diff --git a/src/explore.ipynb b/src/explore.ipynb
index 06b41e325993b25359baa6e5e170beccdbbdf5be..15079c74f0870b4266814bfd615767dc996efb4b 100644
--- a/src/explore.ipynb
+++ b/src/explore.ipynb
@@ -1749,12 +1749,224 @@
"source": [
"# Which actions were triggered how often over the years\n",
"df_actions = pd.read_csv(\"quarry-34047-number-of-abuse-filters-filter-actions-per-month-en-wiki-run346492.csv\", sep=',')\n",
- "df_actions.fillna('log')"
+ "df_actions['LogMonth'] = pd.to_datetime(df_actions['LogMonth'], format=\"%Y%m\")\n",
+ "df_actions.fillna('log only')\n"
]
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " LogMonth FilterActions Freq\n",
+ "14 2018-12-01 NaN 83958\n",
+ "15 2018-12-01 disallow 33417\n",
+ "16 2018-12-01 disallow,tag 6\n",
+ "17 2018-12-01 tag 76257\n",
+ "18 2018-12-01 warn 32649\n",
+ "19 2018-11-01 NaN 83866\n",
+ "20 2018-11-01 disallow 43244\n",
+ "21 2018-11-01 disallow,tag 5\n",
+ "22 2018-11-01 tag 86062\n",
+ "23 2018-11-01 warn 40056\n",
+ "24 2018-10-01 NaN 87070\n",
+ "25 2018-10-01 disallow 38163\n",
+ "26 2018-10-01 disallow,tag 8\n",
+ "27 2018-10-01 tag 86140\n",
+ "28 2018-10-01 warn 45057\n",
+ "29 2018-09-01 NaN 88941\n",
+ "30 2018-09-01 disallow 27452\n",
+ "31 2018-09-01 disallow,tag 1\n",
+ "32 2018-09-01 tag 75443\n",
+ "33 2018-09-01 warn 38517\n",
+ "34 2018-08-01 NaN 97404\n",
+ "35 2018-08-01 disallow 22387\n",
+ "36 2018-08-01 disallow,tag 2\n",
+ "37 2018-08-01 tag 69333\n",
+ "38 2018-08-01 warn 26919\n",
+ "39 2018-07-01 NaN 93867\n",
+ "40 2018-07-01 disallow 18885\n",
+ "41 2018-07-01 disallow,tag 3\n",
+ "42 2018-07-01 tag 68355\n",
+ "43 2018-07-01 warn 24367\n",
+ "44 2018-06-01 NaN 87889\n",
+ "45 2018-06-01 disallow 21996\n",
+ "46 2018-06-01 disallow,tag 3\n",
+ "47 2018-06-01 tag 70779\n",
+ "48 2018-06-01 warn 28707\n",
+ "49 2018-05-01 NaN 83190\n",
+ "50 2018-05-01 disallow 30660\n",
+ "51 2018-05-01 disallow,tag 2\n",
+ "52 2018-05-01 tag 81854\n",
+ "53 2018-05-01 warn 42529\n",
+ "54 2018-04-01 NaN 88356\n",
+ "55 2018-04-01 disallow 30991\n",
+ "56 2018-04-01 disallow,tag 2\n",
+ "57 2018-04-01 tag 83492\n",
+ "58 2018-04-01 warn 40016\n",
+ "59 2018-03-01 NaN 89214\n",
+ "60 2018-03-01 disallow 34215\n",
+ "61 2018-03-01 disallow,tag 14\n",
+ "62 2018-03-01 tag 87523\n",
+ "63 2018-03-01 warn 44465\n",
+ "64 2018-02-01 NaN 62171\n",
+ "65 2018-02-01 disallow 32644\n",
+ "66 2018-02-01 disallow,tag 9\n",
+ "67 2018-02-01 tag 76656\n",
+ "68 2018-02-01 warn 42068\n",
+ "69 2018-01-01 NaN 73898\n",
+ "70 2018-01-01 disallow 32164\n",
+ "71 2018-01-01 disallow,tag 16\n",
+ "72 2018-01-01 tag 82561\n",
+ "73 2018-01-01 warn 47066\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "15 33417\n",
+ "20 43244\n",
+ "25 38163\n",
+ "30 27452\n",
+ "35 22387\n",
+ "40 18885\n",
+ "45 21996\n",
+ "50 30660\n",
+ "55 30991\n",
+ "60 34215\n",
+ "65 32644\n",
+ "70 32164\n",
+ "Name: Freq, dtype: int64"
+ ]
+ },
+ "execution_count": 30,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "mask2018 = (df_actions['LogMonth'] >= '2018-01-01') & (df_actions['LogMonth'] < '2019-01-01')\n",
+ "actions_2018 = df_actions.loc[mask2018]\n",
+ "print (actions_2018)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "ValueError",
+ "evalue": "shape mismatch: objects cannot be broadcast to a single shape",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-51-46c8522bf62c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mactions_2018\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'FilterActions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfillna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'log_only'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mac\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mactions_2018\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfillna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'log_only'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'FilterActions==@a'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mac\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbottom\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0my_offset\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0my_offset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0my_offset\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mac\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mbar\u001b[0;34m(x, height, width, bottom, align, data, **kwargs)\u001b[0m\n\u001b[1;32m 