Cleanup unused code

diff --git a/data/issues.ipynb b/data/issues.ipynb
index 735326e771234919ff27dd251456e45fbfdf1a3c..3340aaf7fa1346863cb8dd42e539c3eb0c4719e5 100644 (file)
--- a/data/issues.ipynb
+++ b/data/issues.ipynb
@@ -2,7 +2,25 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3.12.2\n"
+     ]
+    }
+   ],
+   "source": [
+    "import platform\n",
+    "print(platform.python_version())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -25,24 +43,6 @@
     "\tprint(f\"{file}\", os.path.getsize(file))\n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "3.12.2\n"
-     ]
-    }
-   ],
-   "source": [
-    "import platform\n",
-    "print(platform.python_version())"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -56,30 +56,13 @@
     "file = data_files[6]\n",
     "print(file)\n",
     "\n",
-    "f = open(file, encoding='utf-16')\n",
+    "f = open(file, encoding='utf-8')\n",
     "df = pd.read_json(f)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas._libs.tslibs.timestamps.Timestamp'>\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(type(df.closed[0]))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 94,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -90,16 +73,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "print(df.milestone[22].get('title'))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 95,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -109,7 +83,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 97,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -118,16 +92,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "for_plot = df.groupby(df.closed.dt.month)['url'].count()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 98,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -148,21 +113,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### Plot of closed issues by month for one project\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "for_plot.plot(kind='bar')"
+    "#### Plot of closed issues by month and milestone for one project\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 99,
    "metadata": {},
    "outputs": [],
    "source": [