Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,106 +1,106 @@
-import streamlit as st
-import json
-import pandas as pd
-import altair as alt
-
-# ---------------------------
-# CONFIG
-# ---------------------------
-FILE_PATH = "data_final_version.json"
-
-st.set_page_config(layout="wide")
-st.title("Dota Toxic Messages Dashboard")
-
-# ---------------------------
-# LOAD DATA
-# ---------------------------
-@st.cache_data
-def load_data():
-    with open(FILE_PATH, "r", encoding="utf-8") as f:
-        raw = json.load(f)
-    return pd.DataFrame(raw)
-
-df = load_data()
-
-# ---------------------------
-# CLEAN DATA
-# ---------------------------
-df["lobby_type"] = df["lobby_type"].fillna("Unknown")
-df["region"] = df["region"].fillna("Unknown")
-df["message_classified"] = df["message_classified"].fillna("unknown")
-
-# ---------------------------
-# SIDEBAR FILTERS
-# ---------------------------
-st.sidebar.header("Filters")
-
-regions = st.sidebar.multiselect(
-    "Region",
-    options=df["region"].unique(),
-    default=df["region"].unique()
-)
-
-lobbies = st.sidebar.multiselect(
-    "Lobby Type",
-    options=df["lobby_type"].unique(),
-    default=df["lobby_type"].unique()
-)
-
-df_filtered = df[
-    (df["region"].isin(regions)) &
-    (df["lobby_type"].isin(lobbies))
-]
-
-# ---------------------------
-# KPI
-# ---------------------------
-col1, col2, col3 = st.columns(3)
-
-col1.metric("Total Messages", len(df_filtered))
-col2.metric("Unique Matches", df_filtered["match_id"].nunique())
-col3.metric("Avg Duration", round(df_filtered["duration_game"].mean(), 1))
-
-# ---------------------------
-# CHART 1 - Toxic categories
-# ---------------------------
-st.subheader("Toxic Message Distribution")
-
-chart1 = alt.Chart(df_filtered).mark_bar().encode(
-    x=alt.X("count()", title="Count"),
-    y=alt.Y("message_classified", sort="-x", title="Category"),
-    color="message_classified"
-)
-
-st.altair_chart(chart1, use_container_width=True)
-
-# ---------------------------
-# CHART 2 - By Lobby Type
-# ---------------------------
-st.subheader("Toxicity by Lobby Type")
-
-chart2 = alt.Chart(df_filtered).mark_bar().encode(
-    x="lobby_type",
-    y="count()",
-    color="lobby_type"
-)
-
-st.altair_chart(chart2, use_container_width=True)
-
-# ---------------------------
-# CHART 3 - By Region
-# ---------------------------
-st.subheader("Toxicity by Region")
-
-chart3 = alt.Chart(df_filtered).mark_bar().encode(
-    x=alt.X("region", sort="-y"),
-    y="count()",
-    color="region"
-)
-
-st.altair_chart(chart3, use_container_width=True)
-
-# ---------------------------
-# RAW DATA (optional)
-# ---------------------------
-with st.expander("Show raw data"):
+import streamlit as st
+import json
+import pandas as pd
+import altair as alt
+
+# ---------------------------
+# CONFIG
+# ---------------------------
+FILE_PATH = "src/data_final_version.json"
+
+st.set_page_config(layout="wide")
+st.title("Dota Toxic Messages Dashboard")
+
+# ---------------------------
+# LOAD DATA
+# ---------------------------
+@st.cache_data
+def load_data():
+    with open(FILE_PATH, "r", encoding="utf-8") as f:
+        raw = json.load(f)
+    return pd.DataFrame(raw)
+
+df = load_data()
+
+# ---------------------------
+# CLEAN DATA
+# ---------------------------
+df["lobby_type"] = df["lobby_type"].fillna("Unknown")
+df["region"] = df["region"].fillna("Unknown")
+df["message_classified"] = df["message_classified"].fillna("unknown")
+
+# ---------------------------
+# SIDEBAR FILTERS
+# ---------------------------
+st.sidebar.header("Filters")
+
+regions = st.sidebar.multiselect(
+    "Region",
+    options=df["region"].unique(),
+    default=df["region"].unique()
+)
+
+lobbies = st.sidebar.multiselect(
+    "Lobby Type",
+    options=df["lobby_type"].unique(),
+    default=df["lobby_type"].unique()
+)
+
+df_filtered = df[
+    (df["region"].isin(regions)) &
+    (df["lobby_type"].isin(lobbies))
+]
+
+# ---------------------------
+# KPI
+# ---------------------------
+col1, col2, col3 = st.columns(3)
+
+col1.metric("Total Messages", len(df_filtered))
+col2.metric("Unique Matches", df_filtered["match_id"].nunique())
+col3.metric("Avg Duration", round(df_filtered["duration_game"].mean(), 1))
+
+# ---------------------------
+# CHART 1 - Toxic categories
+# ---------------------------
+st.subheader("Toxic Message Distribution")
+
+chart1 = alt.Chart(df_filtered).mark_bar().encode(
+    x=alt.X("count()", title="Count"),
+    y=alt.Y("message_classified", sort="-x", title="Category"),
+    color="message_classified"
+)
+
+st.altair_chart(chart1, use_container_width=True)
+
+# ---------------------------
+# CHART 2 - By Lobby Type
+# ---------------------------
+st.subheader("Toxicity by Lobby Type")
+
+chart2 = alt.Chart(df_filtered).mark_bar().encode(
+    x="lobby_type",
+    y="count()",
+    color="lobby_type"
+)
+
+st.altair_chart(chart2, use_container_width=True)
+
+# ---------------------------
+# CHART 3 - By Region
+# ---------------------------
+st.subheader("Toxicity by Region")
+
+chart3 = alt.Chart(df_filtered).mark_bar().encode(
+    x=alt.X("region", sort="-y"),
+    y="count()",
+    color="region"
+)
+
+st.altair_chart(chart3, use_container_width=True)
+
+# ---------------------------
+# RAW DATA (optional)
+# ---------------------------
+with st.expander("Show raw data"):
     st.dataframe(df_filtered)