2455\u001b[0m return gca().bar(\n\u001b[1;32m 2456\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mwidth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbottom\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbottom\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malign\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0malign\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2457\u001b[0;31m **({\"data\": data} if data is not None else {}), **kwargs)\n\u001b[0m\u001b[1;32m 2458\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2459\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/__init__.py\u001b[0m in \u001b[0;36minner\u001b[0;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1808\u001b[0m \u001b[0;34m\"the Matplotlib list!)\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mlabel_namer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1809\u001b[0m RuntimeWarning, stacklevel=2)\n\u001b[0;32m-> 1810\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1811\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1812\u001b[0m inner.__doc__ = _add_data_doc(inner.__doc__,\n",
+ "\u001b[0;32m~/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mbar\u001b[0;34m(self, x, height, width, bottom, align, **kwargs)\u001b[0m\n\u001b[1;32m 2249\u001b[0m x, height, width, y, linewidth = np.broadcast_arrays(\n\u001b[1;32m 2250\u001b[0m \u001b[0;31m# Make args iterable too.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2251\u001b[0;31m np.atleast_1d(x), height, width, y, linewidth)\n\u001b[0m\u001b[1;32m 2252\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2253\u001b[0m \u001b[0;31m# Now that units have been converted, set the tick locations.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/numpy/lib/stride_tricks.py\u001b[0m in \u001b[0;36mbroadcast_arrays\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 250\u001b[0m \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_m\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubok\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubok\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0m_m\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 251\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 252\u001b[0;31m \u001b[0mshape\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_broadcast_shape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 253\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 254\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mshape\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0marray\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/numpy/lib/stride_tricks.py\u001b[0m in \u001b[0;36m_broadcast_shape\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m 185\u001b[0m \u001b[0;31m# use the old-iterator because np.nditer does not handle size 0 arrays\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 186\u001b[0m \u001b[0;31m# consistently\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 187\u001b[0;31m \u001b[0mb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbroadcast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m32\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 188\u001b[0m \u001b[0;31m# unfortunately, it cannot handle 32 or more arguments directly\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 189\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mpos\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m32\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m31\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mValueError\u001b[0m: shape mismatch: objects cannot be broadcast to a single shape"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "ind = np.arange(12) # the x locations for the groups\n",
