v2.7 directory structure adjustments

Procfile

@@ -0,0 +1 @@
+web: panel serve --address="0.0.0.0" --port=$PORT src/campaign_dashboard/starbound_dashboard src/campaign_dashboard/protea_dashboard --allow-websocket-origin=campaign-dashboard.herokuapp.com

README.md

@@ -2,7 +2,8 @@
 
 ![Python Badge](https://img.shields.io/badge/Python-FFD43B?style=for-the-badge&logo=python&logoColor=blue) ![Jupyter Badge](https://img.shields.io/badge/Jupyter-F37626.svg?&style=for-the-badge&logo=Jupyter&logoColor=white) ![Pandas](https://img.shields.io/badge/pandas-%23150458.svg?style=for-the-badge&logo=pandas&logoColor=white) ![Plotly](https://img.shields.io/badge/Plotly-%233F4F75.svg?style=for-the-badge&logo=plotly&logoColor=white)
 
-Live: https://sparkcity.github.io/campaign_dashboard/app.html
+Static Github Pages Deployment: https://sparkcity.github.io/campaign_dashboard/app.html
+Full Heroku Deployment: https://campaign-dashboard-5fce31c398a9.herokuapp.com/
 
 A dashboard webapp built to display data visualizations related to the ongoing Dungeons & Dragons campaign I play in with my friends.
 

requirements.txt

@@ -1,4 +1,7 @@
 hvplot
 jupyterlab
 openpyxl
-pyparsing
+pyparsing
+pandas
+python
+plotly

