我想从虹膜数据集https://www.kaggle.com/jchen2186/machine-learning-with-iris-dataset/data
获得协方差我正在使用numpy,并且功能-> np.cov(iris)
with open("Iris.csv") as iris:
reader = csv.reader(iris)
data = []
next(reader)
for row in reader:
data.append(row)
for i in data:
i.pop(0)
i.pop(4)
iris = np.array(data)
np.cov(iris)
我收到此错误:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-4-bfb836354075> in <module>
----> 1 np.cov(iris)
D:\Anaconda\lib\site-packages\numpy\lib\function_base.py in cov(m, y, rowvar, bias, ddof, fweights, aweights)
2300 w *= aweights
2301
-> 2302 avg, w_sum = average(X, axis=1, weights=w, returned=True)
2303 w_sum = w_sum[0]
2304
D:\Anaconda\lib\site-packages\numpy\lib\function_base.py in average(a, axis, weights, returned)
354
355 if weights is None:
--> 356 avg = a.mean(axis)
357 scl = avg.dtype.type(a.size/avg.size)
358 else:
D:\Anaconda\lib\site-packages\numpy\core\_methods.py in _mean(a, axis, dtype, out, keepdims)
73 is_float16_result = True
74
---> 75 ret = umr_sum(arr, axis, dtype, out, keepdims)
76 if isinstance(ret, mu.ndarray):
77 ret = um.true_divide(
TypeError: cannot perform reduce with flexible type
我不明白这是什么意思。
答案 0 :(得分:0)
因此,如果您想修改代码,可以尝试使用带有launch-buildserver
的{{1}}函数。然后选择所需的适当列。
但是,这里有一些命令可以简化此任务。他们使用[{"aptNumber": "", "city": "", "key": "6bba4c82-18e2-3c10-a798-028f42d97857", "nickName": "My name ", "numberofbathrooms": "2", "numberofbedrooms": "1", "state": "", "streetName": "Fskslal", "streetNumber": "Fjsl", "typeof": "Apartment", "userid": "sb7Hj93D08XiaRguQ4cbSjz4vXC3"},
{ "aptNumber": "", "city": "", "key": "714590f6-e8da-2d29-20c2-e5010a3a9df4", "nickName": "BATMAN", "numberofbathrooms": "2", "numberofbedrooms": "0", "state": "", "streetName": "", "streetNumber": "", "typeof": "Apartment", "userid": "sb7Hj93D08XiaRguQ4cbSjz4vXC3"},
{ "aptNumber": "", "city": "", "key": "bd2ad46a-f307-4f8e-1fc8-ba828b6651bc", "nickName": "NOT BATMAN", "numberofbathrooms": "0", "numberofbedrooms": "0", "state": "", "streetName": "", "streetNumber": "", "typeof": "Apartment", "userid": "sb7Hj93D08XiaRguQ4cbSjz4vXC3"} ]
和Iris.csv
加载虹膜数据集,获得X和y并获得协方差矩阵:
pandas.read_csv
希望这有所帮助。