From 544c0a68569be18f490fd5384b3df66ca49caef0 Mon Sep 17 00:00:00 2001 From: Vanessa Braganholo Date: Thu, 19 Sep 2019 14:37:39 -0700 Subject: [PATCH] Issue #17: Jupyter notebook to filter related work. 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authorskeytitleurlyearcrossrefvenue
0Holger Pirkjournals/sigmod/Pirk15...like Commanding an Anthill: A Case for Micr...db/journals/sigmod/sigmod44.html#Pirk152015NaN
1Jos A. BlakeleyVineet RaoIsaac KunenAdam Prout...conf/sigmod/BlakeleyRKPHK08.NET database programmability and extensibilit...db/conf/sigmod/sigmod2008.html#BlakeleyRKPHK082008conf/sigmod/2008NaN
2David B. Martin 0001John RooksbyMark Rouncefie...conf/icse/MartinRRS07'Good' Organisational Reasons for 'Bad' Softwa...db/conf/icse/icse2007.html#MartinRRS072007conf/icse/2007NaN
3Goetz GraefeWey GuyHarumi A. Kunoconf/icde/GraefeGK11'Pause and resume' functionality for index ope...db/conf/icde/icdew2011.html#GraefeGK112011conf/icde/2011wNaN
4Alexander BorgidaJohn MylopoulosRaymond Reiterconf/icse/BorgidaMR93\"...And Nothing Else Changes\": The Frame Probl...db/conf/icse/icse93.html#BorgidaMR931993conf/icse/1993NaN
5Thomas Haighjournals/sigmod/Haigh06\"A veritable bucket of facts\" origins of the d...db/journals/sigmod/sigmod35.html#Haigh062006NaN
6Lucrecia LlerenaNancy RodrguezPablo Gmez-Abajo...conf/icse/LlerenaRGCA18\"Adoption of the visual brainstorming techniqu...db/conf/icse/icse2018c.html#LlerenaRGCA182018conf/icse/2018cNaN
7Hao Zhang 0029Gang Chen 0001Beng Chin OoiWeng-...conf/icde/ZhangCOWWX15\"Anti-Caching\"-based elastic memory management...db/conf/icde/icde2015.html#ZhangCOWWX152015conf/icde/2015NaN
8Asher TrockmanKeenen CatesMark MozinaTuan Nguy...conf/msr/TrockmanCMNKV18\"Automatically assessing code understandabilit...db/conf/msr/msr2018.html#TrockmanCMNKV182018conf/msr/2018NaN
9Kenneth P. SmithLeonard J. SeligmanArnon Rosen...conf/sigmod/SmithSRKGMSE14\"Big Metadata\": The Need for Principled Metada...db/conf/sigmod/danac2014.html#SmithSRKGMSE142014conf/sigmod/2014danacNaN
10Cory KapserMichael W. Godfreyjournals/ese/KapserG08\"Cloning considered harmful\" considered harmfu...db/journals/ese/ese13.html#KapserG082008NaN
11E. A. M. Vefsnmoconf/icse/Vefsnmo85\"DASOM\" - A Software Engineering Tool for Comm...db/conf/icse/icse85.html#Vefsnmo851985conf/icse/1985NaN
12Michael J. FranklinStanley B. Zdonikconf/sigmod/FranklinZ98\"Data In Your Face\": Push Technology in Perspe...db/conf/sigmod/sigmod98.html#FranklinZ981998conf/sigmod/98NaN
13Sohaib Shahid BajwaXiaofeng Wang 0001Anh Nguye...journals/ese/BajwaWDA17\"Failures\" to be celebrated: an analysis of ma...db/journals/ese/ese22.html#BajwaWDA172017NaN
14Lawrence A. Roweconf/vldb/Rowe85\"Fill-in-the-Form\" Programming.db/conf/vldb/vldb85.html#Rowe851985conf/vldb/85NaN