+ "width = 0.35 # the width of the bars: can also be len(x) sequence\n",
+ "y_offset = np.zeros(len(ind))\n",
+ "\n",
+ "for a in actions_2018['FilterActions'].fillna('log_only').unique():\n",
+ " ac = actions_2018.fillna('log_only').query('FilterActions==@a')\n",
+ " plt.bar(ind, ac['Freq'], width, bottom=y_offset)\n",
+ " y_offset = y_offset + ac['Freq']\n",
+ "\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "ValueError",
+ "evalue": "shape mismatch: objects cannot be broadcast to a single shape",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-36-c599c7c7dd11>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mp1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdisallow\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0mp2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdisallow_tag\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbottom\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdisallow\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m \u001b[0mp3\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtag\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbottom\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdisallow\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mdisallow_tag\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 14\u001b[0m \u001b[0mp4\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwarn\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbottom\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdisallow\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mdisallow_tag\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mtag\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0mp5\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlog\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbottom\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdisallow\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mdisallow_tag\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mtag\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mwarn\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Freq'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mbar\u001b[0;34m(x, height, width, bottom, align, data, **kwargs)\u001b[0m\n\u001b[1;32m 2455\u001b[0m return gca().bar(\n\u001b[1;32m 2456\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mwidth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbottom\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbottom\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malign\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0malign\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2457\u001b[0;31m **({\"data\": data} if data is not None else {}), **kwargs)\n\u001b[0m\u001b[1;32m 2458\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2459\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/__init__.py\u001b[0m in \u001b[0;36minner\u001b[0;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1808\u001b[0m \u001b[0;34m\"the Matplotlib list!)\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mlabel_namer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1809\u001b[0m RuntimeWarning, stacklevel=2)\n\u001b[0;32m-> 1810\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1811\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1812\u001b[0m inner.__doc__ = _add_data_doc(inner.__doc__,\n",
