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February 26, 2015 05:50
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pandas 简单分析dns日志
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "code", | |
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| "input": [ | |
| "import pandas as pd\n", | |
| "from pandas import Series, DataFrame, Panel" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 1 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "import matplotlib.pyplot as plt\n", | |
| "%matplotlib inline " | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 2 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "df = DataFrame(pd.read_csv('query.csv'))" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 3 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "DataFrame(df.groupby('domain')['domain'].count()).sort([0], ascending=False).head(10)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "html": [ | |
| "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>0</th>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>domain</th>\n", | |
| " <th></th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>viareality.cz</th>\n", | |
| " <td> 215295</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>pidarastik.ru</th>\n", | |
| " <td> 11670</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>cdnmyhost.com</th>\n", | |
| " <td> 9403</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>nutrition.gov</th>\n", | |
| " <td> 6890</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>response</th>\n", | |
| " <td> 2953</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>a.root-servers.net</th>\n", | |
| " <td> 1112</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>www.qq.com</th>\n", | |
| " <td> 1064</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>_xmpp-client._tcp.hisense2.igrslink.com</th>\n", | |
| " <td> 839</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>tracker.torrent.to</th>\n", | |
| " <td> 737</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>bt.51soft.com</th>\n", | |
| " <td> 484</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>10 rows \u00d7 1 columns</p>\n", | |
| "</div>" | |
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| " 0\n", | |
| "domain \n", | |
| "viareality.cz 215295\n", | |
| "pidarastik.ru 11670\n", | |
| "cdnmyhost.com 9403\n", | |
| "nutrition.gov 6890\n", | |
| "response 2953\n", | |
| "a.root-servers.net 1112\n", | |
| "www.qq.com 1064\n", | |
| "_xmpp-client._tcp.hisense2.igrslink.com 839\n", | |
| "tracker.torrent.to 737\n", | |
| "bt.51soft.com 484\n", | |
| "\n", | |
| "[10 rows x 1 columns]" | |
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| "prompt_number": 4 | |
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| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "DataFrame(df.groupby('ip')['ip'].count()).sort([0], ascending=False).head(300)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "html": [ | |
| "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>0</th>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>ip</th>\n", | |
| " <th></th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>113.17.169.58</th>\n", | |
| " <td> 14752</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>88.198.12.175</th>\n", | |
| " <td> 10162</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>179.232.59.50</th>\n", | |
| " <td> 8878</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>115.159.0.189</th>\n", | |
| " <td> 8838</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>98.168.160.244</th>\n", | |
| " <td> 8237</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1.80.95.13</th>\n", | |
| " <td> 7863</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>92.94.67.44</th>\n", | |
| " <td> 7531</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>37.140.192.72</th>\n", | |
| " <td> 7427</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>173.95.137.168</th>\n", | |
| " <td> 6995</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>187.65.0.12</th>\n", | |
| " <td> 6974</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>81.82.192.245</th>\n", | |
| " <td> 6893</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>68.96.50.164</th>\n", | |
| " <td> 5765</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>147.133.204.73</th>\n", | |
| " <td> 5218</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>49.197.10.220</th>\n", | |
| " <td> 4594</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>97.103.240.104</th>\n", | |
| " <td> 4529</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>72.5.195.90</th>\n", | |