15Praveen Seshadriconf/sigmod/Seshadri99\"Honey, I Shrunk the DBMS\": Footprint, Mobilit...db/conf/sigmod/sigmod99.html#Seshadri991999conf/sigmod/99NaN
16Tamara LopezHelen SharpThein Than TunArosha K....conf/icse/LopezSTBLN19\"Hopefully we are mostly secure\": views on sec...db/conf/icse/chase2019.html#LopezSTBLN192019conf/icse/2019chaseNaN
17Vesna MikulovicMichael Heissconf/icse/MikulovicH06\"How do I know what I have to do?\": the role o...db/conf/icse/icse2006.html#MikulovicH062006conf/icse/2006NaN
18Paul F. WilmsBruce G. Lindsay 0001Patricia G. ...conf/sigmod/WilmsLS83\"I wish I were over there\": Distributed Execut...db/conf/sigmod/sigmod83.html#WilmsLS831983conf/sigmod/83NaN
19Marco BiazziniBenoit Baudryconf/icse/BiazziniB14\"May the fork be with you\": novel metrics to a...db/conf/icse/wetsom2014.html#BiazziniB142014conf/icse/2014wetsomNaN
20Jan Reckerjournals/is/Recker12\"Modeling with tools is easier, believe me\" - ...db/journals/is/is37.html#Recker122012NaN
21Irini FundulakiRichard Hull 0001Bharat KumarDa...conf/icde/FundulakiHKLS04\"My Personal Web\": A Seminar on Personalizatio...db/conf/icde/icde2004.html#FundulakiHKLS042004conf/icde/2004NaN
22Anthony Finkelsteinconf/icse/Finkelstein01\"Not Waving but Drowning\": Representation Sche...db/conf/icse/icse89.html#Finkelstein011989conf/icse/1989NaN
23Daniel D. DeavoursWilliam H. Sandersjournals/tse/DeavoursS98\"On-the-Fly'' Solution Techniques for Stochast...db/journals/tse/tse24.html#DeavoursS981998NaN
24Clark D. Frenchconf/sigmod/French95\"One Size Fits All\" Database Architectures Do ...db/conf/sigmod/sigmod95.html#French951995conf/sigmod/95NaN
25Michael StonebrakerUgur etintemelconf/icde/StonebrakerC05\"One Size Fits All\": An Idea Whose Time Has Co...db/conf/icde/icde2005.html#StonebrakerC052005conf/icde/2005NaN
26Jianfeng ChenVivek NairRahul KrishnaTim Menziesjournals/tse/ChenNKM19\"Sampling\" as a Baseline Optimizer for Search-...db/journals/tse/tse45.html#ChenNKM192019NaN
27Megan Squireconf/icse/Squire15\"Should We Move to Stack Overflow?\" Measuring ...db/conf/icse/icse2015-2.html#Squire152015conf/icse/2015-2NaN
28Maria Teresa BaldassarreDanilo CaivanoDiego Se...conf/sigsoft/BaldassarreCSS18\"Smart Traffic\": an IoT traffic monitoring sys...db/conf/sigsoft/ensemble2018.html#BaldassarreC...2018conf/sigsoft/2018ensembleNaN
29Matas Lopez-Rosenfeldconf/icse/Lopez-Rosenfeld17\"Tell Me and I Forget, Teach Me and I May Reme...db/conf/icse/secm2017.html#Lopez-Rosenfeld172017conf/icse/2017secmNaN
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36793Graham CormodeChris Hickeyconf/icde/CormodeH18You Can Check Others' Work More Quickly Than D...db/conf/icde/icde2018.html#CormodeH182018conf/icde/2018NaN
36794Panagiotis ReveliotisMichael J. Carey 0001conf/icde/ReveliotisC06Your Enterprise on XQuery and XML Schema: XML-...db/conf/icde/icdew2006.html#ReveliotisC062006conf/icde/2006wNaN
