diff --git a/docs/experiments/fourier_checking.ipynb b/docs/experiments/fourier_checking.ipynb
index d31a65c8016..335dbb8db28 100644
--- a/docs/experiments/fourier_checking.ipynb
+++ b/docs/experiments/fourier_checking.ipynb
@@ -279,11 +279,11 @@
     "for _ in range(number_of_functions_to_try):\n",
     "    dist, f = choose_random_function()\n",
     "    decision = randomized_alg(f, samples_size_per_function)\n",
-    "    res = res.append({\n",
-    "        \"Distribution\": dist,\n",
-    "        \"Decision\": decision,\n",
-    "        \"Count\": 1\n",
-    "    }, ignore_index=True)\n",
+    "    res=pd.concat([res, pd.DataFrame({\n",
+    "        \"Distribution\": [dist],\n",
+    "        \"Decision\":[decision],\n",
+    "        \"Count\": [1]\n",
+    "    })], ignore_index=True)\n",
     "confusion = res.pivot_table(index=\"Distribution\",\n",
     "                            columns=\"Decision\",\n",
     "                            values=\"Count\",\n",
@@ -322,12 +322,11 @@
     "        decision = randomized_alg(f, samples_size_per_function)\n",
     "        constant_minus_blanaced_count += 1 if decision == \"constant\" else -1\n",
     "    final_decision = \"constant\" if constant_minus_blanaced_count > 0 else \"balanced\"\n",
-    "    res = res.append(\n",
-    "        {\n",
-    "            \"Distribution\": dist,\n",
-    "            \"Decision\": final_decision,\n",
-    "            \"Count\": 1\n",
-    "        }, ignore_index=True)\n",
+    "    res=pd.concat([res, pd.DataFrame({\n",
+    "        \"Distribution\": [dist],\n",
+    "        \"Decision\":[final_decision],\n",
+    "        \"Count\": [1]\n",
+    "    })], ignore_index=True)\n",
     "confusion = res.pivot_table(index=\"Distribution\",\n",
     "                            columns=\"Decision\",\n",
     "                            values=\"Count\",\n",
@@ -867,18 +866,12 @@
     "    circuit = cirq.Circuit(fourier_checking_algorithm(qubits, fs, gs))\n",
     "    obs = s.run(circuit, repetitions=repetitions)\n",
     "    times_zero_was_measured = len(obs.data[obs.data[qubits_name] == 0])\n",
-    "    if times_zero_was_measured / repetitions > 0.05:\n",
-    "        res = res.append({\n",
-    "            \"Source\": source,\n",
-    "            \"Decision\": \"accept\",\n",
-    "            \"Count\": 1\n",
-    "        }, ignore_index=True)\n",
-    "    else:\n",
-    "        res = res.append({\n",
-    "            \"Source\": source,\n",
-    "            \"Decision\": \"reject\",\n",
-    "            \"Count\": 1\n",
-    "        }, ignore_index=True)\n",
+    "    decision = \"accept\" if times_zero_was_measured / repetitions > 0.05 else \"reject\"\n",
+    "    res=pd.concat([res, pd.DataFrame({\n",
+    "        \"Source\": [source],\n",
+    "        \"Decision\":[decision],\n",
+    "        \"Count\": [1]\n",
+    "    })], ignore_index=True)\n",
     "confusion = res.pivot_table(index=\"Source\", columns=\"Decision\", values=\"Count\", aggfunc=\"sum\")\n",
     "# Translate the counts into percentage\n",
     "confusion.div(confusion.sum(axis=1), axis=0).apply(lambda x: round(x, 4) * 100)"