如何修复AttributeError：“系列”对象没有属性“ to_numpy”

Question

我的输出：

def load_data(self):
    """
    Load data from list of paths
    :return: 3D-array X and 2D-array y
    """
    X = None
    y = None
    df = pd.read_excel('data/Data.xlsx', header=None)
    for i in range(len(df.columns)):
        sentences_ = df[i].to_numpy().tolist()
        label_vec = [0.0 for _ in range(0, self.n_class)]
        label_vec[i] = 1.0
        labels_ = [label_vec for _ in range(0, len(sentences_))]
        if X is None:
            X = sentences_
            y = labels_
        else:
            X += sentences_
            y += labels_
    X, max_length = self.tokenize_sentences(X)
    X = self.word_embed_sentences(X, max_length=self.max_length)
    return np.array(X), np.array(y)

这是我的熊猫库代码为pd的代码。在Google Colab中运行时，出现以下错误：

def load_data(self):
    """
    Load data from list of paths
    :return: 3D-array X and 2D-array y
    """
    X = None
    y = None
    df = pd.read_excel('data/Data.xlsx', header=None)
    for i in range(len(df.columns)):
        sentences_ = df[i].to_numpy().tolist()
        label_vec = [0.0 for _ in range(0, self.n_class)]
        label_vec[i] = 1.0
        labels_ = [label_vec for _ in range(0, len(sentences_))]
        if X is None:
            X = sentences_
            y = labels_
        else:
            X += sentences_
            y += labels_
    X, max_length = self.tokenize_sentences(X)
    X = self.word_embed_sentences(X, max_length=self.max_length)
    return np.array(X), np.array(y)

Answer 1

如果您需要您的代码与所有版本的 Pandas 一起使用，这里有一种将 Series 转换为 NumPy 数组的简单方法：

import pandas as pd
import numpy as np

s = pd.Series([1.1, 2.3])
a = np.array(s)
print(a)  # [1.1 2.3]

在高级说明中，如果您的系列缺少值（作为 NaN 值），则可以将这些值转换为掩码数组：

s = pd.Series([1.1, np.nan])
a = np.ma.masked_invalid(s)
print(a)  # [1.1 --]

Answer 2

检查您的熊猫库的版本：

import pandas
print(pandas.__version__)

如果您的版本小于0.24.1：

pip install --upgrade pandas