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3-2-Pandas 索引

时间：2019-10-08 18:25:42      阅读：83      评论：0      收藏：0      [点我收藏+]

 Pandas章节应用的数据可以在以下链接下载：  https://files.cnblogs.com/files/AI-robort/Titanic_Data-master.zip

 

In [4]:
import pandas as pd
df=pd.read_csv(‘./Titanic_Data-master/Titanic_Data-master/train.csv‘)
In [5]:
df[‘Age‘][:5]
Out[5]:
0    22.0
1    38.0
2    26.0
3    35.0
4    35.0
Name: Age, dtype: float64
In [6]:
df[[‘Age‘,‘Fare‘]][:5]
Out[6]:
 
 AgeFare
0 22.0 7.2500
1 38.0 71.2833
2 26.0 7.9250
3 35.0 53.1000
4 35.0 8.0500
 
  • loc 用lable来定位
  • iloc 用position来定位
In [8]:
df.iloc[0]
Out[8]:
PassengerId                          1
Survived                             0
Pclass                               3
Name           Braund, Mr. Owen Harris
Sex                               male
Age                                 22
SibSp                                1
Parch                                0
Ticket                       A/5 21171
Fare                              7.25
Cabin                              NaN
Embarked                             S
Name: 0, dtype: object
In [9]:
df.iloc[0:5]
Out[9]:
 
 PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
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
In [10]:
df.iloc[0:5,1:3]#指定0-5行数据  1-3不包含第3列
Out[10]:
 
 SurvivedPclass
0 0 3
1 1 1
2 1 3
3 1 1
4 0 3
In [11]:
df=df.set_index(‘Name‘)
In [13]:
df.loc[‘Heikkinen, Miss. Laina‘]
Out[13]:
PassengerId                   3
Survived                      1
Pclass                        3
Sex                      female
Age                          26
SibSp                         0
Parch                         0
Ticket         STON/O2. 3101282
Fare                      7.925
Cabin                       NaN
Embarked                      S
Name: Heikkinen, Miss. Laina, dtype: object
In [14]:
df.loc[‘Heikkinen, Miss. Laina‘,‘Fare‘]
Out[14]:
7.925
In [16]:
df.loc[‘Heikkinen, Miss. Laina‘:‘Allen, Mr. William Henry‘,:]#以lable作为索引
Out[16]:
 
 PassengerIdSurvivedPclassSexAgeSibSpParchTicketFareCabinEmbarked
Name           
Heikkinen, Miss. Laina 3 1 3 female 26.0 0 0 STON/O2. 3101282 7.925 NaN S
Futrelle, Mrs. Jacques Heath (Lily May Peel) 4 1 1 female 35.0 1 0 113803 53.100 C123 S
Allen, Mr. William Henry 5 0 3 male 35.0 0 0 373450 8.050 NaN S
In [17]:
df.loc[‘Heikkinen, Miss. Laina‘,‘Fare‘]=1000#具体定位后赋值操作
df.head()
Out[17]:
 
 PassengerIdSurvivedPclassSexAgeSibSpParchTicketFareCabinEmbarked
Name           
Braund, Mr. Owen Harris 1 0 3 male 22.0 1 0 A/5 21171 7.2500 NaN S
Cumings, Mrs. John Bradley (Florence Briggs Thayer) 2 1 1 female 38.0 1 0 PC 17599 71.2833 C85 C
Heikkinen, Miss. Laina 3 1 3 female 26.0 0 0 STON/O2. 3101282 1000.0000 NaN S
Futrelle, Mrs. Jacques Heath (Lily May Peel) 4 1 1 female 35.0 1 0 113803 53.1000 C123 S
Allen, Mr. William Henry 5 0 3 male 35.0 0 0 373450 8.0500 NaN S
In [18]:
#被遗弃了，现在不用了
df.ix[‘Heikkinen, Miss. Laina‘,‘Fare‘]
 
E:\software\Anaconda3 5.2.0\lib\site-packages\ipykernel_launcher.py:2: DeprecationWarning: 
.ix is deprecated. Please use
.loc for label based indexing or
.iloc for positional indexing

