我有这种方法,我从熊猫数据框
中抓取列,这取决于标签,但是通过Numpy
索引要快得多。
在pandas
或numpy
中,有没有一种方法可以在不迭代的情况下从列标签转到列索引?
DF_var = pd.DataFrame(np.random.random((5,10)), columns=["attr_%d" % _ for _ in range(10)])
query_cols = ["attr_2","attr_5","attr_6","attr_0"]
want_idx = [0,2,5,6]
# Something like np.where w/o iterating through?
# np.where(query_cols in DF_var.columns)
# TypeError: unhashable type: 'list'
# np.where(x in DF_var.columns for x in query_cols)
# (array([0]),)
long_way = list()
for i, label in enumerate(DF_var.columns):
if label in query_cols:
long_way.append(i)
# print(sorted(long_way))
# [0, 2, 5, 6]
short_way = [df.columns.get_loc(col) for col in query_cols]
print(sorted(short_way))
# outputs [0, 2, 5, 6]