Update app.py

app.py

@@ -2,33 +2,64 @@ from datasets import load_dataset
 import streamlit as st
 import pandas as pd
 
-from huggingface_hub import HfFileSystem
-fs = HfFileSystem()
 
 # Load your dataset (replace 'your-dataset' with the actual dataset name)
 csv_url = 'https://huggingface.co/datasets/NENS/wim_data/resolve/main/input_employees/boran.csv'
 
-df = pd.read_csv('esther.csv')
+#df = pd.read_csv('esther.csv')
 
-st.write(df)
+#st.write(df)
 
-df.loc[df['week'] == 42, 'druk'] = 'heel druk'
+#df.loc[df['week'] == 42, 'druk'] = 'heel druk'
 
 
-hoi= fs.ls("datasets/NENS/wim_data/input_employees/", detail=False)
-st.write(hoi)
+#hoi= fs.ls("datasets/NENS/wim_data/input_employees/", detail=False)
+#st.write(hoi)
 
-button = st.button('do it')
+#button = st.button('do it')
 
-if button:
+#if button:
     
-    st.write(df)
+    #st.write(df)
 
-    with fs.open("datasets/NENS/wim_data/input_employees/esther.csv", "w") as f:
-        f.write("text,label")
-        f.write("Fantastic movie!,good")
+    #with fs.open("datasets/NENS/wim_data/input_employees/esther.csv", "w") as f:
+    #    f.write("text,label")
+    #    f.write("Fantastic movie!,good")
 
         #https://huggingface.co/datasets/NENS/wim_data/resolve/main/input_employees/esther.csv
     
     #df.to_csv("hf://spaces/NENS/test/test.csv")
-    print('het werkt!')
+    #print('het werkt!')
+
+
+from huggingface_hub import HfFileSystem
+import pandas as pd
+
+# Initialize HfFileSystem
+fs = HfFileSystem()
+
+# Define the path to your file in the Hugging Face Space
+remote_csv_path = "esther.csv"  # Path to the file in your repo
+
+# Step 1: Read the CSV file from your Hugging Face Space
+with fs.open(remote_csv_path, 'rb') as f:
+    df = pd.read_csv(f)
+
+print("Original DataFrame:")
+print(df)
+
+# Step 2: Make some changes to the DataFrame
+df.loc[df['week'] == 42, 'druk'] = 'heel druk'
+
+print("Modified DataFrame:")
+print(df)
+
+button = st.button('do it')
+
+if button:
+
+    # Step 3: Save the modified DataFrame back to a CSV file
+    with fs.open(remote_csv_path, 'wb') as f:
+        df.to_csv(f, index=False)
+    
+    print(f"Saved changes back to {remote_csv_path}")