diff --git a/socat/ingest/textingest.py b/socat/ingest/textingest.py
index 4196483..d715393 100644
--- a/socat/ingest/textingest.py
+++ b/socat/ingest/textingest.py
@@ -1,7 +1,7 @@
 import pickle
 from pathlib import Path
 
-import numpy as np
+import pandas as pd
 from astropy import units as u
 from astropy.coordinates import ICRS
 
@@ -28,25 +28,10 @@ def ingest_text_file(
     number_of_sources: int
         The number of sources added to the catalog.
     """
-
-    table = np.loadtxt(
-        filename,
-        dtype=[("ra", "f8"), ("dec", "f8"), ("name", "S20"), ("monitored", "S20")],
-        skiprows=1,
-    )
-    names = [
-        name.decode("utf-8") if isinstance(name, (bytes, np.bytes_)) else name
-        for name in table["name"]
-    ]
-    table["name"] = names
-
-    table["monitored"] = [
-        bool(monitored.decode("utf-8")) for monitored in table["monitored"]
-    ]
-
+    table = pd.read_csv(filename)
     number_of_sources = 0
 
-    for row in table:
+    for index, row in table.iterrows():
         client.create_source(
             position=ICRS(
                 ra=float(row["ra"]) * u.deg,
diff --git a/tests/test_ingest.py b/tests/test_ingest.py
index 01da93d..0d194c6 100644
--- a/tests/test_ingest.py
+++ b/tests/test_ingest.py
@@ -5,6 +5,7 @@
 import os
 
 import numpy as np
+import pandas as pd
 from astropy import units as u
 from astropy.coordinates import ICRS
 from astropy.io import fits
@@ -44,15 +45,16 @@ def text_catalog(tmp_path):
     n_sources = 10
     data = np.zeros(
         n_sources,
-        dtype=[("ra", "f8"), ("dec", "f8"), ("name", "U20"), ("monitored", "S20")],
+        dtype=[("ra", "f8"), ("dec", "f8"), ("name", "U20"), ("monitored", "U20")],
     )
     data["ra"] = np.random.uniform(0, 360, n_sources)
     data["dec"] = np.random.uniform(-90, 90, n_sources)
     data["name"] = np.array([f"Source_{i}" for i in range(n_sources)], dtype="U20")
     data["monitored"] = np.random.choice(["True", "False"], size=n_sources)
 
+    data = pd.DataFrame(data)
     text_path = tmp_path / "text_catalog.txt"
-    np.savetxt(text_path, data, fmt="%f %f %s %s", header="ra dec name monitored")
+    data.to_csv(text_path, index=False)
 
     yield text_path