python pandas.DataFrame.loc函数使用详解
官方函数
DataFrame.loc
Accessagroupofrowsandcolumnsbylabel(s)orabooleanarray.
.loc[]isprimarilylabelbased,butmayalsobeusedwithabooleanarray.
#可以使用label值，但是也可以使用布尔值
- Allowedinputsare:#可以接受单个的label，多个label的列表，多个label的切片
- Asinglelabel,e.g.5or‘a',(notethat5isinterpretedasalabeloftheindex,andneverasanintegerpositionalongtheindex).#这里的5不是数值指定的位置，而是label值
- Alistorarrayoflabels,e.g.[‘a',‘b',‘c'].
sliceobjectwithlabels,e.g.‘a':'f'.
Warning:#如果使用多个label的切片，那么切片的起始位置都是包含的
Notethatcontrarytousualpythonslices,boththestartandthestopareincluded
- Abooleanarrayofthesamelengthastheaxisbeingsliced,e.g.[True,False,True].
实例详解
一、选择数值
1、生成df
df=pd.DataFrame([[1,2],[4,5],[7,8]], ...index=['cobra','viper','sidewinder'], ...columns=['max_speed','shield']) df Out[15]: max_speedshield cobra12 viper45 sidewinder78
2、Singlelabel.单个row_label返回的Series
df.loc['viper'] Out[17]: max_speed4 shield5 Name:viper,dtype:int64
2、Listoflabels.列表row_label返回的DataFrame
df.loc[['cobra','viper']] Out[20]: max_speedshield cobra12 viper45
3、Singlelabelforrowandcolumn同时选定行和列
df.loc['cobra','shield'] Out[24]:2
4、Slicewithlabelsforrowandsinglelabelforcolumn.Asmentionedabove,notethatboththestartandstopofthesliceareincluded.同时选定多个行和单个列，注意的是通过列表选定多个rowlabel时，首位均是选定的。
df.loc['cobra':'viper','max_speed'] Out[25]: cobra1 viper4 Name:max_speed,dtype:int64
5、Booleanlistwiththesamelengthastherowaxis布尔列表选择rowlabel
布尔值列表是根据某个位置的TrueorFalse来选定，如果某个位置的布尔值是True，则选定该row
df Out[30]: max_speedshield cobra12 viper45 sidewinder78 df.loc[[True]] Out[31]: max_speedshield cobra12 df.loc[[True,False]] Out[32]: max_speedshield cobra12 df.loc[[True,False,True]] Out[33]: max_speedshield cobra12 sidewinder78
6、ConditionalthatreturnsabooleanSeries条件布尔值
df.loc[df['shield']>6] Out[34]: max_speedshield sidewinder78
7、ConditionalthatreturnsabooleanSerieswithcolumnlabelsspecified条件布尔值和具体某列的数据
df.loc[df['shield']>6,['max_speed']] Out[35]: max_speed sidewinder7
8、CallablethatreturnsabooleanSeries通过函数得到布尔结果选定数据
df Out[37]: max_speedshield cobra12 viper45 sidewinder78 df.loc[lambdadf:df['shield']==8] Out[38]: max_speedshield sidewinder78
二、赋值
1、Setvalueforallitemsmatchingthelistoflabels根据某列表选定的row及某列column赋值
df.loc[['viper','sidewinder'],['shield']]=50 df Out[43]: max_speedshield cobra12 viper450 sidewinder750
2、Setvalueforanentirerow将某行row的数据全部赋值
df.loc['cobra']=10 df Out[48]: max_speedshield cobra1010 viper450 sidewinder750
3、Setvalueforanentirecolumn将某列的数据完全赋值
df.loc[:,'max_speed']=30 df Out[50]: max_speedshield cobra3010 viper3050 sidewinder3050
4、Setvalueforrowsmatchingcallablecondition条件选定rows赋值
df.loc[df['shield']>35]=0 df Out[52]: max_speedshield cobra3010 viper00 sidewinder00
三、行索引是数值
df=pd.DataFrame([[1,2],[4,5],[7,8]], ...index=[7,8,9],columns=['max_speed','shield']) df Out[54]: max_speedshield 712 845 978
通过行rows的切片的方式取多个：
df.loc[7:9] Out[55]: max_speedshield 712 845 978
四、多维索引
1、生成多维索引
tuples=[
...('cobra','marki'),('cobra','markii'),
...('sidewinder','marki'),('sidewinder','markii'),
...('viper','markii'),('viper','markiii')
...]
index=pd.MultiIndex.from_tuples(tuples)
values=[[12,2],[0,4],[10,20],
...[1,4],[7,1],[16,36]]
df=pd.DataFrame(values,columns=['max_speed','shield'],index=index)
df
Out[57]:
max_speedshield
cobramarki122
markii04
sidewindermarki1020
markii14
vipermarkii71
markiii1636
2、Singlelabel.传入的就是最外层的rowlabel，返回DataFrame
df.loc['cobra'] Out[58]: max_speedshield marki122 markii04
3、Singleindextuple.传入的是索引元组，返回Series
df.loc[('cobra','markii')]
Out[59]:
max_speed0
shield4
Name:(cobra,markii),dtype:int64
4、Singlelabelforrowandcolumn.如果传入的是row和column，和传入tuple是类似的，返回Series
df.loc['cobra','marki'] Out[60]: max_speed12 shield2 Name:(cobra,marki),dtype:int64
5、Singletuple.Noteusing[[]]returnsaDataFrame.传入一个数组，返回一个DataFrame
df.loc[[('cobra','markii')]]
Out[61]:
max_speedshield
cobramarkii04
6、Singletuplefortheindexwithasinglelabelforthecolumn获取某个colum的某row的数据，需要左边传入多维索引的tuple，然后再传入column
df.loc[('cobra','marki'),'shield']
Out[62]:2
7、传入多维索引和单个索引的切片：
df.loc[('cobra','marki'):'viper']
Out[63]:
max_speedshield
cobramarki122
markii04
sidewindermarki1020
markii14
vipermarkii71
markiii1636
df.loc[('cobra','marki'):'sidewinder']
Out[64]:
max_speedshield
cobramarki122
markii04
sidewindermarki1020
markii14
df.loc[('cobra','marki'):('sidewinder','marki')]
Out[65]:
max_speedshield
cobramarki122
markii04
sidewindermarki1020
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