对pandas的算术运算和数据对齐实例详解

pandas可以对不同索引的对象进行算术运算，如果存在不同的索引对，结果的索引就是该索引对的并集。

一、算术运算

a、series的加法运算

s1 = Series([1,2,3],index=["a","b","c"])
  s2 = Series([4,5,6],index=["a","c","e"])
  print(s1+s2)
  '''
  a  5.0
  b  NaN
  c  8.0
  e  NaN
  '''

sereis相加会自动进行数据对齐操作，在不重叠的索引处会使用NA(NaN)值进行填充，series进行算术运算的时候，不需要保证series的大小一致。

b、DataFrame的加法运算

d1 = np.arange(1,10).reshape(3,3)
  dataFrame1 = DataFrame(d1,index=["a","b","c"],columns=["one","two","three"])
  d2 = np.arange(1,10).reshape(3,3)
  dataFrame2 = DataFrame(d2,index=["a","b","e"],columns=["one","two","four"])
  print(dataFrame1+dataFrame2)
  '''
    four one three  two
  a  NaN 2.0  NaN  4.0
  b  NaN 8.0  NaN 10.0
  c  NaN NaN  NaN  NaN
  e  NaN NaN  NaN  NaN
  '''

dataFrame相加时，对齐操作需要行和列的索引都重叠的时候才回相加，否则会使用NA值进行填充。

二、指定填充值

s1 = Series([1,2,3],index=["a","b","c"])
  s2 = Series([4,5,6],index=["a","c","e"])
  print( s1.add(s2,fill_value=0))
  '''
  a  5.0
  b  2.0
  c  8.0
  e  6.0
  '''

需要注意的时候，使用add方法对两个series进行相加的时候，设置fill_value的值是对于不存在索引的series用指定值进行填充后再进行相加。除了加法add，还有sub减法,div除法,mul乘法，使用方式与add相同。DataFrame与series一样。

s1 = Series([1,2,3],index=["a","b","c"])
  s2 = Series([4,5,6],index=["a","c","e"])
  print(s2.reindex(["a","b","c","d"],fill_value=0))
  '''
  a  4
  b  0
  c  5
  d  0
  '''
  s3 = s1 + s2
  print(s3.reindex(["a","b","c","e"],fill_value=0))
  '''
  a  5.0
  b  NaN
  c  8.0
  e  NaN
  '''

使用reindex进行填充的时候，需要注意的是，不能对已经是值为NaN的进行重新赋值，只能对使用reindex之前不存在的所以使用指定的填充值，DataFrame也是一样的。

三、DataFrame与Series的混合运算

a、DataFrame的行进行广播

a = np.arange(9).reshape(3,3)
  d = DataFrame(a,index=["a","b","c"],columns=["one","two","three"])
  #取d的第一行为Series
  s = d.ix[0]
  print(d+s)
  '''
    one two three
  a  0  2   4
  b  3  5   7
  c  6  8   10
  '''

b、DataFrame的列进行广播

a = np.arange(9).reshape(3,3)
  d = DataFrame(a,index=["a","b","c"],columns=["one","two","three"])
  #取d的第一列为Series
  s = d["one"]
  print(d.add(s,axis=0))
  '''
    one two three
  a  0  1   2
  b  6  7   8
  c  12  13   14
  '''

对列进行广播的时候，必须要使用add方法，而且还要将axis设置为0，不然就会得到下面的结果

print(d.add(s))
  '''
    a  b  c one three two
  a NaN NaN NaN NaN  NaN NaN
  b NaN NaN NaN NaN  NaN NaN
  c NaN NaN NaN NaN  NaN NaN
  '''

以上这篇对pandas的算术运算和数据对齐实例详解就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持三水点靠木。