PCA: TypeError: can only concatenate list (not "int") to list

Question

我试图按照 this post 的建议解决方案在我的数据集上安装 PCA。该代码适用于形状为 (150, 8) 的 iris 数据，如下所示：


array([[ 1.7837721 , -1.23464679,  4.27808537, ...,  0.63061657,
        -1.79849625, -1.41574397],
       [-0.35396307, -0.13400175,  3.91751182, ..., -0.58928302,
        -0.15735542, -0.99157312],
       [-0.20380491, -1.06074392,  4.65814864, ...,  2.19686369,
         0.14920164,  2.33371106],
       ...,
       [-1.05079672,  1.46836264,  5.41970214, ...,  0.32847349,
         0.27133141,  1.01266607],
       [ 0.19569856,  0.57739573,  3.84749973, ...,  0.02400556,
        -0.08193678,  0.51223263],
       [ 0.04905765,  0.66314259,  6.22608157, ...,  0.60076934,
        -0.56890579, -0.23642103]])

但是，使用我的形状 (3475, 29) 的数据时发现错误：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-292-5661ffbde57b> in <module>
     38 # data = array([randn(8) for k in range(150)])
     39 data[:50, 2:4] += 5
---> 40 data[50:, 2:5] += 5
     41 
     42 """ visualize """

TypeError: can only concatenate list (not "int") to list

我的数据（形状 (3475, 29)）如下所示：

array([[58.5, 27.0, 88.5, ..., nan, 0.0, -3.0],
       [58.5, 27.0, 88.5, ..., nan, 0.0, -3.0],
       [47.0, 45.0, 92.0, ..., 1.6, -0.649519052838329,
        -1.1249999999999998],
       ...,
       [46.0, 44.5, 98.0, ..., 2.5, 0.0, -1.3],
       [46.0, 40.0, 98.0, ..., 2.5, 0.0, -1.3],
       [46.5, 44.5, 76.5, ..., 17.767857142857142, -0.4788774197473401,
        -1.4219984343829701]], dtype=object)

使用的代码：

# SO - doug - my data 
from numpy import array, dot, mean, std, empty, argsort
from numpy.linalg import eigh, solve
from numpy.random import randn
from matplotlib.pyplot import subplots, show


def cov(X):
    """
    Covariance matrix
    note: specifically for mean-centered data
    note: numpy's `cov` uses N-1 as normalization
    """
    return dot(X.T, X) / X.shape[0]
    # N = data.shape[1]
    # C = empty((N, N))
    # for j in range(N):
    #   C[j, j] = mean(data[:, j] * data[:, j])
    #   for k in range(j + 1, N):
    #       C[j, k] = C[k, j] = mean(data[:, j] * data[:, k])
    # return C

def pca(data, pc_count = None):
    """
    Principal component analysis using eigenvalues
    note: this mean-centers and auto-scales the data (in-place)
    """
    data -= mean(data, 0)
    data /= std(data, 0)
    C = cov(data)
    E, V = eigh(C)
    key = argsort(E)[::-1][:pc_count]
    E, V = E[key], V[:, key]
    U = dot(data, V)  # used to be dot(V.T, data.T).T
    return U, E, V

""" test data """
# data = array([randn(8) for k in range(150)])
data = my_data1   # Using my own data
data[:50, 2:4] += 5
data[50:, 2:5] += 5

""" visualize """
trans = pca(data, 3)[0]
fig, (ax1, ax2) = subplots(1, 2)
ax1.scatter(data[:50, 0], data[:50, 1], c = 'r')
ax1.scatter(data[50:, 0], data[50:, 1], c = 'b')
ax2.scatter(trans[:50, 0], trans[:50, 1], c = 'r')
ax2.scatter(trans[50:, 0], trans[50:, 1], c = 'b')
show()

什么

data[:50, 2:4] += 5
data[50:, 2:5] += 5

做吗？

我试着用

替换这两行

data = [data[:50, 2:4] += 5]
data = [data[50:, 2:5] += 5]

基于，返回

  File "<ipython-input-296-5d80e1852b4e>", line 42
    data = [data[:50, 2:4] += 5]
                            ^
SyntaxError: invalid syntax

感谢任何建议！

Answer 1

如果data是二维数值数组，

data[:50, 2:4]

选择数组的一个切片（技术上是 view），并且

data[:50, 2:4] += 5

将 5 添加到该切片的所有元素 - 并修改 data.

但是

TypeError: can only concatenate list (not "int") to list

表示 data 包含一个或多个列表，而不仅仅是数字。对于列表，+ 不是（数学）加法，而是 join/concatenate。 [1,2,3]+[4].

关于你的第二次尝试：

[data[:50, 2:4] += 5]

与

非常不同

[i + 1]

[] 列一个清单。您不能在列表中执行赋值，例如 = 或 +=。因此出现语法错误。

您显示的 (3475, 29) 数组将 dtype 列为 object。这是一个强有力的指标，表明它包含数字以外的东西（或除了数字之外）。根据错误，那必须是一个列表。

所以你需要清理mydata。

PCA: TypeError: can only concatenate list (not "int") to list

PCA: TypeError: can only concatenate list (not "int") to list

python

arrays

numpy

pca