def deal31():
dbutil = DBUtil(host, port, database, username, password)
sql = 'select * from author_info_new'
author_info_new0910 = dbutil.get_allresult(sql, 'df')
sql = 'select * from h_index'
h_index0910 = dbutil.get_allresult(sql, 'df')
sql = 'select * from article_cite_data'
article_cite_data0910 = dbutil.get_allresult(sql, 'df')
sql = 'select scopus_id, person_id, publish_year, count(*) as first_au_doc_num from scopus_author_article ' \
'group by scopus_id, person_id, publish_year'
scopus_author_article0910 = dbutil.get_allresult(sql, 'df')
physics_list = pd.read_excel(
'C:/Users/Administrator/Desktop/物理学人才清单_20200908.xlsx',
sheet_name='data')
physics_list['人才编号'] = physics_list['人才编号'].astype('str')
author_info_new0910 = author_info_new0910.loc[
author_info_new0910['person_id'].isin(list(physics_list['人才编号']))]
h_index0910 = h_index0910.loc[h_index0910['person_id'].isin(
list(physics_list['人才编号']))]
article_cite_data0910 = article_cite_data0910.loc[
article_cite_data0910['person_id'].isin(list(physics_list['人才编号']))]
scopus_author_article0910 = scopus_author_article0910.loc[
scopus_author_article0910['person_id'].isin(list(
physics_list['人才编号']))]
dbutil.df_insert('author_info_new0910', author_info_new0910)
dbutil.df_insert('h_index0910', h_index0910)
dbutil.df_insert('article_cite_data0910', article_cite_data0910)
dbutil.df_insert('scopus_author_article0910', scopus_author_article0910)
def deal6():
dbutil = DBUtil(host, port, database, username, password)
sql = "select person_id, name from not_matched_author where data_no='2020060819255418'"
df = dbutil.get_allresult(sql, 'df')
dbutil.close()
df2 = pd.read_excel(
'C:/Users/Administrator/Desktop/test_data/test_data2.xlsx')
df2['学者代码'] = df2['学者代码'].astype('str')
result = pd.merge(df,
df2,
how='left',
left_on='person_id',
right_on='学者代码')
result.sort_values(by=['学者代码'], inplace=True, ignore_index=True)
search_url = 'https://www.scopus.com/results/authorNamesList.uri?sort=count-f&src=al' \
'&st1={}' \
'&st2={}' \
'&orcidId=&affilName={}' \
'&sot=anl&sdt=anl&sl=64&resultsPerPage=200&offset=1&jtp=false¤tPage=1&exactAuthorSearch=true'
for i in range(len(result)):
first_name = result.loc[i, 'name'].split(' ')[0].lower()
last_name = result.loc[i, 'name'].split(' ')[1].lower()
ins_name = '+'.join(result.loc[i, 'ins_en'].split(' ')).lower()
result.loc[i, '搜索链接'] = search_url.format(first_name, last_name,
ins_name)
result.to_excel('C:/Users/Administrator/Desktop/0609not.xlsx',
sheet_name='Sheet1',
index=False)
def rf_cal():
dbutil = DBUtil(host, port, database, username, password)
sql = 'select scopus_journal_id, cite_num+0 as cite_num, cite_journal_id from scopus_cite_data ' \
'where scopus_journal_id!=cite_journal_id'
all_cite_data = dbutil.get_allresult(sql, 'df')
# with open('core_journal.json', 'r', encoding='utf-8') as cj:
# core_journal = json.load(cj)
core_journal = {}
already_data = pd.read_excel('C:/Users/Administrator/Desktop/分学科结果.xlsx')
already_data['scopus_journal_id'] = already_data[
'scopus_journal_id'].astype('str')
for subject, sub_df in already_data.groupby('subject'):
core_journal[subject] = list(sub_df['scopus_journal_id'])
rf_cited_list = []
rf_citing_list = []
for subject, sub_journal in core_journal.items():
print(subject)
sub_cited_df_temp = all_cite_data.loc[
all_cite_data['cite_journal_id'].isin(sub_journal)]