| " <td> 4460</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>88.246.19.181</th>\n", | |
| " <td> 4435</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>159.118.249.172</th>\n", | |
| " <td> 3600</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>206.31.248.81</th>\n", | |
| " <td> 3376</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>98.220.15.95</th>\n", | |
| " <td> 3313</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>67.168.67.83</th>\n", | |
| " <td> 2875</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>68.82.237.79</th>\n", | |
| " <td> 2763</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>98.119.3.249</th>\n", | |
| " <td> 2693</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>121.56.191.124</th>\n", | |
| " <td> 2692</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>173.187.85.94</th>\n", | |
| " <td> 2554</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>74.106.228.116</th>\n", | |
| " <td> 2353</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>144.80.251.159</th>\n", | |
| " <td> 2334</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>71.239.95.34</th>\n", | |
| " <td> 2252</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>72.199.145.131</th>\n", | |
| " <td> 2198</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>107.161.187.50</th>\n", | |
| " <td> 2190</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>190.112.0.30</th>\n", | |
| " <td> 2076</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>142.161.66.86</th>\n", | |
| " <td> 1769</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>68.96.92.180</th>\n", | |
| " <td> 1743</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>108.54.105.14</th>\n", | |
| " <td> 1741</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>191.234.241.10</th>\n", | |
| " <td> 1611</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>60.11.72.142</th>\n", | |
| " <td> 1470</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>203.153.47.251</th>\n", | |
| " <td> 1418</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>71.75.234.51</th>\n", | |
| " <td> 1371</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>50.121.215.160</th>\n", | |
| " <td> 1352</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>74.176.28.157</th>\n", | |
| " <td> 1344</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>190.0.163.32</th>\n", | |
| " <td> 1344</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>216.36.145.243</th>\n", | |
| " <td> 1297</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>162.224.188.39</th>\n", | |
| " <td> 1277</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>182.254.218.215</th>\n", | |
| " <td> 1267</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>222.77.217.50</th>\n", | |
| " <td> 1252</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>71.191.51.126</th>\n", | |
| " <td> 1240</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>96.18.93.182</th>\n", | |
| " <td> 1227</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>86.154.147.83</th>\n", | |
| " <td> 1215</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>173.89.218.85</th>\n", | |
| " <td> 1211</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>114.218.141.79</th>\n", | |
| " <td> 1190</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>59.59.135.61</th>\n", | |
| " <td> 1188</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>113.137.141.130</th>\n", | |
| " <td> 1164</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>72.47.239.116</th>\n", | |
| " <td> 1158</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>97.90.196.181</th>\n", | |
| " <td> 1130</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>189.172.242.207</th>\n", | |
| " <td> 1129</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>121.205.242.39</th>\n", | |
| " <td> 1107</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>117.26.250.137</th>\n", | |
| " <td> 1098</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>124.224.54.61</th>\n", | |
| " <td> 1098</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>96.40.119.52</th>\n", | |
| " <td> 1095</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>124.116.106.12</th>\n", | |
| " <td> 1053</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th></th>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>300 rows \u00d7 1 columns</p>\n", | |
| "</div>" | |
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| " 0\n", | |
| "ip \n", | |
| "113.17.169.58 14752\n", | |
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| "67.168.67.83 2875\n", | |