src/campaign_dashboard/atlas_dashboard.py

@@ -0,0 +1,300 @@
+################################# Imports and Initializations
+
+import pandas as pd
+import panel as pn
+import plotly.express as px
+
+ACCENT = "#A9A9A9"
+
+SUCCESS_SOLID_BUTTON_STYLE = f"""
+.bk-btn-success {{
+    background-color: var(--accent-foreground-rest, {ACCENT});
+}}
+.bk-active.bk-btn-success {{
+    background-color: var(--accent-foreground-active, {ACCENT});
+}}
+.bk-btn-success:hover {{
+    background-color: var(--accent-foreground-hover, {ACCENT});
+}}
+"""
+
+pn.extension("plotly", "tabulator", sizing_mode="stretch_width")
+
+combat_df = pd.DataFrame(
+    pd.read_csv(
+        "https://raw.githubusercontent.com/sparkcity/campaign_dashboard/main/src/data/starbound/starbound_combat.csv"
+    )
+)
+rolls_df = pd.DataFrame(
+    pd.read_csv(
+        "https://raw.githubusercontent.com/sparkcity/campaign_dashboard/main/src/data/starbound/starbound_rolls.csv"
+    )
+)
+attr_df = pd.DataFrame(
+    pd.read_csv(
+        "https://raw.githubusercontent.com/sparkcity/campaign_dashboard/main/src/data/starbound/starbound_attr.csv"
+    )
+)
+stats_df = pd.DataFrame(
+    pd.read_csv(
+        "https://raw.githubusercontent.com/sparkcity/campaign_dashboard/main/src/data/starbound/starbound_pcs.csv"
+    )
+)
+
+pc_color_map = {
+    "Sparrow": "#118ab2",
+    "Madaine": "#073b4c",
+    "Evelyn": "#06d6a0",
+    "Pollux": "#ffd166",
+    "Trey": "#ef476f",
+}
+
+sess_min = (rolls_df["session"].min()).item()
+sess_max = (rolls_df["session"].max()).item()
+
+################################# Party Visualizations: Context and Overall Rolls
+
+##### Replace the below with the commented section in app.js
+party_dist_df = pd.DataFrame(rolls_df["roll_base"].value_counts()).reset_index()
+
+party_dist_fig = px.bar(
+    party_dist_df,
+    x="roll_base",
+    y="count",
+    color="count",
+    title="Party Rolls Distribution",
+)
+party_dist_fig.update_xaxes(tickmode="linear")
+
+##### For whatever reason, the following has to be uncommented manually in app.js
+##### to replace the above to work because the dataframe reset_index doesn't work properly
+##### instead of making a df with cols ['roll_base','count'],
+##### it always creates df with cols ['index' (should be roll _base),'roll_base' (should be count)]
+
+# party_dist_df = pd.DataFrame(rolls_df["roll_base"].value_counts()).reset_index()
+
+# party_dist_fig = px.bar(
+#  party_dist_df,
+#    x="index",
+#    y="roll_base",
+#    color="roll_base",
+#    labels={'index':'roll_base','roll_base':'count'},
+#    title="Party Rolls Distribution",
+# )
+# party_dist_fig.update_xaxes(tickmode="linear")
+
+party_context_df = (
+    rolls_df.groupby(["pc", "context"]).size().unstack(fill_value=0).reset_index()
+)
+party_context_fig = px.bar(
+    party_context_df,
+    x="pc",
+    y=["Combat", "Exploration", "Social"],
+    title="All Rolls Per Character By Context",
+)
+party_context_fig.update_layout(autosize=True)
+
+party_box = pn.WidgetBox(
+    pn.Column(
+        pn.Row(pn.pane.Markdown(f"# Party Visualizations")),
+        pn.Row(party_dist_fig),
+        pn.Row(party_context_fig),
+    )
+)
+
+################################# Party Visualizations: Total Combat Stats Per Character
+select_combat_stat = pn.widgets.ToggleGroup(
+    name="Combat Stat Selection",
+    options=["dmg_taken", "dmg_dealt", "dmg_mitigated", "dmg_healed"],
+    behavior="radio",
+    value="dmg_taken",
+)
+
+
+def total_combat_stat(cntxt):
+    gb = combat_df.groupby("pc").sum().reset_index()
+
+    fig = px.bar(
+        gb,
+        x="pc",
+        y=cntxt,
+        color="pc",
+        color_discrete_map=pc_color_map,
+        title=f"Total {cntxt} Per Character",
+    )
+    return fig
+
+
+def total_combat_stat_per_session(cntxt):
+    fig = px.line(
+        combat_df,
+        x="session",
+        y=cntxt,
+        color="pc",
+        color_discrete_map=pc_color_map,
+        markers=True,
+        hover_data=["combat_blurb"],
+        title=f"{cntxt} Per Character Per Session",
+    )
+    return fig
+
+
+party_combat_box = pn.WidgetBox(
+    pn.Column(
+        pn.Row(pn.pane.Markdown(f"# Party Combat Visualizations")),
+        pn.Row(select_combat_stat),
+        pn.Row(pn.bind(total_combat_stat, select_combat_stat)),
+        pn.Row(pn.bind(total_combat_stat_per_session, select_combat_stat)),
+        align="start",
+        sizing_mode="stretch_width",
+    )
+)
+
+################################# Individual Visualizations
+
+select_pc = pn.widgets.ToggleGroup(
+    name="Combat Stat Selection",
+    options=["Sparrow", "Madaine", "Trey", "Pollux", "Evelyn"],
+    behavior="radio",
+    value="Sparrow",
+)
+
+
+def stat_radar(nm):