+ "\u001b[0;32m~/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mbar\u001b[0;34m(self, x, height, width, bottom, align, **kwargs)\u001b[0m\n\u001b[1;32m 2249\u001b[0m x, height, width, y, linewidth = np.broadcast_arrays(\n\u001b[1;32m 2250\u001b[0m \u001b[0;31m# Make args iterable too.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2251\u001b[0;31m np.atleast_1d(x), height, width, y, linewidth)\n\u001b[0m\u001b[1;32m 2252\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2253\u001b[0m \u001b[0;31m# Now that units have been converted, set the tick locations.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/numpy/lib/stride_tricks.py\u001b[0m in \u001b[0;36mbroadcast_arrays\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 250\u001b[0m \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_m\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubok\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubok\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0m_m\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 251\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 252\u001b[0;31m \u001b[0mshape\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_broadcast_shape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 253\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 254\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mshape\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0marray\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/numpy/lib/stride_tricks.py\u001b[0m in \u001b[0;36m_broadcast_shape\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m 185\u001b[0m \u001b[0;31m# use the old-iterator because np.nditer does not handle size 0 arrays\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 186\u001b[0m \u001b[0;31m# consistently\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 187\u001b[0;31m \u001b[0mb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbroadcast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m32\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 188\u001b[0m \u001b[0;31m# unfortunately, it cannot handle 32 or more arguments directly\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 189\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mpos\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m32\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m31\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mValueError\u001b[0m: shape mismatch: objects cannot be broadcast to a single shape"
+ ]
+ },
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "disallow = actions_2018.query('FilterActions==\"disallow\"')\n",
+ "disallow_tag = actions_2018.query('FilterActions==\"disallow,tag\"')\n",
+ "tag = actions_2018.query('FilterActions==\"tag\"')\n",
+ "warn = actions_2018.query('FilterActions==\"warn\"')\n",
+ "log = actions_2018.fillna('log_only').query('FilterActions==\"log_only\"')\n",
+ "\n",
+ "\n",
+ "ind = np.arange(12) # the x locations for the groups\n",
+ "width = 0.35 # the width of the bars: can also be len(x) sequence\n",
+ "\n",
+ "'''\n",
+ "p1 = plt.bar(ind, disallow['Freq'], width)\n",
+ "p2 = plt.bar(ind, disallow_tag['Freq'], width, bottom=disallow['Freq'])\n",
+ "p3 = plt.bar(ind, tag['Freq'], width, bottom=(disallow['Freq']+disallow_tag['Freq']))\n",
+ "p4 = plt.bar(ind, warn['Freq'], width, bottom=(disallow['Freq']+disallow_tag['Freq']+tag['Freq']))\n",
+ "p5 = plt.bar(ind, log['Freq'], width, bottom=(disallow['Freq']+disallow_tag['Freq']+tag['Freq']+warn['Freq']))\n",
+ "\n",
+ "plt.ylabel('Frequency of edit filter actions')\n",
+ "plt.title('Edit filter actions per month')\n",
+ "plt.xticks(ind, ('G1', 'G2', 'G3', 'G4', 'G5'))\n",
+ "plt.legend((p1[0], p2[0], p3[0], p4[0], p5[0]), ('disallow', 'disallow, tag', 'tag', 'warn', 'log only'))\n",
+ "'''\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
"metadata": {
"scrolled": true
},
@@ -1788,181 +2000,181 @@
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
- " <td>201903</td>\n",
+ " <td>2019-03-01</td>\n",
" <td>autocreateaccount</td>\n",
" <td>47</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
- " <td>201903</td>\n",
+ " <td>2019-03-01</td>\n",
" <td>createaccount</td>\n",
" <td>4780</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
- " <td>201903</td>\n",
+ " <td>2019-03-01</td>\n",
" <td>delete</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
- " <td>201903</td>\n",
+ " <td>2019-03-01</td>\n",
" <td>edit</td>\n",
" <td>37950</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