36795Sophie CluetClaude DelobelJrme SimonKatarzyna ...conf/sigmod/CluetDSS98Your Mediators Need Data Conversion!db/conf/sigmod/sigmod98.html#CluetDSS981998conf/sigmod/98NaN
36796Eduard Constantin DragutBrian P. BeirneAli Ney...conf/icde/DragutBNAYDM13YumiInt - A deep Web integration system for lo...db/conf/icde/icde2013.html#DragutBNAYDM132013conf/icde/2013NaN
36797Ken C. K. LeeWang-Chien LeeBaihua ZhengHuajing...journals/vldb/LeeLZLT10Z-SKY: an efficient skyline query processing f...db/journals/vldb/vldb19.html#LeeLZLT102010NaN
36798Yunhui ZhengXiangyu Zhang 0001Vijay Ganeshconf/sigsoft/ZhengZG13Z3-str: a z3-based string solver for web appli...db/conf/sigsoft/fse2013.html#ZhengZG132013conf/sigsoft/2013NaN
36799Srilekha MudumbaiKshitij ShahAmit P. ShethKris...conf/icde/MudumbaiSSPB98ZEBRA Image Access System.db/conf/icde/icde98.html#MudumbaiSSPB981998conf/icde/98NaN
36800Laurent BurgyLaurent RveillreJulia L. LawallGi...journals/tse/BurgyRLM11Zebu: A Language-Based Approach for Network Pr...db/journals/tse/tse37.html#BurgyRLM112011NaN
36801Yan LiTao Yue 0002Shaukat Ali 0001Li Zhang 0029journals/ese/LiYAZ17Zen-ReqOptimizer: a search-based approach for ...db/journals/ese/ese22.html#LiYAZ172017NaN
36802Chris Lewis 0002conf/icse/Lewis10Zenet: generating and enforcing real-time temp...db/conf/icse/icse2010-2.html#Lewis102010conf/icse/2010-2NaN
36803Byron HawkinsBrian Demskyconf/icse/HawkinsD17ZenIDS: introspective intrusion detection for ...db/conf/icse/icse2017.html#HawkinsD172017conf/icse/2017NaN
36804Aaron J. ElmoreSudipto DasDivyakant AgrawalAmr...conf/sigmod/ElmoreDAA11Zephyr: live migration in shared nothing datab...db/conf/sigmod/sigmod2011.html#ElmoreDAA112011conf/sigmod/2011NaN
36805Michael de JongArie van DeursenAnthony Cleveconf/icse/JongDC17Zero-Downtime SQL Database Schema Evolution fo...db/conf/icse/icse2017seip.html#JongDC172017conf/icse/2017seipNaN
36806Richard RutledgeSunjae ParkHaider A. KhanAless...conf/icse/RutledgePKOPZ19Zero-overhead path prediction with progressive...db/conf/icse/icse2019.html#RutledgePKOPZ192019conf/icse/2019NaN
36807Wenhai LiLingfeng DengYang LiChen Li 0001conf/sigmod/LiDL018ZigZag: Supporting Similarity Queries on Vecto...db/conf/sigmod/sigmod2018.html#LiDL0182018conf/sigmod/2018NaN
36808Tunaggina Subrina Khanconf/icde/Khan18ZIP-Code Classification Using Spatial and Crow...db/conf/icde/icde2018.html#Khan182018conf/icde/2018NaN
36809Anurag KhandelwalZongheng YangEvan YeRachit Ag...conf/sigmod/KhandelwalYY0S17ZipG: A Memory-efficient Graph Store for Inter...db/conf/sigmod/sigmod2017.html#KhandelwalYY0S172017conf/sigmod/2017NaN
36810Tom JanssenRui AbreuArjan J. C. van Gemundconf/kbse/JanssenAG09Zoltar: A Toolset for Automatic Fault Localiza...db/conf/kbse/ase2009.html#JanssenAG092009conf/kbse/2009NaN
36811Seon Ho KimByunggu YuJae-young Changjournals/is/KimYC08Zoned-partitioning of tree-like access methods.db/journals/is/is33.html#KimYC082008NaN
