diff --git a/antarest/study/service.py b/antarest/study/service.py
index d394056f95..a0b447bf20 100644
--- a/antarest/study/service.py
+++ b/antarest/study/service.py
@@ -1600,6 +1600,7 @@ def _create_edit_study_command(
                         # Can happen with data with only one column. In this case, we don't care about the delimiter.
                         delimiter = "\t"
                     df = pd.read_csv(io.BytesIO(data), delimiter=delimiter, header=None).replace(",", ".", regex=True)
+                    df = df.dropna(axis=1, how="all")  # We want to remove columns full of NaN at the import
                     matrix = df.to_numpy(dtype=np.float64)
                 matrix = matrix.reshape((1, 0)) if matrix.size == 0 else matrix
                 return ReplaceMatrix(
diff --git a/tests/integration/raw_studies_blueprint/test_fetch_raw_data.py b/tests/integration/raw_studies_blueprint/test_fetch_raw_data.py
index e30e929a0b..967a43b6f1 100644
--- a/tests/integration/raw_studies_blueprint/test_fetch_raw_data.py
+++ b/tests/integration/raw_studies_blueprint/test_fetch_raw_data.py
@@ -212,18 +212,20 @@ def test_get_study_data(self, client: TestClient, user_access_token: str, intern
                 b"\xef\xbb\xbf1;1;1;1;1\r\n1;1;1;1;1",
                 b"1;1;1;1;1\r1;1;1;1;1",
                 b"0,000000;0,000000;0,000000;0,000000\n0,000000;0,000000;0,000000;0,000000",
+                b"1;2;3;;;\n4;5;6;;;\n",
             ],
-            ["\t", "\t", ",", "\t", ";", ";", ";"],
+            ["\t", "\t", ",", "\t", ";", ";", ";", ";"],
         ):
             res = client.put(raw_url, params={"path": matrix_path}, files={"file": io.BytesIO(content)})
             assert res.status_code == 204, res.json()
             res = client.get(raw_url, params={"path": matrix_path})
             written_data = res.json()["data"]
             if not content.decode("utf-8"):
-                # For some reason the `GET` returns the default matrix when it's empty
+                # The `GET` returns the default matrix when it's empty
                 expected = 8760 * [[0]] if study_type == "raw" else [[]]
             else:
                 df = pd.read_csv(io.BytesIO(content), delimiter=delimiter, header=None).replace(",", ".", regex=True)
+                df = df.dropna(axis=1, how="all")  # We want to remove columns full of NaN at the import
                 expected = df.to_numpy(dtype=np.float64).tolist()
             assert written_data == expected