diff --git a/scripts/tsne1.py b/scripts/tsne1.py
new file mode 100644
index 0000000..6d7011d
--- /dev/null
+++ b/scripts/tsne1.py
@@ -0,0 +1,67 @@
+import os
+import firebase_admin
+from firebase_admin import credentials
+from firebase_admin import firestore
+from google.cloud.firestore_v1.base_query import FieldFilter
+import pandas as pd
+from datetime import datetime
+import sys
+import matplotlib.pyplot as plt
+import numpy as np
+
+cred = credentials.Certificate(os.getcwd() + '/' + 'keys/hpos-qa-firebase-adminsdk.json')
+firebase_admin.initialize_app(cred)
+
+db = firestore.client()
+
+patient_collection = db.collection("patientData")
+test_collection = db.collection("testData")
+start_date = '2024-02-01' #sys.argv[1]
+end_date = '2024-02-25' #sys.argv[2] 
+
+query = test_collection.where(filter=FieldFilter("testTime", ">=", start_date)).where(filter=FieldFilter("testTime", "<", end_date))
+docs = query.stream()
+
+data = []
+for doc in docs:
+    doc_data = doc.to_dict()
+    data.append(doc_data)
+
+df = pd.DataFrame(data)
+print(df)
+print(df.size)
+
+
+import pandas as pd
+import matplotlib.pyplot as plt
+from sklearn.manifold import TSNE
+from sklearn.preprocessing import StandardScaler
+
+numeric_columns = ['led1Buffer', 'led3Average',
+       'led3Sample', 'led4Average', 'calculatedRatio',
+       'led4Sample', 'led2Sample', 'led3Buffer', 'deviceRatio',
+       'led1Sample', 'led1Average', 'led4Buffer', 'led2Average',
+       'led2Buffer']  #df.select_dtypes(include=[float, int]).columns
+print(numeric_columns)
+
+df_numeric = df[numeric_columns]#.dropna()
+df_numeric.replace([np.inf, -np.inf], np.nan, inplace=True)
+df_numeric.dropna(inplace=True)
+
+if df_numeric.shape[0] > 0:
+    scaler = StandardScaler()
+    df_standardized = pd.DataFrame(scaler.fit_transform(df_numeric), columns=df_numeric.columns)
+
+    tsne = TSNE(n_components=2, random_state=42)
+    df_tsne = tsne.fit_transform(df_standardized)
+
+    plt.scatter(df_tsne[:, 0], df_tsne[:, 1])
+    plt.title("t-SNE Visualization")
+    plt.xlabel("t-SNE Component 1")
+    plt.ylabel("t-SNE Component 2")
+    plt.show()
+else:
+    print("No samples found in the DataFrame after dropping NaN values.")
+
+firebase_admin.delete_app(firebase_admin.get_app())
+