sub_cited_df = sub_cited_df_temp.groupby(
'scopus_journal_id', as_index=False)['cite_num'].sum()
sub_citing_df_temp = all_cite_data.loc[
all_cite_data['scopus_journal_id'].isin(sub_journal)]
sub_citing_df = sub_citing_df_temp.groupby(
'cite_journal_id', as_index=False)['cite_num'].sum()
sub_cited_df['subject'] = subject
rf_cited_list.append(sub_cited_df)
sub_citing_df['subject'] = subject
rf_citing_list.append(sub_citing_df)
rf_cited_df = pd.concat(rf_cited_list)
rf_citing_df = pd.concat(rf_citing_list)
# dbutil.df_insert('rf_cited_data', rf_cited_df)
# dbutil.df_insert('rf_citing_data', rf_citing_df)
select_journal = pd.read_excel(
'C:/Users/Administrator/Desktop/未被分学科期刊.xlsx')
select_journal['Scopus Source ID'] = select_journal[
'Scopus Source ID'].astype('str')
rf_cited_df = rf_cited_df.loc[rf_cited_df['scopus_journal_id'].isin(
list(select_journal['Scopus Source ID']))]
rf_citing_df = rf_citing_df.loc[rf_citing_df['cite_journal_id'].isin(
list(select_journal['Scopus Source ID']))]
dbutil.df_insert('rf_cited_data_last', rf_cited_df)
dbutil.df_insert('rf_citing_data_last', rf_citing_df)
dbutil.close()
def deal10():
dbutil = DBUtil(host, port, database, username, password)
sql = "select person_id+0 as person_id from (select DISTINCT person_id from find_result UNION select " \
"person_id from not_find) a ORDER BY person_id"
df = dbutil.get_allresult(sql, 'df')
df2 = pd.read_excel('C:/Users/Administrator/Desktop/0618webofscience.xlsx')
df3 = df2.loc[~df2['person_id'].isin(list(df['person_id']))]
df3.to_excel('C:/Users/Administrator/Desktop/data_left.xlsx',
sheet_name='Sheet1',
index=False)
def deal8():
df = pd.read_excel('C:/Users/Administrator/Desktop/0618webofscience.xlsx')
dbutil = DBUtil(host, port, database, username, password)
sql = "select distinct (person_id+0) as person_id from not_find where person_id not in (select person_id from find_result)"
not_find = dbutil.get_allresult(sql, 'df')
dbutil.close()
result = pd.merge(not_find, df, how='left', on='person_id')
result.to_excel('C:/Users/Administrator/Desktop/未搜索到结果清单.xlsx',
sheet_name='Sheet1',
index=False)
def data_prepare():
dbutil = DBUtil(host, port, database, username, password)
sql = 'select scopus_journal_id, sum(cite_num+0) as cite_num_all from scopus_cite_data group by scopus_journal_id'
df1 = dbutil.get_allresult(sql, 'df')
sql = 'SELECT scopus_journal_id,cite_num+0 as cite_num_self from scopus_cite_data ' \
'where scopus_journal_id=cite_journal_id'
df2 = dbutil.get_allresult(sql, 'df')
df1 = pd.merge(df1, df2, how='outer', on='scopus_journal_id')
df1.fillna(0, inplace=True)
df1['cite_num_noself'] = df1['cite_num_all'] - df1['cite_num_self']
df1.to_excel('C:/Users/Administrator/Desktop/去除自引被引数据.xlsx', index=False)
sql = 'select cite_journal_id as scopus_journal_id, sum(cite_num+0) as cite_num_all ' \
'from scopus_cite_data group by cite_journal_id'
df3 = dbutil.get_allresult(sql, 'df')
df3 = pd.merge(df3, df2, how='outer', on='scopus_journal_id')
df3.fillna(0, inplace=True)
df3['cite_num_noself'] = df3['cite_num_all'] - df3['cite_num_self']
df3.to_excel('C:/Users/Administrator/Desktop/去除自引引用数据.xlsx', index=False)
def temp(input_data):
from src.config.DBUtil import DBUtil
from src.Scopus_Crawler.scopus_config import host, port, database, username, password
dbutil = DBUtil(host, port, database, username, password)
