首先导入scipy
的包
from scipy.io import loadmat
然后读取
m = loadmat("B0006_404.mat")
注意这里m是一个dict
字典数据结构
查看key
m.keys()
数据展示
>>> m["data"]
array([[ 1. , 0.35 , 0.265 , ..., 0.0995, 0.0485, 0.07 ],
[ 2. , 0.53 , 0.42 , ..., 0.2565, 0.1415, 0.21 ],
[ 1. , 0.44 , 0.365 , ..., 0.2155, 0.114 , 0.155 ],
...,
[ 1. , 0.59 , 0.44 , ..., 0.439 , 0.2145, 0.2605],
[ 1. , 0.6 , 0.475 , ..., 0.5255, 0.2875, 0.308 ],
[ 2. , 0.625 , 0.485 , ..., 0.531 , 0.261 , 0.296 ]])
>>> m["labels"][0]
array([1], dtype=uint8)
>>> m["labels"][0][0]
1
>>> m["labels"][0][0] + 1
2
>>> m["labels"][0].as_type("int")
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'numpy.ndarray' object has no attribute 'as_type' # 注意时astype不是as_type
>>> m["labels"][0].dtype
dtype('uint8')
>>> m["labels"][0].astype("int")
array([1])
>>> df = pd.DataFrame(m["data"])
>>> df.head()
0 1 2 3 4 5 6 7
0 1.0 0.350 0.265 0.090 0.2255 0.0995 0.0485 0.070
1 2.0 0.530 0.420 0.135 0.6770 0.2565 0.1415 0.210
2 1.0 0.440 0.365 0.125 0.5160 0.2155 0.1140 0.155
3 3.0 0.330 0.255 0.080 0.2050 0.0895 0.0395 0.055
4 3.0 0.425 0.300 0.095 0.3515 0.1410 0.0775 0.120
网友评论