使用to_excel存储DataFrame报错

Question

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

def answer_one():
    energy = pd.read_excel('Energy Indicators.xls', skiprows=17,skip_footer= 38)  # 读数据，下载下来的表中前面17行和后面38行都没用，读取时跳过
    energy = energy[['Unnamed: 1','Petajoules','Gigajoules','%']]
    energy.columns = ['Country', 'Energy Supply', 'Energy Supply per Capita', '% Renewable']  # 根据题目要求重命名
    energy[['Energy Supply', 'Energy Supply per Capita', '% Renewable']] =  energy[['Energy Supply', 'Energy Supply per Capita', '% Renewable']].replace('...',np.NaN).apply(pd.to_numeric)  # 根据题目要求将没有数据的值转化为NaN
    energy['Energy Supply'] = energy['Energy Supply']*1000000  # 根据题目要求转换单位
    energy['Country'] = energy['Country'].replace({'China, Hong Kong Special Administrative Region':'Hong Kong','United Kingdom of Great Britain and Northern Ireland':'United Kingdom','Republic of Korea':'South Korea','United States of America':'United States','Iran (Islamic Republic of)':'Iran'})  # 根据题目要求替换相应国家名字，替换写在字典中，replace函数替换
    energy['Country'] = energy['Country'].str.replace(" \(.*\)","")  # 根据题目要求替换相应国家名字，去除一些特殊符号

    GDP = pd.read_csv('world_bank.csv', skiprows=4)
    GDP['Country Name'] = GDP['Country Name'].replace({"Korea, Rep.": "South Korea", "Iran, Islamic Rep.": "Iran", "Hong Kong SAR, China": "Hong Kong"})  # 同样，替换相应国家名字
    GDP = GDP[['Country Name','2006','2007','2008','2009','2010','2011','2012','2013','2014','2015']]  # 题目说只要10年的，就取出这些年的

    ScimEn = pd.read_excel('scimagojr country rank 1996-2019.xlsx')
    ScimEn = ScimEn[0:15]  # 读数据，取出前15个

    df = pd.merge(ScimEn, energy, how = 'inner', left_on = 'Country', right_on='Country')
    dff = pd.merge(df,GDP, how = 'inner', left_on = 'Country', right_on='Country Name').set_index('Country')  # 合并数据，inner方法取交集，最后只有15个国家
    dff = dff[['Rank', 'Documents', 'Citable documents', 'Citations', 'Self-citations', 'Citations per document', 'H index', 'Energy Supply', 'Energy Supply per Capita', '% Renewable', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015']]
    return dff

answer_one.to_excel('data.xlsx')
answer_one()
print(answer_one())

最后总会出来这一行：
answer_one.to_excel('data.xlsx')

AttributeError: 'function' object has no attribute 'to_excel'

小白求助 刚学不久o(╥﹏╥)o

Answer 1

answer_one.to_excel('data.xlsx')
->
answer_one().to_excel('data.xlsx')