36812Yannis E. IoannidisMiron LivnyShivani GuptaNag...conf/vldb/IoannidisLGP96ZOO : A Desktop Experiment Management Environm...db/conf/vldb/vldb96.html#IoannidisLG961996conf/vldb/96NaN
36813Yannis E. IoannidisMiron LivnyAnastassia Ailam...conf/sigmod/IoannidisLANT97ZOO: A Desktop Emperiment Management Environment.db/conf/sigmod/sigmod97.html#IoannidisLANT971997conf/sigmod/97NaN
36814Olivier BitonSarah Cohen BoulakiaSusan B. Davi...conf/vldb/BitonBD07Zoom*UserViews: Querying Relevant Provenance i...db/conf/vldb/vldb2007.html#BitonBD072007conf/vldb/2007NaN
36815Fabrizio PastoreLeonardo Marianiconf/icse/PastoreM15ZoomIn: Discovering Failures by Detecting Wron...db/conf/icse/icse2015-1.html#PastoreM152015conf/icse/2015-1NaN
36816Julia StoyanovichMatthew GilbrideVera Zaychik ...conf/vldb/StoyanovichGM18Zooming in on NYC Taxi Data with Portal.db/conf/vldb/bidup2018.html#StoyanovichGM182018conf/vldb/2018bidupNaN
36817Bradford L. ChamberlainSung-Eun ChoiE. Christo...journals/tse/ChamberlainCLLSW00ZPL: A Machine Independent Programming Languag...db/journals/tse/tse26.html#ChamberlainCLLSW002000NaN
36818Yuan MeiSamuel Maddenconf/sigmod/MeiM09ZStream: a cost-based query processor for adap...db/conf/sigmod/sigmod2009.html#MeiM092009conf/sigmod/2009NaN
36819Bingchang LiuWei HuoChao Zhang 0008Wenchao LiF...conf/kbse/LiuHZLLPZ18αDiff: cross-version binary code similarity de...db/conf/kbse/ase2018.html#LiuHZLLPZ182018conf/kbse/2018NaN
36820Zheng LiTingjian GeCindy X. Chenconf/sigmod/LiGC13ε-Matching: event processing over noisy sequen...db/conf/sigmod/sigmod2013.html#LiGC132013conf/sigmod/2013NaN
36821Chang-ai SunYiqiang LiuZuoyi WangW. K. Chan 0001conf/icse/SunLWC16μMT: a data mutation directed metamorphic rela...db/conf/icse/met2016.html#SunLWC162016conf/icse/2016metNaN
36822Dan OlteanuLampros PapageorgiouSebastiaan J. v...conf/icde/OlteanuPS13Πgora: An Integration System for Probabilistic...db/conf/icde/icde2013.html#OlteanuPS132013conf/icde/2013NaN
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Lindsay 0001Patricia G. ... \n", + "19 Marco BiazziniBenoit Baudry \n", + "20 Jan Recker \n", + "21 Irini FundulakiRichard Hull 0001Bharat KumarDa... \n", + "22 Anthony Finkelstein \n", + "23 Daniel D. DeavoursWilliam H. Sanders \n", + "24 Clark D. French \n", + "25 Michael StonebrakerUgur etintemel \n", + "26 Jianfeng ChenVivek NairRahul KrishnaTim Menzies \n", + "27 Megan Squire \n", + "28 Maria Teresa BaldassarreDanilo CaivanoDiego Se... \n", + "29 Matas Lopez-Rosenfeld \n", + "... ... \n", + "36793 Graham CormodeChris Hickey \n", + "36794 Panagiotis ReveliotisMichael J. Carey 0001 \n", + "36795 Sophie CluetClaude DelobelJrme SimonKatarzyna ... \n", + "36796 Eduard Constantin DragutBrian P. BeirneAli Ney... \n", + "36797 Ken C. K. LeeWang-Chien LeeBaihua ZhengHuajing... \n", + "36798 