Twitter API 検索の複数条件

TwitterのAPIを使用して、ある言葉と共に呟かれてる言葉の頻出分析をしております。

下記のコードで、複数の言葉を含む検索も可能でしょうか？

例）学校＆ひま　が両方含まれる検索方法

コード

#検索キーワード
q = "学校　 exclude:retweets"
date_since = "2020-01-01"
#データ取得
tweet_doc =[]
for tweet in tweepy.Cursor(api.search, q=q,tweet_mode="extended",since=date_since).items(500):
    tweet_doc.append(tweet.full_text)
import MeCab
def sep_by_mecab(text):
    m = MeCab.Tagger ('-Ochasen')    
    node = m.parseToNode(text)
    
    word_list=[]    
    while node:
        hinshi = node.feature.split(",")[0]
        if hinshi in ["名詞"]:
            origin = node.feature.split(",")[6]
            if origin not in ["*","する","いる","なる","てる","れる","ある","こと","もの","日","ん","な","の","大","ない","そう","いい","の","大"] :
                word_list.append(origin)
        node = node.next
        
    return word_list

documents=[]
for t in tweet_doc:
    documents.append(set(sep_by_mecab(t)))
import pyfpgrowth
import pprint
 
#分析
patterns = pyfpgrowth.find_frequent_patterns(documents, 5)
 
#降順に並び替えて見やすく表示
sorted_patterns = sorted(patterns.items(),reverse=True,key=lambda x:x[1])
pprint.pprint(sorted_patterns)
from collections import Counter
import pandas as pd
pd.set_option('display.unicode.east_asian_width', True)

lines =sorted_patterns

# 単語毎に頻度を積算
words = {}
for line in lines:
    for word in line[0]:
        if word not in words:
            words[word] = 0
        words[word] += line[1]

df = pd.DataFrame({'value':list(words.keys()), 'count':list(words.values())})
df = df.sort_values('count', ascending=False).reset_index(drop=True)
df = pd.DataFrame(df, columns=['単語', '件数'])
df.to_excel('pattern5.xlsx', index=None)

import pytablewriter
writer = pytablewriter.MarkdownTableWriter()
writer.from_dataframe(df.head())
writer.write_table()
import pandas as pd

df = pd.DataFrame(sorted_patterns, columns=['単語', '件数'])
df.to_excel('patterns6.xlsx', index=None)