2-Pandas索引--数据分析
【摘要】
Pandas索引 import pandas as pddf = pd.read_csv('C:/JupyterWork/data/titanic.csv') :5df['Age'][:5]0 22.01 38.02 26.03 35.04 35.0Name: Age, dtype: float641、指...
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Pandas索引
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import pandas as pd
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df = pd.read_csv('C:/JupyterWork/data/titanic.csv')
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:5
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df['Age'][:5]
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0 22.0
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1 38.0
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2 26.0
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3 35.0
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4 35.0
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Name: Age, dtype: float64
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1、指定显示两个列以上的数据
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:5
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df[['Age','Fare']][:5]
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Age Fare
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0 22.0 7.2500
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1 38.0 71.2833
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2 26.0 7.9250
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3 35.0 53.1000
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4 35.0 8.0500
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指定显示行索引具体的数据需要用到loc和iloc
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loc：用label来定位去获取数据
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iloc：用位置来定位获取数据
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0
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df.iloc[0]
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PassengerId 1
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Survived 0
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Pclass 3
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Name Braund, Mr. Owen Harris
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Sex male
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Age 22
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SibSp 1
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Parch 0
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Ticket A/5 21171
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Fare 7.25
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Cabin NaN
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Embarked S
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Name: 0, dtype: object
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0:5
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df.iloc[0:5]
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PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked
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0 1 0 3 Braund, Mr. Owen Harris male 22.0 1 0 A/5 21171 7.2500 NaN S
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1 2 1 1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 0 PC 17599 71.2833 C85 C
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2 3 1 3 Heikkinen, Miss. Laina female 26.0 0 0 STON/O2. 3101282 7.9250 NaN S
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3 4 1 1 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 0 113803 53.1000 C123 S
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4 5 0 3 Allen, Mr. William Henry male 35.0 0 0 373450 8.0500 NaN S
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在显示指定的行数据上，再次过滤显示指定列的数据
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1:3]
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df.iloc[0:5,1:3]
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Survived Pclass
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0 0 3
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1 1 1
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2 1 3
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3 1 1
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4 0 3
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df = df.set_index('Name')
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用标签名称做定位就用loc
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用一个数值定位，就用iloc
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df.loc['Braund, Mr. Owen Harris']
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df.loc['Braund, Mr. Owen Harris']
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PassengerId 1
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Survived 0
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Pclass 3
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Sex male
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Age 22
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SibSp 1
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Parch 0
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Ticket A/5 21171
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Fare 7.25
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Cabin NaN
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Embarked S
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Name: Braund, Mr. Owen Harris, dtype: object
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用loc定位显示指定行中，指定列的数据
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df.loc['Braund, Mr. Owen Harris','Fare']
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df.loc['Braund, Mr. Owen Harris','Fare']
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7.25
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用loc定位具体的数据后，并修改数据
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df.loc['Braund, Mr. Owen Harris','Fare']=1000
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df.loc['Braund, Mr. Owen Harris','Fare']
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1000.0
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boolean 类型索引
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df['Fare']>40
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Name
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Braund, Mr. Owen Harris True
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Cumings, Mrs. John Bradley (Florence Briggs Thayer) True
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Heikkinen, Miss. Laina False
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Futrelle, Mrs. Jacques Heath (Lily May Peel) True
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Allen, Mr. William Henry False
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Moran, Mr. James False
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McCarthy, Mr. Timothy J True
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Palsson, Master. Gosta Leonard False
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Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) False
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Nasser, Mrs. Nicholas (Adele Achem) False
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Sandstrom, Miss. Marguerite Rut False
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Bonnell, Miss. Elizabeth False
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Saundercock, Mr. William Henry False
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Andersson, Mr. Anders Johan False
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Vestrom, Miss. Hulda Amanda Adolfina False
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Hewlett, Mrs. (Mary D Kingcome) False
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Rice, Master. Eugene False
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Williams, Mr. Charles Eugene False
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Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) False
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Masselmani, Mrs. Fatima False
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Fynney, Mr. Joseph J False
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Beesley, Mr. Lawrence False
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McGowan, Miss. Anna "Annie" False
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Sloper, Mr. William Thompson False
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Palsson, Miss. Torborg Danira False
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Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson) False
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Emir, Mr. Farred Chehab False
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Fortune, Mr. Charles Alexander True
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O'Dwyer, Miss. Ellen "Nellie" False
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Todoroff, Mr. Lalio False
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...