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| "98.119.3.249 2693\n", | |
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| "144.80.251.159 2334\n", | |
| "71.239.95.34 2252\n", | |
| "72.199.145.131 2198\n", | |
| "107.161.187.50 2190\n", | |
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| "142.161.66.86 1769\n", | |
| "68.96.92.180 1743\n", | |
| "108.54.105.14 1741\n", | |
| "191.234.241.10 1611\n", | |
| "60.11.72.142 1470\n", | |
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| "71.75.234.51 1371\n", | |
| "50.121.215.160 1352\n", | |
| "74.176.28.157 1344\n", | |
| "190.0.163.32 1344\n", | |
| "216.36.145.243 1297\n", | |
| "162.224.188.39 1277\n", | |
| "182.254.218.215 1267\n", | |
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| "71.191.51.126 1240\n", | |
| "96.18.93.182 1227\n", | |
| "86.154.147.83 1215\n", | |
| "173.89.218.85 1211\n", | |
| "114.218.141.79 1190\n", | |
| "59.59.135.61 1188\n", | |
| "113.137.141.130 1164\n", | |
| "72.47.239.116 1158\n", | |
| "97.90.196.181 1130\n", | |
| "189.172.242.207 1129\n", | |
| "121.205.242.39 1107\n", | |
| "117.26.250.137 1098\n", | |
| "124.224.54.61 1098\n", | |
| "96.40.119.52 1095\n", | |
| "124.116.106.12 1053\n", | |
| " ...\n", | |
| "\n", | |
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| "prompt_number": 5 | |
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| { | |
| "cell_type": "code", | |
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| "input": [ | |
| "df.index = pd.to_datetime(df.pop('time'))\n", | |
| "#\u6df1\u5c42\u6b21\u5206\u6790(ip\u4f2a\u9020\u7684, \u53ea\u80fd\u4ece\u57df\u540d\u5165\u624b, \u67e5\u627e)\n", | |
| "resamp = df.groupby('domain')['domain'].resample('1t', how='count')\n", | |
| "# 1\u5206\u949f\u5185\u5927\u4e8e600\u7684\u67e5\u8be2\u53ea\u6709viareality.cz\n", | |
| "resamp[resamp.gt(600)].sort_index().plot(rot=30)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 6, | |
| "text": [ | |
| "<matplotlib.axes.AxesSubplot at 0x7f0280b96610>" | |
| ] | |
| }, | |
| { | |
| "metadata": {}, | |
| "output_type": "display_data", | |
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U36rk8k25EEZJJCdI+GRKNc/m4oPmcahUsli+PFpl4iuFciqoRCJ76nyyLHbf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\nRs6NDiimBOqp0g+VHeqLfMePIovpLOTSW4Bq6B2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FTkSuQmCC\n", | |
| "text": [ | |
| "<matplotlib.figure.Figure at 0x7f0280b962d0>" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 6 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "resamp3 = df.groupby('ip')['ip'].resample('1t', how='count')" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [], | |
| "prompt_number": 7 | |
| }, | |
| { | |
| "cell_type": "code", | |
| "collapsed": false, | |
| "input": [ | |
| "DataFrame(resamp3[resamp3.gt(200)]).sort([0], ascending=False).head(300)" | |
| ], | |
| "language": "python", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "html": [ | |
| "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
| " <th>0</th>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>ip</th>\n", | |
| " <th>time</th>\n", | |
| " <th></th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>72.5.195.90</th>\n", | |
| " <th>2015-02-26 05:40:00</th>\n", | |
| " <td> 4460</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th rowspan=\"10\" valign=\"top\">113.17.169.58</th>\n", | |
| " <th>2015-02-26 04:45:00</th>\n", | |
| " <td> 772</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015-02-26 04:53:00</th>\n", | |
| " <td> 772</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015-02-26 04:52:00</th>\n", | |
| " <td> 769</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015-02-26 04:47:00</th>\n", | |
| " <td> 768</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015-02-26 04:49:00</th>\n", | |
| " <td> 768</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015-02-26 04:46:00</th>\n", | |
| " <td> 767</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015-02-26 04:50:00</th>\n", | |
| " <td> 765</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015-02-26 04:48:00</th>\n", | |
| " <td> 765</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015-02-26 04:51:00</th>\n", | |
| " <td> 761</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015-02-26 04:44:00</th>\n", | |
| " <td> 516</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1.81.201.59</th>\n", | |
| " <th>2015-02-26 05:30:00</th>\n", | |
| " <td> 349</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>113.17.169.58</th>\n", | |
| " <th>2015-02-26 04:54:00</th>\n", | |
