pandas的基本用法06-算术和数据对齐
# -*- coding: utf-8 -*-
import numpy as np
from pandas import Series, DataFrame
import dataframeDemo
from matplotlib.pyplot import axis
s1 = Series([-1,3,4], index=['a','b','c'])
s2 = Series([0,9,2,5], index=['a','b','c','d'])
print s1+s2
# a -1
# b 12
# c 6
# d NaN
# dtype: float64
print 'DataFrame加法'
df1 = DataFrame(np.arange(9).reshape(3,3),
index=list('abc'),
columns=list('123')
)
df2 = DataFrame(np.arange(9).reshape(3,3),
index=list('abd'),
columns=list('023')
)
print df1
print df2
print df1+df2
# 1 2 3
# a 0 1 2
# b 3 4 5
# c 6 7 8
# +
# 0 2 3
# a 0 1 2
# b 3 4 5
# d 6 7 8
# =
# 0 1 2 3
# a NaN NaN 2 4
# b NaN NaN 8 10
# c NaN NaN NaN NaN
# d NaN NaN NaN NaN
print '数据填充'
df1 = DataFrame(np.arange(12.).reshape(3,4))
df2 = DataFrame(np.arange(20.).reshape(4,5))
print df1
# 0 1 2 3
# 0 0 1 2 3
# 1 4 5 6 7
# 2 8 9 10 11
print df2
# 0 1 2 3 4
# 0 0 1 2 3 4
# 1 5 6 7 8 9
# 2 10 11 12 13 14
# 3 15 16 17 18 19
print df1.add(df2)
# 0 1 2 3 4
# 0 0 2 4 6 NaN
# 1 9 11 13 15 NaN
# 2 18 20 22 24 NaN
# 3 NaN NaN NaN NaN NaN
print df1.add(df2, fill_value=0)
# 0 1 2 3 4
# 0 0 2 4 6 4
# 1 9 11 13 15 9
# 2 18 20 22 24 14
# 3 15 16 17 18 19
print df1.reindex(columns=df2.columns, fill_value=0)
# 0 1 2 3 4
# 0 0 1 2 3 0
# 1 4 5 6 7 0
# 2 8 9 10 11 0
print 'DataFrame与Series之间的操作'
dataframe = DataFrame(np.arange(12.).reshape(3,4))
series = dataframe.ix[0]
print dataframe
# 0 1 2 3
# 0 0 1 2 3
# 1 4 5 6 7
# 2 8 9 10 11
print series
# 0 0
# 1 1
# 2 2
# 3 3
print dataframe-series
# 0 1 2 3
# 0 0 0 0 0
# 1 4 4 4 4
# 2 8 8 8 8
series = dataframe[0]
print dataframe.sub(series, axis=0)# 按列减
# 0 1 2 3
# 0 0 1 2 3
# 1 0 1 2 3
# 2 0 1 2 3