- " <td>201903</td>\n",
+ " <td>2019-03-01</td>\n",
" <td>move</td>\n",
" <td>84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
- " <td>201903</td>\n",
+ " <td>2019-03-01</td>\n",
" <td>upload</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
- " <td>201902</td>\n",
+ " <td>2019-02-01</td>\n",
" <td>autocreateaccount</td>\n",
" <td>454</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
- " <td>201902</td>\n",
+ " <td>2019-02-01</td>\n",
" <td>createaccount</td>\n",
" <td>25204</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
- " <td>201902</td>\n",
+ " <td>2019-02-01</td>\n",
" <td>delete</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
- " <td>201902</td>\n",
+ " <td>2019-02-01</td>\n",
" <td>edit</td>\n",
" <td>210488</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
- " <td>201902</td>\n",
+ " <td>2019-02-01</td>\n",
" <td>move</td>\n",
" <td>445</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
- " <td>201902</td>\n",
+ " <td>2019-02-01</td>\n",
" <td>upload</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
- " <td>201901</td>\n",
+ " <td>2019-01-01</td>\n",
" <td>autocreateaccount</td>\n",
" <td>281</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
- " <td>201901</td>\n",
+ " <td>2019-01-01</td>\n",
" <td>createaccount</td>\n",
" <td>27924</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
- " <td>201901</td>\n",
+ " <td>2019-01-01</td>\n",
" <td>delete</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
- " <td>201901</td>\n",
+ " <td>2019-01-01</td>\n",
" <td>edit</td>\n",
" <td>223870</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
- " <td>201901</td>\n",
+ " <td>2019-01-01</td>\n",
" <td>move</td>\n",
" <td>568</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
- " <td>201901</td>\n",
+ " <td>2019-01-01</td>\n",
" <td>upload</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
- " <td>201812</td>\n",
+ " <td>2018-12-01</td>\n",
" <td>autocreateaccount</td>\n",
" <td>102</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
- " <td>201812</td>\n",
+ " <td>2018-12-01</td>\n",
" <td>createaccount</td>\n",
" <td>35405</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
- " <td>201812</td>\n",
+ " <td>2018-12-01</td>\n",
" <td>delete</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
- " <td>201812</td>\n",
+ " <td>2018-12-01</td>\n",
" <td>edit</td>\n",
" <td>189795</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
- " <td>201812</td>\n",
+ " <td>2018-12-01</td>\n",
" <td>move</td>\n",
" <td>959</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
- " <td>201812</td>\n",
+ " <td>2018-12-01</td>\n",
" <td>upload</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
- " <td>201811</td>\n",
+ " <td>2018-11-01</td>\n",
" <td>autocreateaccount</td>\n",
" <td>486</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
- " <td>201811</td>\n",
+ " <td>2018-11-01</td>\n",
" <td>createaccount</td>\n",
" <td>35421</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
- " <td>201811</td>\n",
+ " <td>2018-11-01</td>\n",
" <td>delete</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
- " <td>201811</td>\n",
+ " <td>2018-11-01</td>\n",
" <td>edit</td>\n",
" <td>216220</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
- " <td>201811</td>\n",
+ " <td>2018-11-01</td>\n",
" <td>move</td>\n",
" <td>1048</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
- " <td>201811</td>\n",
+ " <td>2018-11-01</td>\n",
" <td>upload</td>\n",
" <td>56</td>\n",
" </tr>\n",
@@ -1974,181 +2186,181 @@
" </tr>\n",
" <tr>\n",
" <th>535</th>\n",
- " <td>200911</td>\n",
+ " <td>2009-11-01</td>\n",
" <td>move</td>\n",
" <td>128</td>\n",
" </tr>\n",
" <tr>\n",
" <th>536</th>\n",
- " <td>200910</td>\n",
+ " <td>2009-10-01</td>\n",
" <td>createaccount</td>\n",
" <td>145</td>\n",
" </tr>\n",
" <tr>\n",
" <th>537</th>\n",
- " <td>200910</td>\n",
+ " <td>2009-10-01</td>\n",
" <td>edit</td>\n",
" <td>226571</td>\n",
" </tr>\n",
" <tr>\n",
" <th>538</th>\n",
- " <td>200910</td>\n",
+ " <td>2009-10-01</td>\n",