| " <td> 268</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th rowspan=\"2\" valign=\"top\">68.96.50.164</th>\n", | |
| " <th>2015-02-26 04:54:00</th>\n", | |
| " <td> 261</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015-02-26 04:53:00</th>\n", | |
| " <td> 248</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>88.198.12.175</th>\n", | |
| " <th>2015-02-26 04:35:00</th>\n", | |
| " <td> 241</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>121.56.191.124</th>\n", | |
| " <th>2015-02-26 04:35:00</th>\n", | |
| " <td> 238</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>68.96.50.164</th>\n", | |
| " <th>2015-02-26 04:49:00</th>\n", | |
| " <td> 238</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>49.197.10.220</th>\n", | |
| " <th>2015-02-26 04:36:00</th>\n", | |
| " <td> 236</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>68.96.50.164</th>\n", | |
| " <th>2015-02-26 04:50:00</th>\n", | |
| " <td> 236</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>88.198.12.175</th>\n", | |
| " <th>2015-02-26 04:44:00</th>\n", | |
| " <td> 228</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>68.96.50.164</th>\n", | |
| " <th>2015-02-26 04:52:00</th>\n", | |
| " <td> 224</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1.80.95.13</th>\n", | |
| " <th>2015-02-26 05:39:00</th>\n", | |
| " <td> 223</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>68.96.50.164</th>\n", | |
| " <th>2015-02-26 04:51:00</th>\n", | |
| " <td> 221</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>37.140.192.72</th>\n", | |
| " <th>2015-02-26 04:32:00</th>\n", | |
| " <td> 220</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>88.198.12.175</th>\n", | |
| " <th>2015-02-26 04:34:00</th>\n", | |
| " <td> 217</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>199.184.205.95</th>\n", | |
| " <th>2015-02-26 04:51:00</th>\n", | |
| " <td> 213</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1.80.95.13</th>\n", | |
| " <th>2015-02-26 05:34:00</th>\n", | |
| " <td> 212</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>88.198.12.175</th>\n", | |
| " <th>2015-02-26 04:39:00</th>\n", | |
| " <td> 211</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>68.96.50.164</th>\n", | |
| " <th>2015-02-26 04:07:00</th>\n", | |
| " <td> 209</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>88.198.12.175</th>\n", | |
| " <th>2015-02-26 04:51:00</th>\n", | |
| " <td> 209</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>121.56.191.124</th>\n", | |
| " <th>2015-02-26 04:36:00</th>\n", | |
| " <td> 205</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>37.140.192.72</th>\n", | |
| " <th>2015-02-26 04:31:00</th>\n", | |
| " <td> 202</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>33 rows \u00d7 1 columns</p>\n", | |
| "</div>" | |
| ], | |
| "metadata": {}, | |
| "output_type": "pyout", | |
| "prompt_number": 8, | |
| "text": [ | |
| " 0\n", | |
| "ip time \n", | |
| "72.5.195.90 2015-02-26 05:40:00 4460\n", | |
| "113.17.169.58 2015-02-26 04:45:00 772\n", | |
| " 2015-02-26 04:53:00 772\n", | |
| " 2015-02-26 04:52:00 769\n", | |
| " 2015-02-26 04:47:00 768\n", | |
| " 2015-02-26 04:49:00 768\n", | |
| " 2015-02-26 04:46:00 767\n", | |
| " 2015-02-26 04:50:00 765\n", | |
| " 2015-02-26 04:48:00 765\n", | |
| " 2015-02-26 04:51:00 761\n", | |
| " 2015-02-26 04:44:00 516\n", | |
| "1.81.201.59 2015-02-26 05:30:00 349\n", | |
| "113.17.169.58 2015-02-26 04:54:00 268\n", | |
| "68.96.50.164 2015-02-26 04:54:00 261\n", | |
| " 2015-02-26 04:53:00 248\n", | |
| "88.198.12.175 2015-02-26 04:35:00 241\n", | |
| "121.56.191.124 2015-02-26 04:35:00 238\n", | |
| "68.96.50.164 2015-02-26 04:49:00 238\n", | |
| "49.197.10.220 2015-02-26 04:36:00 236\n", | |
| "68.96.50.164 2015-02-26 04:50:00 236\n", | |
| "88.198.12.175 2015-02-26 04:44:00 228\n", | |
| "68.96.50.164 2015-02-26 04:52:00 224\n", | |
| "1.80.95.13 2015-02-26 05:39:00 223\n", | |
| "68.96.50.164 2015-02-26 04:51:00 221\n", | |
| "37.140.192.72 2015-02-26 04:32:00 220\n", | |
| "88.198.12.175 2015-02-26 04:34:00 217\n", | |
| "199.184.205.95 2015-02-26 04:51:00 213\n", | |
| "1.80.95.13 2015-02-26 05:34:00 212\n", | |
| "88.198.12.175 2015-02-26 04:39:00 211\n", | |
| "68.96.50.164 2015-02-26 04:07:00 209\n", | |
| "88.198.12.175 2015-02-26 04:51:00 209\n", | |
| "121.56.191.124 2015-02-26 04:36:00 205\n", | |
| "37.140.192.72 2015-02-26 04:31:00 202\n", | |
| "\n", | |
| "[33 rows x 1 columns]" | |
| ] | |
| } | |
| ], | |
| "prompt_number": 8 | |
| } | |
| ], | |
| "metadata": {} | |
| } | |
| ] | |
| } |
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