Yunhui ZhengXiangyu Zhang 0001Vijay Ganesh \n", + "36799 Srilekha MudumbaiKshitij ShahAmit P. ShethKris... \n", + "36800 Laurent BurgyLaurent RveillreJulia L. LawallGi... \n", + "36801 Yan LiTao Yue 0002Shaukat Ali 0001Li Zhang 0029 \n", + "36802 Chris Lewis 0002 \n", + "36803 Byron HawkinsBrian Demsky \n", + "36804 Aaron J. ElmoreSudipto DasDivyakant AgrawalAmr... \n", + "36805 Michael de JongArie van DeursenAnthony Cleve \n", + "36806 Richard RutledgeSunjae ParkHaider A. KhanAless... \n", + "36807 Wenhai LiLingfeng DengYang LiChen Li 0001 \n", + "36808 Tunaggina Subrina Khan \n", + "36809 Anurag KhandelwalZongheng YangEvan YeRachit Ag... \n", + "36810 Tom JanssenRui AbreuArjan J. C. van Gemund \n", + "36811 Seon Ho KimByunggu YuJae-young Chang \n", + "36812 Yannis E. IoannidisMiron LivnyShivani GuptaNag... \n", + "36813 Yannis E. IoannidisMiron LivnyAnastassia Ailam... \n", + "36814 Olivier BitonSarah Cohen BoulakiaSusan B. Davi... \n", + "36815 Fabrizio PastoreLeonardo Mariani \n", + "36816 Julia StoyanovichMatthew GilbrideVera Zaychik ... \n", + "36817 Bradford L. ChamberlainSung-Eun ChoiE. Christo... \n", + "36818 Yuan MeiSamuel Madden \n", + "36819 Bingchang LiuWei HuoChao Zhang 0008Wenchao LiF... \n", + "36820 Zheng LiTingjian GeCindy X. Chen \n", + "36821 Chang-ai SunYiqiang LiuZuoyi WangW. K. Chan 0001 \n", + "36822 Dan OlteanuLampros PapageorgiouSebastiaan J. v... \n", + "\n", + " key \\\n", + "0 journals/sigmod/Pirk15 \n", + "1 conf/sigmod/BlakeleyRKPHK08 \n", + "2 conf/icse/MartinRRS07 \n", + "3 conf/icde/GraefeGK11 \n", + "4 conf/icse/BorgidaMR93 \n", + "5 journals/sigmod/Haigh06 \n", + "6 conf/icse/LlerenaRGCA18 \n", + "7 conf/icde/ZhangCOWWX15 \n", + "8 conf/msr/TrockmanCMNKV18 \n", + "9 conf/sigmod/SmithSRKGMSE14 \n", + "10 journals/ese/KapserG08 \n", + "11 conf/icse/Vefsnmo85 \n", + "12 conf/sigmod/FranklinZ98 \n", + "13 journals/ese/BajwaWDA17 \n", + "14 conf/vldb/Rowe85 \n", + "15 conf/sigmod/Seshadri99 \n", + "16 conf/icse/LopezSTBLN19 \n", + "17 conf/icse/MikulovicH06 \n", + "18 conf/sigmod/WilmsLS83 \n", + "19 conf/icse/BiazziniB14 \n", + "20 journals/is/Recker12 \n", + "21 conf/icde/FundulakiHKLS04 \n", + "22 conf/icse/Finkelstein01 \n", + "23 journals/tse/DeavoursS98 \n", + "24 conf/sigmod/French95 \n", + "25 conf/icde/StonebrakerC05 \n", + "26 journals/tse/ChenNKM19 \n", + "27 conf/icse/Squire15 \n", + "28 conf/sigsoft/BaldassarreCSS18 \n", + "29 conf/icse/Lopez-Rosenfeld17 \n", + "... ... \n", + "36793 conf/icde/CormodeH18 \n", + "36794 conf/icde/ReveliotisC06 \n", + "36795 conf/sigmod/CluetDSS98 \n", + "36796 conf/icde/DragutBNAYDM13 \n", + "36797 journals/vldb/LeeLZLT10 \n", + "36798 conf/sigsoft/ZhengZG13 \n", + "36799 conf/icde/MudumbaiSSPB98 \n", + "36800 journals/tse/BurgyRLM11 \n", + "36801 journals/ese/LiYAZ17 \n", + "36802 conf/icse/Lewis10 \n", + "36803 conf/icse/HawkinsD17 \n", + "36804 conf/sigmod/ElmoreDAA11 \n", + "36805 conf/icse/JongDC17 \n", + "36806 conf/icse/RutledgePKOPZ19 \n", + "36807 conf/sigmod/LiDL018 \n", + "36808 conf/icde/Khan18 \n", + "36809 conf/sigmod/KhandelwalYY0S17 \n", + "36810 conf/kbse/JanssenAG09 \n", + "36811 journals/is/KimYC08 \n", + "36812 conf/vldb/IoannidisLGP96 \n", + "36813 conf/sigmod/IoannidisLANT97 \n", + "36814 conf/vldb/BitonBD07 \n", + "36815 conf/icse/PastoreM15 \n", + "36816 conf/vldb/StoyanovichGM18 \n", + "36817 journals/tse/ChamberlainCLLSW00 \n", + "36818 conf/sigmod/MeiM09 \n", + "36819 conf/kbse/LiuHZLLPZ18 \n", + "36820 conf/sigmod/LiGC13 \n", + "36821 conf/icse/SunLWC16 \n", + "36822 conf/icde/OlteanuPS13 \n", + "\n", + " title \\\n", + "0 ...like Commanding an Anthill: A Case for Micr... \n", + "1 .NET database programmability and extensibilit... \n", + "2 'Good' Organisational Reasons for 'Bad' Softwa... \n", + "3 'Pause and resume' functionality for index ope... \n", + "4 \"...And Nothing Else Changes\": The Frame Probl... \n", + "5 \"A veritable bucket of facts\" origins of the d... \n", + "6 \"Adoption of the visual brainstorming techniqu... \n", + "7 \"Anti-Caching\"-based elastic memory management... \n", + "8 \"Automatically assessing code understandabilit... \n", + "9 \"Big Metadata\": The Need for Principled Metada... \n", + "10 \"Cloning considered harmful\" considered harmfu... \n", + "11 \"DASOM\" - A Software Engineering Tool for Comm... \n", + "12 \"Data In Your Face\": Push Technology in Perspe... \n", + "13 \"Failures\" to be celebrated: an analysis of ma... \n", + "14 \"Fill-in-the-Form\" Programming. \n", + "15 \"Honey, I Shrunk the DBMS\": Footprint, Mobilit... \n", + "16 \"Hopefully we are mostly secure\": views on sec... \n", + "17 \"How do I know what I have to do?\": the role o... \n", + "18 \"I wish I were over there\": Distributed Execut... \n", + "19 \"May the fork be with you\": novel metrics to a... \n", + "20 \"Modeling with tools is easier, believe me\" - ... \n", + "21 \"My Personal Web\": A Seminar on Personalizatio... \n", + "22 \"Not Waving but Drowning\": Representation Sche... \n", + "23 \"On-the-Fly'' Solution Techniques for Stochast... \n", + "24 \"One Size Fits All\" Database Architectures Do ... \n", + "25 \"One Size Fits All\": An Idea Whose Time Has Co... \n", + "26 \"Sampling\" as a Baseline Optimizer for Search-... \n", + "27 \"Should We Move to Stack Overflow?