DataFrame的loc标签,切片,布尔索引选择单行多行多列

　　pandas中DataFrame选择数据可以用loc选择器，注意loc不是函数。loc用于标签索引筛选，也可以用于布尔值筛选。

　　官方介绍如下：

　　Access a group of rows and columns by label(s) or a boolean array。.loc[] is primarily label based, but may also be used with a boolean array.

　　我们按照这个df为例来进行学习。

df = pd.DataFrame([['bj','100','200'],['sh','80','60'],['nj','50','30']],columns=['city','sale','rent'],index=['a','b','c'])
print(df)

  city sale rent
a   bj  100  200
b   sh   80   60
c   nj   50   30

　　1、loc标签索引选择单行，返回Series或者DataFrame

df = pd.DataFrame([['bj','100','200'],['sh','80','60'],['nj','50','30']],columns=['city','sale','rent'],index=['a','b','c'])
print(df.loc['a'])
print('-------------')
print(df.loc[['a']])

city     bj
sale    100
rent    200
Name: a, dtype: object
-------------
  city sale rent
a   bj  100  200

　　2、loc标签索引选择多行及所有列，返回DataFrame

df = pd.DataFrame([['bj','100','200'],['sh','80','60'],['nj','50','30']],columns=['city','sale','rent'],index=['a','b','c'])
print(df.loc[['a','b']])

  city sale rent
a   bj  100  200
b   sh   80   60

　　3、loc标签索引选择多行多列，返回DataFrame

df = pd.DataFrame([['bj','100','200'],['sh','80','60'],['nj','50','30']],columns=['city','sale','rent'],index=['a','b','c'])
print(df.loc[['a','b'],['city','sale']])

  city sale
a   bj  100
b   sh   80

　　4、loc标签切片索引（末端包含）选择多行及所有列，返回DataFrame

df = pd.DataFrame([['bj','100','200'],['sh','80','60'],['nj','50','30']],columns=['city','sale','rent'],index=['a','b','c'])
print(df.loc['a':'b',:])
print('=====')
print(df.loc[['a','b'],:])

  city sale rent
a   bj  100  200
b   sh   80   60
=====
  city sale rent
a   bj  100  200
b   sh   80   60

　　5、loc标签切片索引（末端包含）选择多行多列，返回DataFrame

df = pd.DataFrame([['bj','100','200'],['sh','80','60'],['nj','50','30']],columns=['city','sale','rent'],index=['a','b','c'])
print(df.loc['a':'b','city':'sale'])

  city sale
a   bj  100
b   sh   80

　　6、loc布尔索引（末端包含）选择多行多列，返回DataFrame

df = pd.DataFrame([['bj','100','200'],['sh','80','60'],['nj','50','30']],columns=['city','sale','rent'],index=['a','b','c'])
print(df.loc[[True,False,True],'city':'sale'])
print('====')
print(df.loc[[True,False,True],[True,True,False]])

  city sale
a   bj  100
c   nj   50
====
  city sale
a   bj  100
c   nj   50

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