improve

app.py

@@ -1,6 +1,7 @@
 import os
 from datetime import datetime
 import json
+import matplotlib.ticker as ticker
 from huggingface_hub import snapshot_download
 from collections import defaultdict
 import pandas as pd
@@ -8,21 +9,18 @@ import streamlit as st
 from datetime import datetime, timedelta
 import matplotlib.pyplot as plt
 
-user_input = st.text_input("Enter your text here:")
-
 libraries = [
-    "open-source-metrics/accelerate-dependents",
-    "open-source-metrics/hub-docs-dependents",
-    "open-source-metrics/huggingface_hub-dependents",
-    "open-source-metrics/evaluate-dependents",
-    "open-source-metrics/datasets-dependents",
-    "open-source-metrics/pytorch-image-models-dependents",
-    "open-source-metrics/tokenizers-dependents",
     "open-source-metrics/transformers-dependents",
     "open-source-metrics/diffusers-dependents",
+    "open-source-metrics/pytorch-image-models-dependents",
+    "open-source-metrics/datasets-dependents",
     "open-source-metrics/gradio-dependents",
-    "open-source-metrics/optimum-dependents",
     "open-source-metrics/accelerate-dependents",
+    "open-source-metrics/evaluate-dependents",
+    "open-source-metrics/tokenizers-dependents",
+    "open-source-metrics/optimum-dependents",
+    "open-source-metrics/hub-docs-dependents",
+    "open-source-metrics/huggingface_hub-dependents",
 ]
 
 option = st.selectbox(
@@ -30,7 +28,7 @@ option = st.selectbox(
     libraries 
 )
 
-cached_folder = snapshot_download("open-source-metrics/transformers-dependents", repo_type="dataset")
+cached_folder = snapshot_download(option, repo_type="dataset")
 
 num_dependents = defaultdict(int)
 num_stars_all_dependents = defaultdict(int)
@@ -131,12 +129,22 @@ num_cum_stars_df.set_index('Date', inplace=True)
 num_cum_stars_df = num_cum_stars_df.resample('D').asfreq()
 num_cum_stars_df['Value'] = num_cum_stars_df['Value'].interpolate()
 
+filename = "_".join(option.split("/"))
+
 # Plotting
 plt.figure(figsize=(10, 6))
+plt.gca().yaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))
 plt.plot(num_dependents_df.index, num_dependents_df['Value'], marker='o')
 plt.xlabel('Date')
 plt.ylabel('Number of Dependents')
 plt.title('Dependencies History')
+st.pyplot(plt)
 
 # Display in Streamlit
+plt.figure(figsize=(10, 6))
+plt.gca().yaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))
+plt.plot(num_cum_stars_df.index, num_cum_stars_df['Value'], marker='o')
+plt.xlabel('Date')
+plt.ylabel('Cumulative number of stars of Dependents')
+plt.title('Dependents Stars History')
 st.pyplot(plt)