sql = "SELECT person_id FROM author_info_new UNION SELECT person_id FROM mult_matched_author UNION SELECT " \
"person_id FROM not_matched_author"
df = dbutil.get_allresult(sql, 'df')
dbutil.close()
input_list = [str(i['person_id']) for i in input_data]
diff = set(input_list).difference(set(df['person_id']))
out_data = [i for i in input_data if str(i['person_id']) in diff]
return out_data
def deal9():
dbutil = DBUtil(host, port, database, username, password)
sql = "select person_id+0 as person_id, find_num, ins from find_result"
find_result = dbutil.get_allresult(sql, 'df')
find_result['s_num'] = '0'
for i in range(len(find_result)):
temp_list = find_result.loc[i, 'ins'][:-1].split(' (')
find_result.loc[i, 'ins'] = temp_list[0]
find_result.loc[i, 's_num'] = temp_list[1]
df = pd.read_excel('C:/Users/Administrator/Desktop/0618webofscience.xlsx')
result = pd.merge(find_result, df, on='person_id', how='left')
result.set_index(['person_id', 'JCR期刊列表', '姓名', 'find_num', 'ins_x'],
inplace=True)
result.to_excel('C:/Users/Administrator/Desktop/有搜索结果的数据.xlsx',
sheet_name='Sheet1')
def deal1():
dbutil = DBUtil(host, port, database, username, password)
sql = "select DISTINCT person_id, name, scopus_id from author_info_new where data_no='2020060819255418'"
author_list1 = dbutil.get_allresult(sql, 'df')
dbutil.close()
author_list2 = pd.read_excel(
'C:/Users/Administrator/Desktop/test_data/test_data2.xlsx',
sheet_name='Sheet1')
author_list2['学者代码'] = author_list2['学者代码'].astype('str')
author_list = pd.merge(author_list1,
author_list2,
how='left',
left_on='person_id',
right_on='学者代码')
author_list.drop_duplicates(subset=['person_id'],
inplace=True,
keep='first')
author_list.reset_index(drop=True, inplace=True)
author_list['详细链接'] = 'a'
author_list['百度搜索链接'] = 'b'
author_list['搜索链接'] = 'c'
search_url = 'https://www.scopus.com/results/authorNamesList.uri?sort=count-f&src=al' \
'&st1={}' \
'&st2={}' \
'&orcidId=&affilName={}' \
'&sot=anl&sdt=anl&sl=64&resultsPerPage=200&offset=1&jtp=false¤tPage=1&exactAuthorSearch=true'
for i in range(len(author_list)):
author_list.loc[
i,
'详细链接'] = 'https://www.scopus.com/authid/detail.uri?authorId=%s' % author_list.loc[
i, 'scopus_id']
first_name = author_list.loc[i, 'name'].split(' ')[0].lower()
last_name = author_list.loc[i, 'name'].split(' ')[1].lower()
ins_name = '+'.join(author_list.loc[i, 'ins_en'].split(' ')).lower()
author_list.loc[i, '搜索链接'] = search_url.format(first_name, last_name,
ins_name)
author_list.loc[i, '百度搜索链接'] = 'https://www.baidu.com/s?ie=utf-8&f=8&rsv_bp=1&tn=baidu&wd=%s' \
% author_list.loc[i, '头衔当选单位'] + author_list.loc[i, '姓名']
author_list.to_excel('C:/Users/Administrator/Desktop/check_data.xlsx',
index=False,
encoding='utf-8')
def deal30():
dbutil = DBUtil(host, port, database, username, password)
sql = 'select distinct person_id from author_info_new'
df = dbutil.get_allresult(sql, 'df')
input_df = pd.read_excel(
'C:/Users/Administrator/Desktop/物理学人才清单_20200908.xlsx',
sheet_name='Sheet2')
input_df['人才编号'] = input_df['人才编号'].astype('str')
input_df = input_df.loc[~input_df['人才编号'].isin(list(df['person_id']))]
input_df[
'百度搜索'] = 'https://www.baidu.com/s?ie=utf-8&f=8&rsv_bp=1&tn=baidu&wd=' + input_df[
'当选单位信息'] + input_df['姓名']
input_df['百度学术搜索'] = 'https://xueshu.baidu.com/usercenter/data/authorchannel?cmd=inject_page&author=' + \
input_df['姓名'] + '&affiliate=' + input_df['当选单位信息']