" <td>move</td>\n",
" <td>149</td>\n",
" </tr>\n",
" <tr>\n",
" <th>539</th>\n",
- " <td>200909</td>\n",
+ " <td>2009-09-01</td>\n",
" <td>createaccount</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>540</th>\n",
- " <td>200909</td>\n",
+ " <td>2009-09-01</td>\n",
" <td>edit</td>\n",
" <td>213070</td>\n",
" </tr>\n",
" <tr>\n",
" <th>541</th>\n",
- " <td>200909</td>\n",
+ " <td>2009-09-01</td>\n",
" <td>move</td>\n",
" <td>103</td>\n",
" </tr>\n",
" <tr>\n",
" <th>542</th>\n",
- " <td>200908</td>\n",
+ " <td>2009-08-01</td>\n",
" <td>createaccount</td>\n",
" <td>95</td>\n",
" </tr>\n",
" <tr>\n",
" <th>543</th>\n",
- " <td>200908</td>\n",
+ " <td>2009-08-01</td>\n",
" <td>delete</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>544</th>\n",
- " <td>200908</td>\n",
+ " <td>2009-08-01</td>\n",
" <td>edit</td>\n",
" <td>162038</td>\n",
" </tr>\n",
" <tr>\n",
" <th>545</th>\n",
- " <td>200908</td>\n",
+ " <td>2009-08-01</td>\n",
" <td>move</td>\n",
" <td>146</td>\n",
" </tr>\n",
" <tr>\n",
" <th>546</th>\n",
- " <td>200907</td>\n",
+ " <td>2009-07-01</td>\n",
" <td>createaccount</td>\n",
" <td>124</td>\n",
" </tr>\n",
" <tr>\n",
" <th>547</th>\n",
- " <td>200907</td>\n",
+ " <td>2009-07-01</td>\n",
" <td>delete</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>548</th>\n",
- " <td>200907</td>\n",
+ " <td>2009-07-01</td>\n",
" <td>edit</td>\n",
" <td>160740</td>\n",
" </tr>\n",
" <tr>\n",
" <th>549</th>\n",
- " <td>200907</td>\n",
+ " <td>2009-07-01</td>\n",
" <td>move</td>\n",
" <td>128</td>\n",
" </tr>\n",
" <tr>\n",
" <th>550</th>\n",
- " <td>200906</td>\n",
+ " <td>2009-06-01</td>\n",
" <td>createaccount</td>\n",
" <td>141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>551</th>\n",
- " <td>200906</td>\n",
+ " <td>2009-06-01</td>\n",
" <td>edit</td>\n",
" <td>178879</td>\n",
" </tr>\n",
" <tr>\n",
" <th>552</th>\n",
- " <td>200906</td>\n",
+ " <td>2009-06-01</td>\n",
" <td>move</td>\n",
" <td>156</td>\n",
" </tr>\n",
" <tr>\n",
" <th>553</th>\n",
- " <td>200905</td>\n",
+ " <td>2009-05-01</td>\n",
" <td>createaccount</td>\n",
" <td>156</td>\n",
" </tr>\n",
" <tr>\n",
" <th>554</th>\n",
- " <td>200905</td>\n",
+ " <td>2009-05-01</td>\n",
" <td>delete</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>555</th>\n",
- " <td>200905</td>\n",
+ " <td>2009-05-01</td>\n",
" <td>edit</td>\n",
" <td>211506</td>\n",
" </tr>\n",
" <tr>\n",
" <th>556</th>\n",
- " <td>200905</td>\n",
+ " <td>2009-05-01</td>\n",
" <td>move</td>\n",
" <td>215</td>\n",
" </tr>\n",
" <tr>\n",
" <th>557</th>\n",
- " <td>200904</td>\n",
+ " <td>2009-04-01</td>\n",
" <td>createaccount</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>558</th>\n",
- " <td>200904</td>\n",
+ " <td>2009-04-01</td>\n",
" <td>delete</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>559</th>\n",
- " <td>200904</td>\n",
+ " <td>2009-04-01</td>\n",
" <td>edit</td>\n",
" <td>178865</td>\n",
" </tr>\n",
" <tr>\n",
" <th>560</th>\n",
- " <td>200904</td>\n",
+ " <td>2009-04-01</td>\n",
" <td>move</td>\n",
" <td>256</td>\n",
" </tr>\n",
" <tr>\n",
" <th>561</th>\n",
- " <td>200903</td>\n",
+ " <td>2009-03-01</td>\n",
" <td>createaccount</td>\n",
" <td>418</td>\n",
" </tr>\n",
" <tr>\n",
" <th>562</th>\n",
- " <td>200903</td>\n",
+ " <td>2009-03-01</td>\n",
" <td>delete</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>563</th>\n",
- " <td>200903</td>\n",
+ " <td>2009-03-01</td>\n",
" <td>edit</td>\n",
" <td>98346</td>\n",
" </tr>\n",
" <tr>\n",
" <th>564</th>\n",
- " <td>200903</td>\n",
+ " <td>2009-03-01</td>\n",
" <td>move</td>\n",
" <td>241</td>\n",
" </tr>\n",
@@ -2158,73 +2370,73 @@
"</div>"
],
"text/plain": [
- " LogMonth EditorActions Freq\n",
- "0 201903 autocreateaccount 47\n",
- "1 201903 createaccount 4780\n",
- "2 201903 delete 5\n",
- "3 201903 edit 37950\n",
- "4 201903 move 84\n",
- "5 201903 upload 3\n",
- "6 201902 autocreateaccount 454\n",
- "7 201902 createaccount 25204\n",
- "8 201902 delete 5\n",
- "9 201902 edit 210488\n",
- "10 201902 move 445\n",
