Update app.py

app.py

@@ -1,12 +1,14 @@
+from pathlib import Path
 from typing import Optional, Tuple
 
 import gradio as gr
+import matplotlib.pyplot as plt
+import numpy as np
 import pandas as pd
-from pathlib import Path
+import plotly.graph_objects as go
 import seaborn as sns
-import matplotlib.pyplot as plt
 from wordcloud import WordCloud
-import numpy as np
+
 
 def _rename_columns(df: pd.DataFrame, is_tournament: bool) -> pd.DataFrame:
     columns = {
@@ -49,6 +51,9 @@ def _fix_dtypes(df: pd.DataFrame, is_tournament: bool) -> pd.DataFrame:
 
     return df
 
+def snake_case_to_human_readable(s: str) -> str:
+    return " ".join(s.capitalize().split("_"))
+
 def make_df_columns_readable(df: Optional[pd.DataFrame], is_tournament: bool) -> Optional[pd.DataFrame]:
     """Make a data frame's columns human-readable."""
     if df is None:
@@ -83,7 +88,7 @@ def make_df_columns_readable(df: Optional[pd.DataFrame], is_tournament: bool) ->
             df['event_date'] = df['event_date'].dt.date.astype(str).apply(nat_to_none)
         df = df.rename(columns={"league_name": "league"})
 
-    df = df.rename(columns=lambda c: " ".join(c.capitalize().split("_")))
+    df = df.rename(columns=lambda c: snake_case_to_human_readable(c))
     return df
 
 def _check_match_type(match_type: str) -> str:
@@ -125,15 +130,21 @@ def get_opponent_name_word_cloud_fig(df: pd.DataFrame):
 
 
 def get_rating_over_time_fig(df: pd.DataFrame, is_tournament: bool):
-    fig = plt.figure()
-    plt.title('Rating over time')
-    sns.lineplot(data=df,
-                 x="tournament_end_date" if is_tournament else "event_date",
-                 y="rating",
-                 marker='.',
-                 markersize=10)
-    plt.xlabel('Competition date')
-    plt.ylabel('Rating')
+    fig = go.Figure()
+    fig.add_trace(go.Scatter(x=df["tournament_end_date" if is_tournament else "event_date"],
+                             y=df["rating"],
+                             mode='lines+markers',
+                             line=dict( width=0.9),
+                             marker=dict(size=4))),
+
+    fig.update_layout(
+        title='Rating over time',
+        xaxis_title='Competition date',
+        yaxis_title='Rating',
+        showlegend=False,
+        template="plotly_white",
+    )
+
     return fig
 
 
@@ -208,6 +219,7 @@ def get_opponent_rating_dist_over_time_fig(df: pd.DataFrame, is_tournament: bool
                    inner='points',
                    cut=1,
                    ax=ax)
+    plt.xticks(rotation=30)
     plt.xlabel('Competition year')
     plt.ylabel('Opponent rating')
     return fig
@@ -262,7 +274,9 @@ def usatt_rating_analyzer(file_obj):
 with gr.Blocks() as demo:
     analyze_btn_title = "Analyze"
     gr.Markdown(f"""# USATT rating analyzer
-    Analyze [USA table tennis](https://www.teamusa.org/usa-table-tennis) tournament and league results. 
+    Analyze [USA table tennis](https://www.teamusa.org/usa-table-tennis) tournament and league results. The more matches
+     and competitions you have played, the better the tool works. Additionally, due to limitations on the available 
+    data, ratings are always displayed as the rating received *after* the competition has been played.
     ## Downloading match results
     1. Make sure you are [logged in](https://usatt.simplycompete.com/login/auth) to your USATT account.
     2. Find the *active* player you wish to analyze (e.g.,  [Kanak Jha](https://usatt.simplycompete.com/userAccount/up/3431)).