input_df.to_excel('C:/Users/Administrator/Desktop/人工查找0909.xlsx',
index=False)
def deal21():
dbutil = DBUtil(host, port, database, username, password)
sql = 'select * from wos_doc_data'
df = dbutil.get_allresult(sql, 'df')
df['doc_num'] = df['doc_num'].astype('int')
df2 = pd.read_excel(
'C:/Users/Administrator/Desktop/cssc-category-mapping.xlsx',
sheet_name='Sheet1')
df2['id'] = df2['id'].astype('str')
for i in range(len(df2)):
if len(df2.loc[i, 'id']) < 4:
df2.loc[i, 'id'] = '0' + df2.loc[i, 'id']
df = pd.merge(df, df2, on='category_id')
result = df.groupby(by=['orgName', 'year', 'id', 'Description'],
as_index=False)['doc_num'].sum()
dbutil.df_insert('doc_data', result)
def deal5():
dbutil = DBUtil(host, port, database, username, password)
sql = "select DISTINCT person_id from mult_matched_author where data_no='2020052716115197'"
df = dbutil.get_allresult(sql, 'df')
dbutil.close()
df2 = pd.read_excel(
'C:/Users/Administrator/Desktop/test_data/test_data2.xlsx')
df2['学者代码'] = df2['学者代码'].astype('str')
result = pd.merge(df,
df2,
how='left',
left_on='person_id',
right_on='学者代码')
result.drop_duplicates(subset=['person_id'],
inplace=True,
ignore_index=True)
result.to_excel('C:/Users/Administrator/Desktop/0605.xlsx',
sheet_name='Sheet1',
index=False)
def last_process():
dbutil = DBUtil(host, port, database, username, password)
# sql = 'select scopus_journal_id, cite_num as rf_cited_num, subject from rf_cited_data'
# rf_cited_data = dbutil.get_allresult(sql, 'df')
#
# sql = 'select cite_journal_id as scopus_journal_id, cite_num as rf_citing_num, subject from rf_citing_data'
# rf_citing_data = dbutil.get_allresult(sql, 'df')
sql = 'select scopus_journal_id, cite_num as rf_cited_num, subject from rf_cited_data_last'
rf_cited_data = dbutil.get_allresult(sql, 'df')
sql = 'select cite_journal_id as scopus_journal_id, cite_num as rf_citing_num, subject from rf_citing_data_last'
rf_citing_data = dbutil.get_allresult(sql, 'df')
sql = 'select * from cited_data'
sum_cited_data = dbutil.get_allresult(sql, 'df')
sql = 'select * from citing_data'
sum_citing_data = dbutil.get_allresult(sql, 'df')
rf_cited_data = pd.merge(rf_cited_data,
sum_cited_data,
how='left',
on='scopus_journal_id')
rf_cited_data['rf_cited_value'] = rf_cited_data[
'rf_cited_num'] / rf_cited_data['cited_num']
rf_cited_sum = rf_cited_data.groupby(
'scopus_journal_id', as_index=False)['rf_cited_value'].sum()
rf_cited_sum.rename(columns={'rf_cited_value': 'rf_cited_sum'},
inplace=True)
rf_cited_data = pd.merge(rf_cited_data,
rf_cited_sum,
on='scopus_journal_id')
rf_cited_data['rf_cited_percent'] = rf_cited_data[
'rf_cited_value'] / rf_cited_data['rf_cited_sum']
rf_citing_data = pd.merge(rf_citing_data,
sum_citing_data,
how='left',
on='scopus_journal_id')
rf_citing_data['rf_citing_value'] = rf_citing_data[
'rf_citing_num'] / rf_citing_data['citing_num']
rf_citing_sum = rf_citing_data.groupby(
'scopus_journal_id', as_index=False)['rf_citing_value'].sum()
rf_citing_sum.rename(columns={'rf_citing_value': 'rf_citing_sum'},
inplace=True)
rf_citing_data = pd.merge(rf_citing_data,
rf_citing_sum,
on='scopus_journal_id')
rf_citing_data['rf_citing_percent'] = rf_citing_data[
'rf_citing_value'] / rf_citing_data['rf_citing_sum']
rf_data = pd.merge(rf_cited_data,
rf_citing_data,
how='outer',
on=['scopus_journal_id', 'subject'])