+    df = stats_df.loc[stats_df["pc"] == nm]
+    pc_r = [
+        df["str"].item(),
+        df["dex"].item(),
+        df["con"].item(),
+        df["int"].item(),
+        df["wis"].item(),
+        df["cha"].item(),
+    ]
+    pc_theta = ["str", "dex", "con", "int", "wis", "cha"]
+
+    fig = px.scatter_polar(df, title="Stats", r=pc_r, theta=pc_theta)
+    fig.update_traces(fill="toself")
+    return fig
+
+
+def pc_sum(nm):
+    df = stats_df.loc[stats_df["pc"] == nm]
+    c_df = combat_df.loc[combat_df["pc"] == nm]
+
+    lvl = df["lvl"].item()
+    rc = df["race"].item()
+    cls = df["class"].item()
+    arctps = df["archetypes"].item()
+
+    if type(arctps) == float:
+        description = f"{nm} is a level {lvl} {rc} {cls} with no Archetypes."
+    else:
+        description = f"{nm} is a level {lvl} {rc} {cls} with Archetypes in {arctps}."
+
+    mx_dmg_dlt = c_df.loc[c_df["dmg_dealt"].idxmax()]
+    dmg_dlt = f"{mx_dmg_dlt['dmg_dealt']} damage dealt in Session {mx_dmg_dlt['session']}. </br> Combat encounter summary: {mx_dmg_dlt['combat_blurb']}"
+    mx_dmg_tkn = c_df.loc[c_df["dmg_taken"].idxmax()]
+    dmg_tkn = f"{mx_dmg_tkn['dmg_taken']} damage taken in Session {mx_dmg_tkn['session']}. </br> Combat encounter summary: {mx_dmg_tkn['combat_blurb']}"
+    mx_dmg_mtg = c_df.loc[c_df["dmg_mitigated"].idxmax()]
+    dmg_mtg = f"{mx_dmg_mtg['dmg_mitigated']} damage mitigated in Session {mx_dmg_mtg['session']}. </br> Combat encounter summary: {mx_dmg_mtg['combat_blurb']}"
+    mx_dmg_hld = c_df.loc[c_df["dmg_mitigated"].idxmax()]
+    dmg_hld = f"{mx_dmg_hld['dmg_healed']} damage healed in Session {mx_dmg_hld['session']}. </br> Combat encounter summary: {mx_dmg_hld['combat_blurb']}"
+    other = f"Total Successful Attacks: {c_df['atks_success'].sum()} </br> Total Failed Attacks: {c_df['atks_fail'].sum()} </br> Total Spells Cast: {c_df['spells_cast'].sum()} </br>Total Final Blows: {c_df['final_blows'].sum()}"
+
+    pane = pn.pane.Markdown(
+        f"""
+        # Character Highlights: {nm}
+        | Category      | Info |
+        | ----------- | ----------- |
+        | **Description**| {description}|
+        | **Most Damage Dealt** | {dmg_dlt}|
+        | **Most Damage Taken**| {dmg_tkn}|
+        | **Most Damage Mitigated**|{dmg_mtg}|
+        | **Most Damage Healed**|{dmg_hld}|
+        | **Other**| {other} |
+        """
+    )
+    return pane
+
+
+def attr_radar(nm):
+    df = attr_df.loc[stats_df["pc"] == nm]
+    pc_r = [
+        df["acrobatics"].item(),
+        df["animal_handling"].item(),
+        df["arcana"].item(),
+        df["athletics"].item(),
+        df["deception"].item(),
+        df["history"].item(),
+        df["insight"].item(),
+        df["intimidation"].item(),
+        df["investigation"].item(),
+        df["medicine"].item(),
+        df["nature"].item(),
+        df["perception"].item(),
+        df["performance"].item(),
+        df["persuasion"].item(),
+        df["religion"].item(),
+        df["sleight_of_hand"].item(),
+        df["stealth"].item(),
+        df["survival"].item(),
+    ]
+
+    pc_theta = [
+        "acrobatics",
+        "animal_handling",
+        "arcana",
+        "athletics",
+        "deception",
+        "history",
+        "insight",
+        "intimidation",
+        "investigation",
+        "medicine",
+        "nature",
+        "perception",
+        "performance",
+        "persuasion",
+        "religion",
+        "sleight_of_hand",
+        "stealth",
+        "survival",
+    ]
+
+    fig = px.scatter_polar(df, title="Skill Bonuses", r=pc_r, theta=pc_theta)
+    fig.update_traces(fill="toself")
+    return fig
+
+
+ind_box = pn.WidgetBox(
+    pn.Column(
+        pn.Row(pn.pane.Markdown(f"# Individual Visualizations")),
+        pn.Row(select_pc),
+        pn.Row(pn.bind(pc_sum, select_pc), pn.bind(stat_radar, select_pc)),
+        pn.Row(pn.bind(attr_radar, select_pc)),
+        align="start",
+        sizing_mode="stretch_width",
+    )
+)
+
+################################# Layout Template
+
+template = pn.template.FastListTemplate(
+    title="Atlassian Campaign Visualizations",
+    sidebar=[
+        pn.pane.Markdown("## Dashboard"),
+        pn.pane.PNG(
+            "https://raw.githubusercontent.com/sparkcity/campaign_dashboard/main/img/thorns_logo.png",
+            sizing_mode="scale_both",
+        ),
+        pn.pane.Markdown(
+            f"""Earliest Session Data Available: {sess_min}
+             <br/>Latest Session Data Available: {sess_max}"""
+        ),
+    ],
+    main=[pn.Row(party_box), pn.Row(party_combat_box), pn.Row(ind_box)],
+    main_max_width="1000px",
+    accent=ACCENT,
+    theme_toggle=False,
+)
+template.servable()