See the documentation here:
http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated
Out[18]:
1000.0
 

bool类型的索引

In [19]:
df[‘Fare‘]>10#返回BOOL值
Out[19]:
Name
Braund, Mr. Owen Harris                                      False
Cumings, Mrs. John Bradley (Florence Briggs Thayer)           True
Heikkinen, Miss. Laina                                        True
Futrelle, Mrs. Jacques Heath (Lily May Peel)                  True
Allen, Mr. William Henry                                     False
Moran, Mr. James                                             False
McCarthy, Mr. Timothy J                                       True
Palsson, Master. Gosta Leonard                                True
Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)             True
Nasser, Mrs. Nicholas (Adele Achem)                           True
Sandstrom, Miss. Marguerite Rut                               True
Bonnell, Miss. Elizabeth                                      True
Saundercock, Mr. William Henry                               False
Andersson, Mr. Anders Johan                                   True
Vestrom, Miss. Hulda Amanda Adolfina                         False
Hewlett, Mrs. (Mary D Kingcome)                               True
Rice, Master. Eugene                                          True
Williams, Mr. Charles Eugene                                  True
Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)       True
Masselmani, Mrs. Fatima                                      False
Fynney, Mr. Joseph J                                          True
Beesley, Mr. Lawrence                                         True
McGowan, Miss. Anna "Annie"                                  False
Sloper, Mr. William Thompson                                  True
Palsson, Miss. Torborg Danira                                 True
Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)     True
Emir, Mr. Farred Chehab                                      False
Fortune, Mr. Charles Alexander                                True
O‘Dwyer, Miss. Ellen "Nellie"                                False
Todoroff, Mr. Lalio                                          False
                                                             ...  
Giles, Mr. Frederick Edward                                   True
Swift, Mrs. Frederick Joel (Margaret Welles Barron)           True
Sage, Miss. Dorothy Edith "Dolly"                             True
Gill, Mr. John William                                        True
Bystrom, Mrs. (Karolina)                                      True
Duran y More, Miss. Asuncion                                  True
Roebling, Mr. Washington Augustus II                          True
van Melkebeke, Mr. Philemon                                  False
Johnson, Master. Harold Theodor                               True
Balkic, Mr. Cerin                                            False
Beckwith, Mrs. Richard Leonard (Sallie Monypeny)              True
Carlsson, Mr. Frans Olof                                     False
Vander Cruyssen, Mr. Victor                                  False
Abelson, Mrs. Samuel (Hannah Wizosky)                         True
Najib, Miss. Adele Kiamie "Jane"                             False
Gustafsson, Mr. Alfred Ossian                                False
Petroff, Mr. Nedelio                                         False
Laleff, Mr. Kristo                                           False
Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)                 True
Shelley, Mrs. William (Imanita Parrish Hall)                  True
Markun, Mr. Johann                                           False
Dahlberg, Miss. Gerda Ulrika                                  True
Banfield, Mr. Frederick James                                 True
Sutehall, Mr. Henry Jr                                       False
Rice, Mrs. William (Margaret Norton)                          True
Montvila, Rev. Juozas                                         True
Graham, Miss. Margaret Edith                                  True
Johnston, Miss. Catherine Helen "Carrie"                      True
Behr, Mr. Karl Howell                                         True
Dooley, Mr. Patrick                                          False
Name: Fare, Length: 891, dtype: bool
In [20]:
df[df[‘Fare‘]>40]#把Bool类型传到 data_frame中=>显示大于40的表格
Out[20]:
 