rf_data.drop(columns=['cited_num', 'citing_num'], inplace=True)
rf_data = pd.merge(rf_data,
sum_cited_data,
how='left',
on='scopus_journal_id')
rf_data = pd.merge(rf_data,
sum_citing_data,
how='left',
on='scopus_journal_id')
rf_data.fillna(0, inplace=True)
rf_data['scopus_journal_id'] = rf_data['scopus_journal_id'].astype('int64')
journal_name_data = pd.read_excel(
'C:/Users/Administrator/Desktop/Journal Citation Score 2019带一级学科信息20200726.xlsx'
)
journal_name_data.drop_duplicates(subset=['Scopus Source ID'],
inplace=True,
ignore_index=True)
with open('core_journal.json', 'r', encoding='utf-8') as cj:
core_journal = json.load(cj)
journal_name_data_temp = journal_name_data.loc[:, [
'Scopus Source ID', 'Scholarly Output'
]]
journal_name_data_temp['Scopus Source ID'] = journal_name_data_temp[
'Scopus Source ID'].astype('str')
core_journal_article_num = {}
for subject, value in core_journal.items():
core_journal_article_num[subject] = sum(
journal_name_data_temp[journal_name_data_temp['Scopus Source ID'].
isin(value)]['Scholarly Output'])
rf_data['cited_citing_sum'] = rf_data['citing_num'] + rf_data['cited_num']
rf_data['cited_citing_percent_sum'] = rf_data[
'rf_cited_percent'] + rf_data['rf_citing_percent']
# 获取中文名称
journal_name_zh = pd.read_excel(
'C:/Users/Administrator/Desktop/期刊翻译结果.xlsx')
rf_data = pd.merge(rf_data,
journal_name_zh,
how='left',
on='scopus_journal_id')
# rf_data.to_excel('C:/Users/Administrator/Desktop/rf_data.xlsx', index=False)
rf_data.to_excel('C:/Users/Administrator/Desktop/rf_data_last.xlsx',
index=False)
rf_data_result = rf_data
core_journal_num_dict = {}
for subject, value in core_journal.items():
core_journal_num_dict[subject] = len(value)
rf_data_result['core_journal数量'] = rf_data_result['subject']
rf_data_result['core_journal数量'].replace(core_journal_num_dict,
inplace=True)
rf_data_result['core_journal数量'] = rf_data_result['core_journal数量'].astype(
'int64')
rf_data_result['core_journal发文数量'] = rf_data_result['subject']
rf_data_result['core_journal发文数量'].replace(core_journal_article_num,
inplace=True)
rf_data_result['core_journal发文数量'] = rf_data_result[
'core_journal发文数量'].astype('int64')
rf_data_result1 = copy.deepcopy(rf_data_result)
rf_data_result2 = copy.deepcopy(rf_data_result)
# 分学科结果，原始结果
# 合并core_journal学科
select_core_journal = pd.read_excel(
'C:/Users/Administrator/Desktop/core_journal-new.xlsx')
select_core_journal = select_core_journal.loc[
select_core_journal['Core journal'].notnull(),
['scopus_journal_id', 'Core journal']]
rf_data_result2 = pd.merge(rf_data_result2,
select_core_journal,
how='left',
on='scopus_journal_id')
rf_data_result2 = rf_data_result2.loc[
(rf_data_result2['cited_citing_percent_sum'] >= 0.4) |
(rf_data_result2['subject'] == rf_data_result2['Core journal'])]
# rf_data_result2.to_excel('C:/Users/Administrator/Desktop/分学科结果.xlsx', index=False)
rf_data_result2.to_excel('C:/Users/Administrator/Desktop/分学科结果last.xlsx',
index=False)
element = h_index.find(class_='fontLarge')
if element:
result_list.append(
[input_data[i][0], input_data[i][1], element.text])
# 结束循环
count = len(input_data)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
count = i
# 将已完成的部分进行数据写入
result_df = pd.DataFrame(data=result_list,
columns=['person_id', 'scopus_id', 'h_index'])
write2sql([['h_index', result_df]])
if __name__ == '__main__':