src/campaign_dashboard/dashboard_functions.py

@@ -0,0 +1,60 @@
+import pandas as pd
+import panel as pn
+import plotly.express as px
+
+
+def stat_radar(nm, stats_df):
+    df = stats_df.loc[stats_df["pc"] == nm]
+    pc_r = [
+        df["str"].item(),
+        df["dex"].item(),
+        df["con"].item(),
+        df["int"].item(),
+        df["wis"].item(),
+        df["cha"].item(),
+    ]
+    pc_theta = ["str", "dex", "con", "int", "wis", "cha"]
+
+    fig = px.scatter_polar(df, title="Stats", r=pc_r, theta=pc_theta)
+    fig.update_traces(fill="toself")
+    return fig
+
+
+def pc_sum(nm, stats_df, combat_df):
+    df = stats_df.loc[stats_df["pc"] == nm]
+    c_df = combat_df.loc[combat_df["pc"] == nm]
+
+    lvl = df["lvl"].item()
+    rc = df["race"].item()
+    cls = df["class"].item()
+    arctps = df["archetypes"].item()
+
+    if type(arctps) == float:
+        description = f"{nm} is a level {lvl} {rc} {cls} with no Archetypes."
+    else:
+        description = f"{nm} is a level {lvl} {rc} {cls} with Archetypes in {arctps}."
+
+    mx_dmg_dlt = c_df.loc[c_df["dmg_dealt"].idxmax()]
+    dmg_dlt = f"{mx_dmg_dlt['dmg_dealt']} damage dealt in Session {mx_dmg_dlt['session']}. </br> Combat encounter summary: {mx_dmg_dlt['combat_blurb']}"
+    mx_dmg_tkn = c_df.loc[c_df["dmg_taken"].idxmax()]
+    dmg_tkn = f"{mx_dmg_tkn['dmg_taken']} damage taken in Session {mx_dmg_tkn['session']}. </br> Combat encounter summary: {mx_dmg_tkn['combat_blurb']}"
+    mx_dmg_mtg = c_df.loc[c_df["dmg_mitigated"].idxmax()]
+    dmg_mtg = f"{mx_dmg_mtg['dmg_mitigated']} damage mitigated in Session {mx_dmg_mtg['session']}. </br> Combat encounter summary: {mx_dmg_mtg['combat_blurb']}"
+    mx_dmg_hld = c_df.loc[c_df["dmg_mitigated"].idxmax()]
+    dmg_hld = f"{mx_dmg_hld['dmg_healed']} damage healed in Session {mx_dmg_hld['session']}. </br> Combat encounter summary: {mx_dmg_hld['combat_blurb']}"
+    other = f"Total Successful Attacks: {c_df['atks_success'].sum()} </br> Total Failed Attacks: {c_df['atks_fail'].sum()} </br> Total Spells Cast: {c_df['spells_cast'].sum()} </br>Total Final Blows: {c_df['final_blows'].sum()}"
+
+    pane = pn.pane.Markdown(
+        f"""
+        # Character Highlights: {nm}
+        | Category      | Info |
+        | ----------- | ----------- |
+        | **Description**| {description}|
+        | **Most Damage Dealt** | {dmg_dlt}|
+        | **Most Damage Taken**| {dmg_tkn}|
+        | **Most Damage Mitigated**|{dmg_mtg}|
+        | **Most Damage Healed**|{dmg_hld}|
+        | **Other**| {other} |
+        """
+    )
+    return pane