diff --git a/shiny/api-examples/input_file/app.py b/shiny/api-examples/input_file/app.py
index 7038bf6de..a6134cb34 100644
--- a/shiny/api-examples/input_file/app.py
+++ b/shiny/api-examples/input_file/app.py
@@ -1,31 +1,54 @@
 import pandas as pd
 
-from shiny import App, Inputs, Outputs, Session, render, ui
+from shiny import App, Inputs, Outputs, Session, reactive, render, ui
 from shiny.types import FileInfo
 
 app_ui = ui.page_fluid(
-    ui.layout_sidebar(
-        ui.panel_sidebar(
-            ui.input_file("file1", "Choose CSV File", accept=[".csv"], multiple=False),
-            ui.input_checkbox("header", "Header", True),
-            width=5,
-        ),
-        ui.panel_main(
-            ui.output_ui("contents"),
-        ),
+    ui.input_file("file1", "Choose CSV File", accept=[".csv"], multiple=False),
+    ui.input_checkbox_group(
+        "stats",
+        "Summary Stats",
+        choices=["Row Count", "Column Count", "Column Names"],
+        selected=["Row Count", "Column Count", "Column Names"],
     ),
+    ui.output_table("summary"),
 )
 
 
 def server(input: Inputs, output: Outputs, session: Session):
+    @reactive.Calc
+    def parsed_file():
+        file: list[FileInfo] = input.file1()
+        if file is None:
+            return pd.DataFrame()
+        return pd.read_csv(file[0]["datapath"])
+
     @output
-    @render.ui
-    def contents():
-        if input.file1() is None:
-            return "Please upload a csv file"
-        f: list[FileInfo] = input.file1()
-        df = pd.read_csv(f[0]["datapath"], header=0 if input.header() else None)
-        return ui.HTML(df.to_html(classes="table table-striped"))
+    @render.table
+    def summary():
+        df = parsed_file()
+
+        if df.empty:
+            return pd.DataFrame()
+
+        # Get the row count, column count, and column names of the DataFrame
+        row_count = df.shape[0]
+        column_count = df.shape[1]
+        names = df.columns.tolist()
+        column_names = ", ".join(str(name) for name in names)
+
+        # Create a new DataFrame to display the information
+        info_df = pd.DataFrame(
+            {
+                "Row Count": [row_count],
+                "Column Count": [column_count],
+                "Column Names": [column_names],
+            }
+        )
+
+        # input.stats() is a list of strings; subset the columns based on the selected
+        # checkboxes
+        return info_df.loc[:, input.stats()]
 
 
 app = App(app_ui, server)
diff --git a/shiny/examples/input_file/app.py b/shiny/examples/input_file/app.py
new file mode 100644
index 000000000..d7bb420db
--- /dev/null
+++ b/shiny/examples/input_file/app.py
@@ -0,0 +1,53 @@
+import pandas as pd
+
+from shiny import App, reactive, render, ui
+
+app_ui = ui.page_fluid(
+    ui.input_file("file1", "Upload a CSV file", accept=".csv"),
+    ui.input_checkbox_group(
+        "stats",
+        "Summary Stats",
+        choices=["Row Count", "Column Count", "Column Names"],
+        selected=["Row Count", "Column Count", "Column Names"],
+    ),
+    ui.output_table("summary"),
+)
+
+
+def server(input: Inputs, output: Outputs, session: Session):
+    @reactive.Calc
+    def parsed_file():
+        file: list[FileInfo] = input.file1()
+        if file is None:
+            return pd.DataFrame()
+        return pd.read_csv(file[0]["datapath"])
+
+    @output
+    @render.table
+    def summary():
+        df = parsed_file()
+
+        if df.empty:
+            return pd.DataFrame()
+
+        # Get the row count, column count, and column names of the DataFrame
+        row_count = df.shape[0]
+        column_count = df.shape[1]
+        names = df.columns.tolist()
+        column_names = ", ".join(str(name) for name in names)
+
+        # Create a new DataFrame to display the information
+        info_df = pd.DataFrame(
+            {
+                "Row Count": [row_count],
+                "Column Count": [column_count],
+                "Column Names": [column_names],
+            }
+        )
+
+        # input.stats() is a list of strings; subset the columns based on the selected
+        # checkboxes
+        return info_df.loc[:, input.stats()]
+
+
+app = App(app_ui, server)