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Giles, Mr. Frederick Edward False
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Swift, Mrs. Frederick Joel (Margaret Welles Barron) False
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Sage, Miss. Dorothy Edith "Dolly" True
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Gill, Mr. John William False
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Bystrom, Mrs. (Karolina) False
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Duran y More, Miss. Asuncion False
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Roebling, Mr. Washington Augustus II True
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van Melkebeke, Mr. Philemon False
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Johnson, Master. Harold Theodor False
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Balkic, Mr. Cerin False
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Beckwith, Mrs. Richard Leonard (Sallie Monypeny) True
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Carlsson, Mr. Frans Olof False
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Vander Cruyssen, Mr. Victor False
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Abelson, Mrs. Samuel (Hannah Wizosky) False
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Najib, Miss. Adele Kiamie "Jane" False
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Gustafsson, Mr. Alfred Ossian False
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Petroff, Mr. Nedelio False
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Laleff, Mr. Kristo False
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Potter, Mrs. Thomas Jr (Lily Alexenia Wilson) True
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Shelley, Mrs. William (Imanita Parrish Hall) False
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Markun, Mr. Johann False
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Dahlberg, Miss. Gerda Ulrika False
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Banfield, Mr. Frederick James False
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Sutehall, Mr. Henry Jr False
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Rice, Mrs. William (Margaret Norton) False
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Montvila, Rev. Juozas False
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Graham, Miss. Margaret Edith False
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Johnston, Miss. Catherine Helen "Carrie" False
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Behr, Mr. Karl Howell False
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Dooley, Mr. Patrick False
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Name: Fare, Length: 891, dtype: bool
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用bool类型帅选数据，只显示符合条件的数据
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:5
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df[df['Fare']>40][:5]
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PassengerId Survived Pclass Sex Age SibSp Parch Ticket Fare Cabin Embarked
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Name
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Braund, Mr. Owen Harris 1 0 3 male 22.0 1 0 A/5 21171 1000.0000 NaN S
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Cumings, Mrs. John Bradley (Florence Briggs Thayer) 2 1 1 female 38.0 1 0 PC 17599 71.2833 C85 C
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Futrelle, Mrs. Jacques Heath (Lily May Peel) 4 1 1 female 35.0 1 0 113803 53.1000 C123 S
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McCarthy, Mr. Timothy J 7 0 1 male 54.0 0 0 17463 51.8625 E46 S
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Fortune, Mr. Charles Alexander 28 0 1 male 19.0 3 2 19950 263.0000 C23 C25 C27 S
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显示Sex为male的前5条数据
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df[df['Sex']== 'male'][:5]
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PassengerId Survived Pclass Sex Age SibSp Parch Ticket Fare Cabin Embarked
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Name
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Braund, Mr. Owen Harris 1 0 3 male 22.0 1 0 A/5 21171 1000.0000 NaN S
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Allen, Mr. William Henry 5 0 3 male 35.0 0 0 373450 8.0500 NaN S
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Moran, Mr. James 6 0 3 male NaN 0 0 330877 8.4583 NaN Q
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McCarthy, Mr. Timothy J 7 0 1 male 54.0 0 0 17463 51.8625 E46 S
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Palsson, Master. Gosta Leonard 8 0 3 male 2.0 3 1 349909 21.0750 NaN S
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显示Sex为male数据，并且计算数据中age的平均值
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df.loc[df['Sex']=='male','Age'].mean()
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30.72664459161148
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统计数据中Age大于70的数量
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(
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(df['Age']>70).sum()
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5
文章来源: brucelong.blog.csdn.net，作者：Bruce小鬼，版权归原作者所有，如需转载，请联系作者。
原文链接：brucelong.blog.csdn.net/article/details/80719026
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