 PassengerIdSurvivedPclassSexAgeSibSpParchTicketFareCabinEmbarked
Name           
Cumings, Mrs. John Bradley (Florence Briggs Thayer) 2 1 1 female 38.0 1 0 PC 17599 71.2833 C85 C
Heikkinen, Miss. Laina 3 1 3 female 26.0 0 0 STON/O2. 3101282 1000.0000 NaN S
Futrelle, Mrs. Jacques Heath (Lily May Peel) 4 1 1 female 35.0 1 0 113803 53.1000 C123 S
McCarthy, Mr. Timothy J 7 0 1 male 54.0 0 0 17463 51.8625 E46 S
Fortune, Mr. Charles Alexander 28 0 1 male 19.0 3 2 19950 263.0000 C23 C25 C27 S
Spencer, Mrs. William Augustus (Marie Eugenie) 32 1 1 female NaN 1 0 PC 17569 146.5208 B78 C
Meyer, Mr. Edgar Joseph 35 0 1 male 28.0 1 0 PC 17604 82.1708 NaN C
Holverson, Mr. Alexander Oskar 36 0 1 male 42.0 1 0 113789 52.0000 NaN S
Laroche, Miss. Simonne Marie Anne Andree 44 1 2 female 3.0 1 2 SC/Paris 2123 41.5792 NaN C
Harper, Mrs. Henry Sleeper (Myna Haxtun) 53 1 1 female 49.0 1 0 PC 17572 76.7292 D33 C
Ostby, Mr. Engelhart Cornelius 55 0 1 male 65.0 0 1 113509 61.9792 B30 C
Goodwin, Master. William Frederick 60 0 3 male 11.0 5 2 CA 2144 46.9000 NaN S
Icard, Miss. Amelie 62 1 1 female 38.0 0 0 113572 80.0000 B28 NaN
Harris, Mr. Henry Birkhardt 63 0 1 male 45.0 1 0 36973 83.4750 C83 S
Goodwin, Miss. Lillian Amy 72 0 3 female 16.0 5 2 CA 2144 46.9000 NaN S
Hood, Mr. Ambrose Jr 73 0 2 male 21.0 0 0 S.O.C. 14879 73.5000 NaN S
Bing, Mr. Lee 75 1 3 male 32.0 0 0 1601 56.4958 NaN S
Carrau, Mr. Francisco M 84 0 1 male 28.0 0 0 113059 47.1000 NaN S
Fortune, Miss. Mabel Helen 89 1 1 female 23.0 3 2 19950 263.0000 C23 C25 C27 S
Chaffee, Mr. Herbert Fuller 93 0 1 male 46.0 1 0 W.E.P. 5734 61.1750 E31 S
Greenfield, Mr. William Bertram 98 1 1 male 23.0 0 1 PC 17759 63.3583 D10 D12 C
White, Mr. Richard Frasar 103 0 1 male 21.0 0 1 35281 77.2875 D26 S
Porter, Mr. Walter Chamberlain 111 0 1 male 47.0 0 0 110465 52.0000 C110 S
Baxter, Mr. Quigg Edmond 119 0 1 male 24.0 0 1 PC 17558 247.5208 B58 B60 C
Hickman, Mr. Stanley George 121 0 2 male 21.0 2 0 S.O.C. 14879 73.5000 NaN S
White, Mr. Percival Wayland 125 0 1 male 54.0 0 1 35281 77.2875 D26 S
Futrelle, Mr. Jacques Heath 138 0 1 male 37.0 1 0 113803 53.1000 C123 S
Giglio, Mr. Victor 140 0 1 male 24.0 0 0 PC 17593 79.2000 B86 C
Pears, Mrs. Thomas (Edith Wearne) 152 1 1 female 22.0 1 0 113776 66.6000 C2 S
Williams, Mr. Charles Duane 156 0 1 male 51.0 0 1 PC 17597 61.3792 NaN C
... ... ... ... ... ... ... ... ... ... ... ...
Endres, Miss. Caroline Louise 717 1 1 female 38.0 0 0 PC 17757 227.5250 C45 C
Chambers, Mr. Norman Campbell 725 1 1 male 27.0 1 0 113806 53.1000 E8 S
Allen, Miss. Elisabeth Walton 731 1 1 female 29.0 0 0 24160 211.3375 B5 S
Lesurer, Mr. Gustave J 738 1 1 male 35.0 0 0 PC 17755 512.3292 B101 C
Cavendish, Mr. Tyrell William 742 0 1 male 36.0 1 0 19877 78.8500 C46 S
