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analysis/main/5-1-prop-bot-reverts.ipynb

@@ -25,6 +25,14 @@
     "%matplotlib inline"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Import datasets\n",
+    "Using a dictionary of pandas dataframes, with the key as the language. A better way would be to have a tidy dataframe."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -345,19 +353,36 @@
     "df_rev_dict['en'][0:5]"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Clean and combine the two datasets"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 21,
    "metadata": {
     "collapsed": true
    },
    "outputs": [],
    "source": [
     "def truncate_my(s):\n",
+    "    \"\"\"\n",
+    "    Truncate YYYYMMDD format to YYYYMM. For use with df.apply()\n",
+    "    \"\"\"\n",
     "    s = str(s)\n",
     "    return int(s[0:6])"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Test function"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 12,
@@ -378,6 +403,15 @@
     "truncate_my(20100101)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": 13,