# 单元测试用
dbutil = DBUtil(host, port, database, username, password)
sql = 'select distinct person_id, scopus_id from author_info_new where ' \
'person_id not in (select person_id from h_index)'
author_id_df = dbutil.get_allresult(sql, 'df')
dbutil.close()
input_data = author_id_df.values.tolist()
crawl_h_index(input_data)
print('****** END ******')
# dbutil = DBUtil(host, port, database, username, password)
# sql = 'select * from wos_doc_data_copy'
# data = dbutil.get_allresult(sql, 'df')
# print('读取源数据完成')
# df = pd.read_excel('C:/Users/Administrator/Desktop/校名映射表.xlsx')
# data = pd.merge(data, df, how='left', on='orgName')
#
# print('merge完成')
# print('开始写入数据库')
# write2sql([['wos_doc_data0930', data]])
# print('写入数据库完成')
dbutil = DBUtil(host, port, database, username, password)
sql = 'select * from wos_doc_data_detail'
data = dbutil.get_allresult(sql, 'df')
print('读取源数据完成')
df = pd.read_excel('C:/Users/Administrator/Desktop/校名映射表.xlsx')
data = pd.merge(data, df, how='left', on='orgName')
data1 = data.loc[0:499999]
data2 = data.loc[500000:999999]
data3 = data.loc[1000000:1499999]
data4 = data.loc[1500000:1999999]
data5 = data.loc[2000000:2499999]
data6 = data.loc[2500000:2999999]
data7 = data.loc[3000000:]
data_list = [data1, data2, data3, data4, data5, data6, data7]
i = 0
})
cite_df_temp['cite_num'] = 1
cite_journal_data = cite_df_temp.groupby(
by=['cite_journal',
'cite_journal_id'], as_index=False).sum()
cite_journal_data['scopus_journal_id'] = input_data[i][0]
result_df_list.append(cite_journal_data)
count = len(input_data)
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
count = i
if result_df_list:
all_data = pd.concat(result_df_list)
write2sql([['scopus_cite_data0810', all_data]])
if __name__ == '__main__':
dbutil = DBUtil(host, port, database, username, password)
sql = 'select scopus_journal_id from scopus_journal_id where scopus_journal_id not ' \
'in (select distinct scopus_journal_id from scopus_cite_data0810) and cite_num!="0"'
journal_id_df = dbutil.get_allresult(sql, 'df')
dbutil.close()
input_data = journal_id_df.values.tolist()
# input_data = input_data[:5]
get_cite_data(input_data)
#! /usr/bin/python
# -*- coding: utf-8 -*-
import pandas as pd
from src.config.DBUtil import DBUtil
from src.Scopus_Crawler.scopus_config import host, port, database, username, password
dbutil = DBUtil(host, port, database, username, password)
sql = 'select * from wos_article_data'
already_df = dbutil.get_allresult(sql, 'df')
already_df.drop_duplicates(subset=['UT'], ignore_index=True, inplace=True)
dbutil.df_insert('wos_article_data_final', already_df)
dbutil.close()
data_df['orgName'] = input_data[i][0]
result_df_list.append(data_df)
count = len(input_data)
session.close()
# 出现错误时，从错误处中断，再从该处开始
except Exception as err:
print('ERROR:%s' % err)
session.close()
count = i
if result_df_list:
all_data_df = pd.concat(result_df_list)
write2sql([['wos_doc_data_detail', all_data_df]])
if __name__ == '__main__':
dbutil = DBUtil(host, port, database, username, password)
sql = 'select orgName, `key`, year, category_id, category_name from wos_doc_data_copy'
input_df = dbutil.get_allresult(sql, 'df')
input_df.drop_duplicates(
subset=['orgName', 'key', 'category_id', 'category_name'],
inplace=True)
dbutil.close()
input_data = input_df.values.tolist()
for rdd in range(9):
get_doc_data(input_data[5000 * rdd:5000 * rdd + 5000])
