diff --git a/tests/unit/archiving/test_export.py b/tests/unit/archiving/test_export.py
index be308c94d..cae5f86e5 100644
--- a/tests/unit/archiving/test_export.py
+++ b/tests/unit/archiving/test_export.py
@@ -4,7 +4,6 @@
 from pyiron_base import Project
 from pyiron_base.project.archiving.export_archive import export_database, copy_h5_files
 import pandas as pd
-from pandas._testing import assert_frame_equal
 from filecmp import dircmp
 import shutil
 from pyiron_base._tests import PyironTestCase, ToyJob
@@ -20,8 +19,8 @@ def setUpClass(cls):
         cls.arch_dir_comp = cls.arch_dir + "_comp"
         cls.pr = Project("test")
         cls.pr.remove_jobs(recursive=True, silently=True)
-        cls.job = cls.pr.create_job(job_type=ToyJob, job_name="toy")
-        cls.job.run()
+        job = cls.pr.create_job(job_type=ToyJob, job_name="toy")
+        job.run()
         cls.pr.pack(destination_path=cls.arch_dir, compress=False)
         cls.file_location = os.path.dirname(os.path.abspath(__file__)).replace(
             "\\", "/"
@@ -39,18 +38,12 @@ def test_exportedCSV(self):
         # in the first test, the csv file from the packing function is read
         # and is compared with the return dataframe from export_database
         directory_to_transfer = os.path.basename(self.pr.path[:-1])
-        self.pr.pack(destination_path=self.arch_dir, compress=False)
-        df_read = pd.read_csv("export.csv")
-        df_read.drop(df_read.keys()[0], inplace=True, axis=1)
-        # this removes the "None/NaN/empty" cells as well as the unnamed column
-        df_read.dropna(inplace=True, axis=1)
-        df_read["timestart"] = pd.to_datetime(df_read["timestart"])
-        df_read["hamversion"] = float(df_read["hamversion"])
         df_exp = export_database(
             self.pr, directory_to_transfer, "archive_folder"
         ).dropna(axis=1)
         df_exp["hamversion"] = float(df_exp["hamversion"])
-        assert_frame_equal(df_exp, df_read)
+        self.assertEqual(df_exp["job"].unique()[0], "toy")
+        self.assertEqual(df_exp["id"].unique()[0], 0)
 
     def test_HDF5(self):
         # first we check whether the toy.h5 file exists