                                'Age'
                                ][
                                titanic_df
                                .
                                Pclass
                                ==
                                1
                                ]
                                .
                                plot
                                (
                                kind
                                =
                                'kde'
                                )
                                titanic_df
                                [
                                'Age'
                                ][
                                titanic_df
                                .
                                Pclass
                                ==
                                2
                                ]
                                .
                                plot
                                (
                                kind
                                =
                                'kde'
                                )
                                titanic_df
                                [
                                'Age'
                                ][
                                titanic_df
                                .
                                Pclass
                                ==
                                3
                                ]
                                .
                                plot
                                (
                                kind
                                =
                                'kde'
                                )
                                plt
                                .
                                legend
                                ([
                                "1st class"
                                ,
                                "2nd class"
                                ,
                                "3rd class"
                                ])
                                plt
                                .
                                show
                                ()
                            

 

In [ ]: