def prepare_features_scores_list(self,features): features_scores = pd.DataFrame() features_scores.insert(0, 'feature', list(features)) return features_scores

这是一个定义在类中的函数，该函数的输入参数是一个DataFrame对象features，其作用是将特征列按照原有顺序生成一个新的DataFrame对象features_scores，并且在features_scores的第一列插入一个'feature'列，该列的值为原有特征列的列名。具体地，该函数首先创建一个空的DataFrame对象features_scores，然后使用insert方法在其第0列插入一个'feature'列，该列的值为原有DataFrame对象features的列名，最后返回生成的features_scores对象。该函数的输出是一个新的DataFrame对象features_scores，其包含了原有DataFrame对象features的特征列及其列名。

相关问题

def transform_new_features(self,X,features_scores): features_list= features_scores['feature'].values new_features = X.loc[:, features_list] return new_features

这是一个定义在类中的函数，该函数的输入参数包括一个DataFrame对象X和一个DataFrame对象features_scores，其作用是将X中的特征列按照features_scores中的顺序进行重排，并生成一个新的DataFrame对象new_features。具体地，该函数首先从features_scores中提取出特征列名称，存储在列表features_list中；然后，使用loc方法从X中选取特征列，仅保留features_list中包含的特征列，并将其存储到新的DataFrame对象new_features中。最后，该函数返回生成的new_features对象。该函数的输出是一个新的DataFrame对象new_features，其包含了X中包含的特征列，但是按照features_scores中的顺序进行了重排。

import requests from bs4 import BeautifulSoup import matplotlib.pyplot as plt import pandas as pd PLAYERS_LIMIT = 25 TABLE_CLASS_NAME = "players_table" plt.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['axes.unicode_minus'] = False def get_top_players_scores(limit=PLAYERS_LIMIT, table_class_name=TABLE_CLASS_NAME): url = "https://nba.hupu.com/stats/players" response = requests.get(url) soup = BeautifulSoup(response.text, "html.parser") players = [] scores = [] table = soup.find("table", class_=table_class_name) rows = table.find_all("tr") for row in rows[1:limit+1]: cols = row.find_all("td") player = cols[1].text.strip() score_range = cols[4].text.strip() score_parts = score_range.split("-") min_score = float(score_parts[0]) max_score = float(score_parts[1]) score = int((min_score + max_score) / 2) players.append(player) scores.append(score) return players, scores def plot_top_players_scores(players, scores): data = {"Player": players, "Score": scores} df = pd.DataFrame(data) fig, ax = plt.subplots(figsize=(12, 6)) ax.bar(players, scores, color='green', alpha=0.6) ax.set_xlabel('球员', fontsize=12) ax.set_ylabel('得分', fontsize=12) ax.set_title('NBA球员得分', fontsize=14) plt.xticks(rotation=45, ha='right', fontsize=8) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) for i, score in enumerate(scores): ax.text(i, score+0.5, str(score), ha='center', va='bottom') writer = pd.ExcelWriter('plot_top_players_scores.xlsx') df.to_excel(writer, index=False) writer.save() fig.tight_layout() plt.show() if __name__ == "__main__": players, scores = get_top_players_scores() plot_top_players_scores(players, scores)这段代码生成的excel损坏

这可能是因为在代码中将Excel文件的写操作放在了`for`循环中，每次迭代都会打开并写入Excel文件，导致Excel文件损坏。应该将Excel文件的写操作放在循环外面，只在循环结束后执行一次即可。修改后的代码如下：

import requests
from bs4 import BeautifulSoup
import matplotlib.pyplot as plt
import pandas as pd

PLAYERS_LIMIT = 25
TABLE_CLASS_NAME = "players_table"

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

def get_top_players_scores(limit=PLAYERS_LIMIT, table_class_name=TABLE_CLASS_NAME):
    url = "https://nba.hupu.com/stats/players"
    response = requests.get(url)
    soup = BeautifulSoup(response.text, "html.parser")
    players = []
    scores = []
    table = soup.find("table", class_=table_class_name)
    rows = table.find_all("tr")
    for row in rows[1:limit+1]:
        cols = row.find_all("td")
        player = cols[1].text.strip()
        score_range = cols[4].text.strip()
        score_parts = score_range.split("-")
        min_score = float(score_parts[0])
        max_score = float(score_parts[1])
        score = int((min_score + max_score) / 2)
        players.append(player)
        scores.append(score)
    return players, scores

def plot_top_players_scores(players, scores):
    data = {"Player": players, "Score": scores}
    df = pd.DataFrame(data)
    fig, ax = plt.subplots(figsize=(12, 6))
    ax.bar(players, scores, color='green', alpha=0.6)
    ax.set_xlabel('球员', fontsize=12)
    ax.set_ylabel('得分', fontsize=12)
    ax.set_title('NBA球员得分', fontsize=14)
    plt.xticks(rotation=45, ha='right', fontsize=8)
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)
    for i, score in enumerate(scores):
        ax.text(i, score+0.5, str(score), ha='center', va='bottom')
    writer = pd.ExcelWriter('plot_top_players_scores.xlsx')
    df.to_excel(writer, index=False)
    writer.save()
    fig.tight_layout()
    plt.show()

if __name__ == "__main__":
    players, scores = get_top_players_scores()
    plot_top_players_scores(players, scores)

这样修改后，Excel文件的写操作只会在循环结束后执行一次，不会出现损坏的问题。