DeprecationWarning: .ix is deprecated. Please use.loc for label based indexing or.iloc for positi

抄过来的例子 自我体会

import pandas as pd
data = [[1,2,3],[4,5,6],[7,8,9]]
rows = ['row1','row2','row3']#行标签
columns = ['col1','col2','col3']#列标签
df = pd.DataFrame(data, index=rows, columns=columns)
print df

    col1  col2  col3
row1     1     2     3
row2     4     5     6
row3     7     8     9

print df.loc['row1']

col1    1
col2    2
col3    3
Name: row1, dtype: int64

print df.iloc[0]

col1    1
col2    2
col3    3
Name: row1, dtype: int64

print df.ix[0] print df.ix['row1']

col1    1
col2    2
col3    3
Name: row1, dtype: int64

说明以上三种是等同的，

但是loc和iloc更具体，稍不注意就会语法出错

ix更通用性，估计容易出现误差

print df.ix['row1'，‘col1’]   print df.ix['row1',0]

这两个具体到行号和列号，直接定位