Create app.py

app.py

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+import pandas as pd
+import gradio as gr
+
+
+URL = "https://docs.google.com/spreadsheets/d/1pJPFxqbWeASWi4KZAPf7Go7b46y_7sHePmf-vPRD67I/edit?usp=sharing"
+csv_url = URL.replace('/edit?usp=', '/export?format=csv&usp=')
+
+def get_data():
+  df = pd.read_csv(csv_url)
+  df['Tweet Volume'] = df['Tweet Volume'].str[:-1]
+  df['Tweet Volume'] = df['Tweet Volume'].transform( lambda x: x[-2:] if 'Under' in x else x)
+  df['Trending Topic / Hashtag'] = df['Trending Topic / Hashtag'].transform( lambda x: x.split()[0])
+  df["Tweet Volume"] = pd.to_numeric(df["Tweet Volume"])
+  df = df.sort_values(by=['Tweet Volume'], ascending=False)
+  return df[["Trending Topic / Hashtag",	"Tweet Volume"]][:15]
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 📈 Twitter Trends - Qatar using Real-Time Line and Scatter Plot")
+    gr.Markdown("Following are the current top twitter trending topics in Qatar, Trends last updated every 30 minutes !")
+    with gr.Row():
+            gr.LinePlot(get_data, x="Trending Topic / Hashtag", y="Tweet Volume", tooltip=["Trending Topic / Hashtag","Tweet Volume"] , every=5, overlay_point=True, width=500, height=500, title='Real-Time Line Plot')
+            gr.ScatterPlot(get_data, y="Tweet Volume", x="Trending Topic / Hashtag",  tooltip=["Trending Topic / Hashtag","Tweet Volume"] , every=5,  width=500, height=500, title='Real-Time Scatter Plot')
+    with gr.Row():
+        gr.DataFrame(get_data, every=5)
+demo.queue().launch()  # Run the demo with queuing enabled