Update app.py

app.py

@@ -1,13 +1,84 @@
 import gradio as gr
 
+# Capex in Millions of USD per Quarter of Microsoft, Google, Meta, Apple, Amazon
+big_five_capex: list[tuple[str, int, int, int, int, int]] = [
+   ("2014 Q3", 1282, 2417, 482, 3826, 1378),
+   ("2014 Q4", 1490, 3606, 517, 3217, 1145),
+   ("2015 Q1", 1391, 2927, 502, 2369, 871),
+   ("2015 Q2", 1781, 2515, 549, 2043, 1213),
+   ("2015 Q3", 1356, 2406, 780, 3618, 1195),
+   ("2015 Q4", 2024, 2102, 692, 3612, 1309),
+   ("2016 Q1", 2308, 2444, 1132, 2336, 1179),
+   ("2016 Q2", 2655, 2136, 995, 2809, 1711),
+   ("2016 Q3", 2163, 2554, 1095, 3977, 1841),
+   ("2016 Q4", 1988, 3078, 1269, 3334, 3073),
+   ("2017 Q1", 1695, 2508, 1271, 2975, 2148),
+   ("2017 Q2", 2283, 2831, 1444, 2277, 3113),
+   ("2017 Q3", 2132, 3538, 1755, 3865, 3074),
+   ("2017 Q4", 2586, 4307, 2263, 2810, 3619),
+   ("2018 Q1", 2934, 7299, 2812, 4195, 3098),
+   ("2018 Q2", 3980, 5477, 3460, 3267, 3243),
+   ("2018 Q3", 3602, 5282, 3342, 3041, 3352),
+   ("2018 Q4", 3707, 7081, 4301, 3355, 3734),
+   ("2019 Q1", 2565, 4638, 3837, 2363, 3290),
+   ("2019 Q2", 4051, 6126, 3633, 2000, 3562),
+   ("2019 Q3", 3385, 6732, 3532, 2777, 4697),
+   ("2019 Q4", 3545, 6052, 4100, 2107, 5312),
+   ("2020 Q1", 3767, 6005, 3558, 1853, 6795),
+   ("2020 Q2", 4744, 5391, 3255, 1565, 7459),
+   ("2020 Q3", 4907, 5406, 3689, 1784, 11063),
+   ("2020 Q4", 4174, 5479, 4613, 3500, 14823),
+   ("2021 Q1", 5089, 5942, 4303, 2269, 12082),
+   ("2021 Q2", 6452, 5496, 4641, 2093, 14288),
+   ("2021 Q3", 5810, 6819, 4346, 3223, 15748),
+   ("2021 Q4", 5865, 6383, 5400, 2803, 18935),
+   ("2022 Q1", 5340, 9786, 5441, 2514, 14951),
+   ("2022 Q2", 6871, 6828, 7572, 2102, 15724),
+   ("2022 Q3", 6283, 7276, 9375, 3289, 16378),
+   ("2022 Q4", 6274, 7595, 9043, 3787, 16592),
+   ("2023 Q1", 6607, 6289, 6823, 2916, 14207),
+   ("2023 Q2", 8943, 6888, 6134, 2093, 11455),
+   ("2023 Q3", 9917, 8055, 6543, 2163, 12479),
+   ("2023 Q4", 9735, 11019, 7665, 2392, 14588),
+   ("2024 Q1", 10952, 12012, 6400, 1996, 14925),
+   ("2024 Q2", 13873, 13186, 8173, 2151, 17620),
+]
+
+
+def create_chart():
+    df = pd.DataFrame(big_five_capex, columns=['Quarter', 'Microsoft', 'Google', 'Meta', 'Apple', 'Amazon'])
+    
+    fig = go.Figure()
+    
+    companies = ['Microsoft', 'Google', 'Meta', 'Apple', 'Amazon']
+    colors = ['#00a1f1', '#3cba54', '#1877f2', '#a2aaad', '#ff9900']
+    
+    for company, color in zip(companies, colors):
+        fig.add_trace(go.Bar(
+            x=df['Quarter'],
+            y=df[company],
+            name=company,
+            marker_color=color
+        ))
+    
+    fig.update_layout(
+        title='Capital Expenditure of the Big Five Tech Companies (Millions of USD per Quarter)',
+        xaxis_title='Quarter',
+        yaxis_title='Capex (Millions of USD)',
+        barmode='stack',
+        legend_title='Companies',
+        width=1200,
+        height=700
+    )
+
+    return fig
+
 
 with gr.Blocks() as demo:
-    with gr.Tab("Lion"):
-        gr.Image("lion.jpg")
-        gr.Button("New Lion")
-    with gr.Tab("Tiger"):
-        gr.Image("tiger.jpg")
-        gr.Button("New Tiger")
+    with gr.Tab("Big Five Capex"):
+        big_five_capex_plot: gr.Plot = gr.Plot()
+        generate_btn = gr.Button("Generate Plot")
+    generate_btn.click(fn=create_step_chart, outputs=plot_output)
 
 
 if __name__ == "__main__":