How to select multiple columns without deprecated ix in pandas

Question

In python, for data slicing in DataFrame in package pandas, .ix is already deprecated from pandas 0.20.0. The official website offers alternative solutions with either .loc or .iloc to do the hybrid selection (http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html). The .index could help extract multiple rows. By contrast, the columns.get_loc seems can only select one column at most. Is there an alternative function available that can be used to extract multiple columns in a hybrid manner using .iloc?

Answer 1

Yes, function is called Index.get_indexer and return position of columns or index by list of names.

Use it this way:

df = pd.DataFrame({
         'a':[4,5,4,5,5,4],
         'b':[7,8,9,4,2,3],
         'c':[1,3,5,7,1,0],
         'd':[5,3,6,9,2,4],
}, index=list('ABCDEF'))
print (df)
   a  b  c  d
A  4  7  1  5
B  5  8  3  3
C  4  9  5  6
D  5  4  7  9
E  5  2  1  2
F  4  3  0  4

cols = ['a','b','c']
df1 = df.iloc[1, df.columns.get_indexer(cols)]
print (df1)
a    5
b    8
c    3
Name: B, dtype: int64

df11 = df.iloc[[1], df.columns.get_indexer(cols)]
print (df11)
   a  b  c
B  5  8  3

idx = ['A','C']
df2 = df.iloc[df.index.get_indexer(idx), 2:]
print (df2)
   c  d
A  1  5
C  5  6