Problems encountered in installing Fabric Explore - hyperledger-fabric

I installed it according to the guide on the official website.fabricexplorer But I may be having problems initializing the database.
MacOS
$ cd blockchain-explorer/app/persistence/fabric/postgreSQL/db
$ ./createdb.sh
$ createdb whoami
psql -c '\l'
List of databases
Name | Owner | Encoding | Collate | Ctype | Access privileges
----------------+----------+----------+---------+-------+-----------------------
fabricexplorer | hyy | UTF8 | C | C |
heyueyue | heyueyue | UTF8 | C | C |
postgres | postgres | UTF8 | C | C | =Tc/postgres +
| | | | | postgres=CTc/postgres
template0 | heyueyue | UTF8 | C | C | =c/heyueyue +
| | | | | heyueyue=CTc/heyueyue
template1 | heyueyue | UTF8 | C | C | =c/heyueyue +
| | | | | heyueyue=CTc/heyueyue
(5 rows)
heyueyue#heyueyuedeMacBook-Pro test-network % psql $DATABASE_DATABASE -c '\d'
Did not find any relations.
However, there are tables in the database fabricexplorer.
fabricexplorer-# \d
List of relations
Schema | Name | Type | Owner
--------+---------------------------+----------+-------
public | blocks | table | hyy
public | blocks_id_seq | sequence | hyy
public | chaincodes | table | hyy
public | chaincodes_id_seq | sequence | hyy
public | channel | table | hyy
public | channel_id_seq | sequence | hyy
public | orderer | table | hyy
public | orderer_id_seq | sequence | hyy
public | peer | table | hyy
public | peer_id_seq | sequence | hyy
public | peer_ref_chaincode | table | hyy
public | peer_ref_chaincode_id_seq | sequence | hyy
public | peer_ref_channel | table | hyy
public | peer_ref_channel_id_seq | sequence | hyy
public | transactions | table | hyy
public | transactions_id_seq | sequence | hyy
public | users | table | hyy
public | users_id_seq | sequence | hyy
public | write_lock | table | hyy
And I start the service , I can’t login with the correct user and password.
enter image description here
[2022-06-19T16:29:11.875] [DEBUG] PgService - the getRowsBySQlCase select * from channel where name=$1 and channel_genesis_hash=$2 and network_name = $3
Can anybody help?

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| email | adam.meyer#my-company.com | |
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| fax | | |
| room | | |
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I'm not an excel expert that's why I'm happy about every hint how to ease the preparation of the data for the import.
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Oh I see what you want now
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I have an excel sheet table with a structure like this:
+------------+-----+----------+----------+------------------+------------------+------------------+------------------+------------------+------------------+----------------+----------------+------------------+------------------+------------------+------------------+------------------+------------------+----------------+----------------+
| date | Day | StoreDdg | StoreR/H | DbgCategory1Dpt1 | R/HCategory1Dpt1 | DbgCategory2Dpt1 | R/HCategory2Dpt1 | DbgCategory3Dpt1 | R/HCategory2Dpt1 | DbgDepartment1 | R/HDepartment1 | DbgCategory1Dpt2 | R/HCategory1Dpt2 | DbgCategory2Dpt2 | R/HCategory2Dpt2 | DbgCategory3Dpt2 | R/HCategory2Dpt2 | DbgDepartment2 | R/HDepartment2 |
+------------+-----+----------+----------+------------------+------------------+------------------+------------------+------------------+------------------+----------------+----------------+------------------+------------------+------------------+------------------+------------------+------------------+----------------+----------------+
| 1-Jan-2017 | Sun | 138,894 | 133% | 500 | 44% | 12,420 | 146% | | | | 11,920 | 104% | #DIV/0! | 13,580 | 113% | 9,250 | 92% | 6,530 | 147% |
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+------------+-----+--------+-------------+---------------+---------+------+
| 1-Jan-2017 | Sun | Store1 | Department1 | Category1Dpt1 | 138,894 | 133% |
| 1-Jan-2017 | Sun | Store1 | Department1 | Category2Dpt1 | 500 | 44% |
| 1-Jan-2017 | Sun | Store1 | Department1 | Category3Dpt1 | 12,420 | 146% |
| 1-Jan-2017 | Sun | Store1 | Department2 | Category1Dpt2 | 11,920 | 104% |
| 1-Jan-2017 | Sun | Store1 | Department2 | Category2Dpt2 | 13,580 | 44% |
| 1-Jan-2017 | Sun | Store1 | Department2 | Category3Dpt2 | 9,250 | 92% |
| 2-Jan-2017 | Mon | Store1 | Department1 | Category1Dpt1 | 138,894 | 270% |
| 2-Jan-2017 | Mon | Store1 | Department1 | Category2Dpt1 | 500 | 136% |
| 2-Jan-2017 | Mon | Store1 | Department1 | Category3Dpt1 | 12,420 | 277% |
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| 2-Jan-2017 | Mon | Store1 | Department2 | Category2Dpt2 | 9,250 | 225% |
| 2-Jan-2017 | Mon | Store1 | Department2 | Category3Dpt2 | 6,530 | 181% |
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