- "11 201902 upload 10\n",
- "12 201901 autocreateaccount 281\n",
- "13 201901 createaccount 27924\n",
- "14 201901 delete 21\n",
- "15 201901 edit 223870\n",
- "16 201901 move 568\n",
- "17 201901 upload 4\n",
- "18 201812 autocreateaccount 102\n",
- "19 201812 createaccount 35405\n",
- "20 201812 delete 5\n",
- "21 201812 edit 189795\n",
- "22 201812 move 959\n",
- "23 201812 upload 21\n",
- "24 201811 autocreateaccount 486\n",
- "25 201811 createaccount 35421\n",
- "26 201811 delete 2\n",
- "27 201811 edit 216220\n",
- "28 201811 move 1048\n",
- "29 201811 upload 56\n",
- ".. ... ... ...\n",
- "535 200911 move 128\n",
- "536 200910 createaccount 145\n",
- "537 200910 edit 226571\n",
- "538 200910 move 149\n",
- "539 200909 createaccount 35\n",
- "540 200909 edit 213070\n",
- "541 200909 move 103\n",
- "542 200908 createaccount 95\n",
- "543 200908 delete 2\n",
- "544 200908 edit 162038\n",
- "545 200908 move 146\n",
- "546 200907 createaccount 124\n",
- "547 200907 delete 1\n",
- "548 200907 edit 160740\n",
- "549 200907 move 128\n",
- "550 200906 createaccount 141\n",
- "551 200906 edit 178879\n",
- "552 200906 move 156\n",
- "553 200905 createaccount 156\n",
- "554 200905 delete 2\n",
- "555 200905 edit 211506\n",
- "556 200905 move 215\n",
- "557 200904 createaccount 24\n",
- "558 200904 delete 7\n",
- "559 200904 edit 178865\n",
- "560 200904 move 256\n",
- "561 200903 createaccount 418\n",
- "562 200903 delete 3\n",
- "563 200903 edit 98346\n",
- "564 200903 move 241\n",
+ " LogMonth EditorActions Freq\n",
+ "0 2019-03-01 autocreateaccount 47\n",
+ "1 2019-03-01 createaccount 4780\n",
+ "2 2019-03-01 delete 5\n",
+ "3 2019-03-01 edit 37950\n",
+ "4 2019-03-01 move 84\n",
+ "5 2019-03-01 upload 3\n",
+ "6 2019-02-01 autocreateaccount 454\n",
+ "7 2019-02-01 createaccount 25204\n",
+ "8 2019-02-01 delete 5\n",
+ "9 2019-02-01 edit 210488\n",
+ "10 2019-02-01 move 445\n",
+ "11 2019-02-01 upload 10\n",
+ "12 2019-01-01 autocreateaccount 281\n",
+ "13 2019-01-01 createaccount 27924\n",
+ "14 2019-01-01 delete 21\n",
+ "15 2019-01-01 edit 223870\n",
+ "16 2019-01-01 move 568\n",
+ "17 2019-01-01 upload 4\n",
+ "18 2018-12-01 autocreateaccount 102\n",
+ "19 2018-12-01 createaccount 35405\n",
+ "20 2018-12-01 delete 5\n",
+ "21 2018-12-01 edit 189795\n",
+ "22 2018-12-01 move 959\n",
+ "23 2018-12-01 upload 21\n",
+ "24 2018-11-01 autocreateaccount 486\n",
+ "25 2018-11-01 createaccount 35421\n",
+ "26 2018-11-01 delete 2\n",
+ "27 2018-11-01 edit 216220\n",
+ "28 2018-11-01 move 1048\n",
+ "29 2018-11-01 upload 56\n",
+ ".. ... ... ...\n",
+ "535 2009-11-01 move 128\n",
+ "536 2009-10-01 createaccount 145\n",
+ "537 2009-10-01 edit 226571\n",
+ "538 2009-10-01 move 149\n",
+ "539 2009-09-01 createaccount 35\n",
+ "540 2009-09-01 edit 213070\n",
+ "541 2009-09-01 move 103\n",
+ "542 2009-08-01 createaccount 95\n",
+ "543 2009-08-01 delete 2\n",
+ "544 2009-08-01 edit 162038\n",
+ "545 2009-08-01 move 146\n",
+ "546 2009-07-01 createaccount 124\n",
+ "547 2009-07-01 delete 1\n",
+ "548 2009-07-01 edit 160740\n",
+ "549 2009-07-01 move 128\n",
+ "550 2009-06-01 createaccount 141\n",
+ "551 2009-06-01 edit 178879\n",
+ "552 2009-06-01 move 156\n",
+ "553 2009-05-01 createaccount 156\n",
+ "554 2009-05-01 delete 2\n",
+ "555 2009-05-01 edit 211506\n",
+ "556 2009-05-01 move 215\n",
+ "557 2009-04-01 createaccount 24\n",
+ "558 2009-04-01 delete 7\n",
+ "559 2009-04-01 edit 178865\n",
+ "560 2009-04-01 move 256\n",
+ "561 2009-03-01 createaccount 418\n",
+ "562 2009-03-01 delete 3\n",
+ "563 2009-03-01 edit 98346\n",
+ "564 2009-03-01 move 241\n",
"\n",
"[565 rows x 3 columns]"
]
},
- "execution_count": 2,
+ "execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
@@ -2232,6 +2444,7 @@
"source": [
"# Which editors' actions triggered a filter\n",
"df_ed_actions = pd.read_csv(\"quarry-34050-which-actions-triggered-an-abuse-filter-en-wiki-run346498.csv\", sep=',')\n",
+ "df_ed_actions['LogMonth'] = pd.to_datetime(df_ed_actions['LogMonth'], format=\"%Y%m\")\n",
"df_ed_actions"
]
},