Ryerson, Miss. Susan Parker "Suzette" 743 1 1 female 21.0 2 2 PC 17608 262.3750 B57 B59 B63 B66 C
Crosby, Capt. Edward Gifford 746 0 1 male 70.0 1 1 WE/P 5735 71.0000 B22 S
Marvin, Mr. Daniel Warner 749 0 1 male 19.0 1 0 113773 53.1000 D30 S
Herman, Mrs. Samuel (Jane Laver) 755 1 2 female 48.0 1 2 220845 65.0000 NaN S
Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards) 760 1 1 female 33.0 0 0 110152 86.5000 B77 S
Carter, Mrs. William Ernest (Lucile Polk) 764 1 1 female 36.0 1 2 113760 120.0000 B96 B98 S
Hogeboom, Mrs. John C (Anna Andrews) 766 1 1 female 51.0 1 0 13502 77.9583 D11 S
Robert, Mrs. Edward Scott (Elisabeth Walton McMillan) 780 1 1 female 43.0 0 1 24160 211.3375 B3 S
Dick, Mrs. Albert Adrian (Vera Gillespie) 782 1 1 female 17.0 1 0 17474 57.0000 B20 S
Guggenheim, Mr. Benjamin 790 0 1 male 46.0 0 0 PC 17593 79.2000 B82 B84 C
Sage, Miss. Stella Anna 793 0 3 female NaN 8 2 CA. 2343 69.5500 NaN S
Carter, Master. William Thornton II 803 1 1 male 11.0 1 2 113760 120.0000 B96 B98 S
Chambers, Mrs. Norman Campbell (Bertha Griggs) 810 1 1 female 33.0 1 0 113806 53.1000 E8 S
Hays, Mrs. Charles Melville (Clara Jennings Gregg) 821 1 1 female 52.0 1 1 12749 93.5000 B69 S
Lam, Mr. Len 827 0 3 male NaN 0 0 1601 56.4958 NaN S
Stone, Mrs. George Nelson (Martha Evelyn) 830 1 1 female 62.0 0 0 113572 80.0000 B28 NaN
Compton, Miss. Sara Rebecca 836 1 1 female 39.0 1 1 PC 17756 83.1583 E49 C
Chip, Mr. Chang 839 1 3 male 32.0 0 0 1601 56.4958 NaN S
Sage, Mr. Douglas Bullen 847 0 3 male NaN 8 2 CA. 2343 69.5500 NaN S
Goldenberg, Mrs. Samuel L (Edwiga Grabowska) 850 1 1 female NaN 1 0 17453 89.1042 C92 C
Wick, Mrs. George Dennick (Mary Hitchcock) 857 1 1 female 45.0 1 1 36928 164.8667 NaN S
Sage, Miss. Dorothy Edith "Dolly" 864 0 3 female NaN 8 2 CA. 2343 69.5500 NaN S
Roebling, Mr. Washington Augustus II 868 0 1 male 31.0 0 0 PC 17590 50.4958 A24 S
Beckwith, Mrs. Richard Leonard (Sallie Monypeny) 872 1 1 female 47.0 1 1 11751 52.5542 D35 S
Potter, Mrs. Thomas Jr (Lily Alexenia Wilson) 880 1 1 female 56.0 0 1 11767 83.1583 C50 C

177 rows × 11 columns

In [21]:
df[df[‘Sex‘]==‘male‘][:5]
Out[21]:
 
 PassengerIdSurvivedPclassSexAgeSibSpParchTicketFareCabinEmbarked
Name           
Braund, Mr. Owen Harris 1 0 3 male 22.0 1 0 A/5 21171 7.2500 NaN S
Allen, Mr. William Henry 5 0 3 male 35.0 0 0 373450 8.0500 NaN S
Moran, Mr. James 6 0 3 male NaN 0 0 330877 8.4583 NaN Q
McCarthy, Mr. Timothy J 7 0 1 male 54.0 0 0 17463 51.8625 E46 S
Palsson, Master. Gosta Leonard 8 0 3 male 2.0 3 1 349909 21.0750 NaN S
In [22]:
df.loc[df[‘Sex‘]==‘male‘,‘Age‘].mean()#索引性别，然后对年龄求平均值
Out[22]:
30.72664459161148
In [24]:
(df[‘Age‘]>70).sum()#对大于70年龄的人统计个数
Out[24]:
5

3-2-Pandas 索引

原文：https://www.cnblogs.com/AI-robort/p/11636743.html
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