Fix header parameter handling in sklearn's data_loader, update README…

… with new AUC (#2363)

* Fix header parameter of data_loader, update README with new AUC

* Fix header parameter in load_data and load_data_for_range functions

* Update header handling in load_data function by removing redundancy

* Fix formatting issues

* Remove read_json

---------

Co-authored-by: Ziyue Xu <[email protected]>
Co-authored-by: Chester Chen <[email protected]>
Co-authored-by: Yuan-Ting Hsieh (謝沅廷) <[email protected]>

examples/advanced/sklearn-svm/README.md

@@ -122,4 +122,4 @@ We can run the FL simulator with three clients under the uniform data split with
 bash run_experiment_simulator.sh
 ```
 Running with default [SVC](https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html) classifier, the 
-resulting global model's AUC is 0.806 which can be seen in the clients' logs.
+resulting global model's AUC is 0.8088 which can be seen in the clients' logs.

nvflare/app_opt/sklearn/data_loader.py

@@ -18,7 +18,6 @@
     "csv": pd.read_csv,
     "xls": pd.read_excel,
     "xlsx": pd.read_excel,
-    "json": pd.read_json,
 }
 
 
@@ -42,13 +41,10 @@ def get_pandas_reader(data_path: str):
 
 def load_data(data_path: str, require_header: bool = False):
     reader = get_pandas_reader(data_path)
-    if hasattr(reader, "header"):
-        if require_header:
-            data = reader(data_path)
-        else:
-            data = reader(data_path, header=None)
-    else:
+    if hasattr(reader, "header") and require_header:
         data = reader(data_path)
+    else:
+        data = reader(data_path, header=None)
 
     return _to_data_tuple(data)
 
@@ -58,11 +54,14 @@ def load_data_for_range(data_path: str, start: int, end: int, require_header: bo
 
     if hasattr(reader, "skiprows"):
         data_size = end - start
-        if hasattr(reader, "header") and not require_header:
-            data = reader(data_path, header=None, skiprows=start, nrows=data_size)
-        else:
+        if hasattr(reader, "header") and require_header:
             data = reader(data_path, skiprows=start, nrows=data_size)
+        else:
+            data = reader(data_path, header=None, skiprows=start, nrows=data_size)
     else:
-        data = reader(data_path).iloc[start:end]
+        if hasattr(reader, "header") and require_header:
+            data = reader(data_path).iloc[start:end]
+        else:
+            data = reader(data_path, header=None).iloc[start:end]
 
     return _to_data_tuple(data)