Merge pull request #65 from TokenEngineeringCommunity/NBupdate

NB updates

Author: Ramarti

NB1-BalancerAMM-V1.0.ipynb

@@ -309,9 +309,9 @@
     "- D1.2 Token Balances (individual balances, over time)\n",
     "\n",
     "**b) Pool Characteristics:**  \n",
-    "- D1.3 Source of Pool Power Growth (Pool Shares (BPT) vs. Fees collected, over time)\n",
-    "- D1.4 Token Ratio (over time)\n",
-    "- D1.5 Action Types (per timestep)"
+    "- D1.3 Source of Pool Growth (Total Growth vs. Fees collected)\n",
+    "- D1.4 Token Ratio\n",
+    "- D1.5 Action Types"
    ]
   },
   {
@@ -462,7 +462,55 @@
     "fee_p_df = p_df[['timestep','generated_fees_dai','token_dai_price','generated_fees_weth','token_weth_price']]\n",
     "fig.add_trace(go.Scatter(x=p_df['timestep'], y=p_df['generated_fees_weth'], line=dict(color='#015B99'), name='fees generated WETH'), row=1, col=1)\n",
     "fig.add_trace(go.Scatter(x=p_df['timestep'], y=p_df['generated_fees_dai'], line=dict(color='#5CB1EC'), name='fees generated DAI'), row=2, col=1)\n",
-    "fig.update_layout(height=400, width=1000, title_text=\"<b>Fees Generated</b>\")"
+    "fig.update_layout(height=400, width=1000, title_text=\"<b>Fees Generated over time</b>\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "p_df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# TODO: use generated_fees instead of price\n",
+    "# TODO: loop over tokens in a list\n",
+    "\n",
+    "#balance growth (total observation period)\n",
+    "daib_df = (p_df.iloc[-1][['token_dai_balance']])-(p_df.iloc[0][['token_dai_balance']]).copy()\n",
+    "daib_df = daib_df.reset_index()\n",
+    "daib_df.columns =['source', 'growth']\n",
+    "wethb_df = (p_df.iloc[-1][['token_weth_balance']])-(p_df.iloc[0][['token_weth_balance']]).copy()\n",
+    "wethb_df = wethb_df.reset_index()\n",
+    "wethb_df.columns =['source', 'growth']\n",
+    "\n",
+    "#fee growth ACHTUNG add \"generated_fees_k\", is currently an object, this is why I use price atm\n",
+    "daif_df = p_df.groupby('action_type').sum()['token_dai_price'].drop(['exit', 'exit_swap', 'external_price_update','pool_creation']).reset_index()\n",
+    "daif_df.columns =['source', 'growth'] \n",
+    "wethf_df = p_df.groupby('action_type').sum()['token_weth_price'].drop(['exit', 'exit_swap', 'external_price_update','pool_creation']).reset_index()\n",
+    "wethf_df.columns =['source', 'growth'] \n",
+    "\n",
+    "#merge\n",
+    "dai_df= pd.concat([daib_df, daif_df], ignore_index=True)\n",
+    "dai_df\n",
+    "weth_df= pd.concat([wethb_df, wethf_df], ignore_index=True)\n",
+    "weth_df\n",
+    "\n",
+    "#plot chart\n",
+    "k = 2 #define number of tokens in your pool\n",
+    "fig = make_subplots(rows=1, cols=k, subplot_titles=(\"DAI Growth\", \"WETH Growth\"))\n",
+    "fig.add_trace(go.Bar(name=\"DAI Growth\", y=dai_df['growth'], x=dai_df['source'], marker_color=px.colors.sequential.Turbo), row=1, col=1)\n",
+    "fig.add_trace(go.Bar(name=\"WETH Growth\", y=weth_df['growth'], x=weth_df['source'], marker_color=px.colors.sequential.Turbo), row=1, col=2)\n",
+    "fig.update_layout(height=400, width=1000, title_text=\"<b>Growth & Sources of Growth</b>\", showlegend=False)\n",
+    "\n",
+    "fig.show()"
    ]
   },
   {
@@ -472,15 +520,14 @@
    "outputs": [],
    "source": [
     "# Compare USD value of fees collected ETH/DAI\n",
-    "# Compare accumulated fees to token_balance\n",
     "# Compare % of USD value total fees collected via DAI vs. ETH"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### C1.4 Token Ratio (over time)"
+    "### C1.4 Token Ratio"
    ]
   },
   {
@@ -489,7 +536,20 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# to be added"
+    "# TODO: create subplots\n",
+    "# TODO: alternatively consider line chart showing changes across particular events\n",
+    "\n",
+    "events = [0, -1]\n",
+    "r_p_df = p_df.iloc[events][['token_dai_balance','token_weth_balance']].transpose(copy=True).reset_index()\n",
+    "r_p_df\n",
+    "\n",
+    "fig1 = px.pie(r_p_df, values=0, names='index', color_discrete_sequence=px.colors.sequential.Turbo)\n",
+    "fig2 = px.pie(r_p_df, values=25601, names='index', color_discrete_sequence=px.colors.sequential.Turbo)\n",
+    "fig1.update_layout(height=300, width=1000, title_text=\"<b>Token Ratio</b>\")\n",
+    "fig2.update_layout(height=300, width=1000, title_text=\"<b>Token Ratio</b>\")\n",
+    "\n",
+    "fig1.show()\n",
+    "fig2.show()"
    ]
   },
   {