\" Measuring ... \n", + "28 \"Smart Traffic\": an IoT traffic monitoring sys... \n", + "29 \"Tell Me and I Forget, Teach Me and I May Reme... \n", + "... ... \n", + "36793 You Can Check Others' Work More Quickly Than D... \n", + "36794 Your Enterprise on XQuery and XML Schema: XML-... \n", + "36795 Your Mediators Need Data Conversion! \n", + "36796 YumiInt - A deep Web integration system for lo... \n", + "36797 Z-SKY: an efficient skyline query processing f... \n", + "36798 Z3-str: a z3-based string solver for web appli... \n", + "36799 ZEBRA Image Access System. \n", + "36800 Zebu: A Language-Based Approach for Network Pr... \n", + "36801 Zen-ReqOptimizer: a search-based approach for ... \n", + "36802 Zenet: generating and enforcing real-time temp... \n", + "36803 ZenIDS: introspective intrusion detection for ... \n", + "36804 Zephyr: live migration in shared nothing datab... \n", + "36805 Zero-Downtime SQL Database Schema Evolution fo... \n", + "36806 Zero-overhead path prediction with progressive... 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\n", + "17 conf/icse/2006 NaN \n", + "18 conf/sigmod/83 NaN \n", + "19 conf/icse/2014wetsom NaN \n", + "20 NaN \n", + "21 conf/icde/2004 NaN \n", + "22 conf/icse/1989 NaN \n", + "23 NaN \n", + "24 conf/sigmod/95 NaN \n", + "25 conf/icde/2005 NaN \n", + "26 NaN \n", + "27 conf/icse/2015-2 NaN \n", + "28 conf/sigsoft/2018ensemble NaN \n", + "29 conf/icse/2017secm NaN \n", + "... ... ... \n", + "36793 conf/icde/2018 NaN \n", + "36794 conf/icde/2006w NaN \n", + "36795 conf/sigmod/98 NaN \n", + "36796 conf/icde/2013 NaN \n", + "36797 NaN \n", + "36798 conf/sigsoft/2013 NaN \n", + "36799 conf/icde/98 NaN \n", + "36800 NaN \n", + "36801 NaN \n", + "36802 conf/icse/2010-2 NaN \n", + "36803 conf/icse/2017 NaN \n", + "36804 conf/sigmod/2011 NaN \n", + "36805 conf/icse/2017seip NaN \n", + "36806 conf/icse/2019 NaN \n", + "36807 conf/sigmod/2018 NaN \n", + "36808 conf/icde/2018 NaN \n", + "36809 conf/sigmod/2017 NaN \n", + "36810 conf/kbse/2009 NaN \n", + "36811 NaN \n", + "36812 conf/vldb/96 NaN \n", + "36813 conf/sigmod/97 NaN \n", + "36814 conf/vldb/2007 NaN \n", + "36815 conf/icse/2015-1 NaN \n", + "36816 conf/vldb/2018bidup NaN \n", + "36817 NaN \n", + "36818 conf/sigmod/2009 NaN \n", + "36819 conf/kbse/2018 NaN \n", + "36820 conf/sigmod/2013 NaN \n", + "36821 conf/icse/2016met NaN \n", + "36822 conf/icde/2013 NaN \n", + "\n", + "[36823 rows x 7 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "new_index = ['authors', 'key', 'title', 'url', 'year', 'crossref', 'venue']\n", + "df.reindex(columns = new_index)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, "outputs": [], "source": [ "for index_label, row in df.iterrows():\n", @@ -964,7 +1944,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -1932,7 +2912,7 @@ "[36823 rows x 7 columns]" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -1943,16 +2923,16 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, @@ -1973,7 +2953,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -1982,7 +2962,7 @@ "828" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -1994,7 +2974,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -2962,7 +3942,7 @@ "[828 rows x 7 columns]" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -2971,6 +3951,69 @@ "df" ] }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "conf/sigmod 239\n", + "journals/is 214\n", + "conf/icde 141\n", + "journals/vldb 94\n", + "journals/sigmod 72\n", + "conf/icse 23\n", + "conf/vldb 18\n", + "conf/sigsoft 8\n", + "conf/kbse 7\n", + "journals/ase 5\n", + "journals/tosem 3\n", + "journals/tse 2\n", + "conf/msr 2\n", + "Name: venue, dtype: int64" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.venue.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df.venue.value_counts().plot(kind='pie', autopct='%1.1f%%')" + ] + }, { "cell_type": "code", "execution_count": 12, @@ -2979,16 +4022,38 @@ { "data": { "text/plain": [ - "" + "50" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" + } + ], + "source": [ + "es_venues = ['conf/icse', 'conf/sigsoft', 'conf/kbse', 'journals/ase', 'journals/tosem', 'journals/tse', 'conf/msr']\n", + "df=df[df.venue.isin(es_venues)]\n", + "len(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" }, { "data": { - "image/png": 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VKXz5Frqe9Gtqln9AqHA9Kbnj8I87uaPeWlO+BsYWzJphx6Nxl51x9+rCTbiiB0CSRPv3oWhbR7ap0QhFr/6F9JHTSRtm/Narl39I2iHmedrwowlu+2631wamXEDvy/4fORf+GRSSuvTe6Xzt6nn4eg5Fw/WEijfQ/cyZ1Hz9MXa4PrZvaveMAs6PR8MuzUls4csLdAd+FW8zOhOneb7osAREqkrJO/eQlN2PzElnfX/ck9GV4KblANRvWNpM0ADUjhKtqwQgVLiecNF6UgYe1ng+GqHyyzfIPOJsNBLke28sVYhGYvem9k5e7sz8hPQa6Gwkes6FK2nud5jQnOqZH30genqHtBXcspKarz8mqXsuWx+/GoAu035C9ilXU/bBQ6gdRbw+up5szgW3rab6q3fIPuU3YEfZ8ezvARBfGt1+eB1iNWpK1eJ8MkYfj5WUQlL3gYCy9dGrSB08ESslo0Pe324YBpwH/CteBrgYEneOLy/gAzYAPeNtSmcipN6CQ4JP5cbbjoOYJQWzZhzWcjGXWJLIQ90f4YpeM3wSye1FyfZ423EQM95NTRl/Eln4rom3AZ2VH3rmrYu3DQc5v4+3AYlOYgpfXmA6JtKMy26Y4ZkXjbcNBznHu7s54ktiCl9rtrAlMCNkgxueKvb8JN4GJDKJJ3x5gcHAD+NtRmcmWSIDcygtjLcdBzkX5s7MT7zvXychEW/8T0nM990mZnjmtzaijcu+0RuYHm8jEpVEFIBz27vCTRU2xz5Zw4j7qhn1z2rumWdCDubNrqfP36oY90A14x6o5u3Vu99WfPcXQUb9s5rR/6zmR/+upT5iXIwueqWWsfdX84cPG3ca3PpJkNe/aY/tyXtnhmde3Lx8E4j/ircBiUpiCZ8JNDq0vav1WvB/P0hh1VUZzPtpOvctDLOyyKwP/PeRPr66MoOvrszg1KFJza7dUmlz74IQX/48nRW/yiBqw79WhFm2w1y/7JcZfLoxSkW9sq3KZsHWKGcMb15PezNaCvrEvBGXc3Jn5ifH24hEJLGED2KS7b6X3+KwXmbXgD9ZGNHdYktl6x3DIzbURSBiK7Vh6O23SLKgLgy2KqGo4rHg5o+D/Gl6x3xPkiU8uBvlRR3SWOKSBZwabyMSkUQTvpiHBioot1myLcoRfY0Q/mNBiLH3V3P563WU1TUXwz6ZFtdN9tH/7ip6/V81gRT4wWAvI7p76B+wOOzBGs4fmcSaUhsFxvfquK2eMzzz13ZYY4nLRfE2IBFJnC1reYGhwO7DfLQT1SHlmCdquGlqMmePSGJHtU23NEEE/vhRkG3VymNnpO50TVmdcs6LtbxwbipZKcJ5L9Vx7kgvF4/dOe3Iac/X8uAPU3h8SZilO6KcOMjLzyfENhHcQvuQOeeF8hI2KnUHUQ/kFMyaURlvQxKJROrxxWSY20A4agTsojFJnD3CzMHlZFh4LMES4ecTfCzY0twv+IN1EQZmWXRPt0jyCGeP8DJ3087lXv8mzMReHmpCyoqiKC+el8bTy8LUhmP7ozVG1veKaQMuYIJkuEFKOxhX+NoBVeWnb9QzopuH301unIPbVtUYc/LVVWFG92h+u/sHhHlbotSGFVXlw/VRRnRrHM6Go8o980Ncf5SP2nBjqjtbIRTj/RXJhId0paIktq24YHJLu3QgiRGWKi/Qh+YJytuNzzdFeXpZmDE9LMY9UA3AX45P5vkVEb7aHkWA3CyLB39oImBtrbL52Rv1vH1RGkf09XLuCC+HPViD1zJzeL+Y0Lhqe9/CEJccmkRakjA2x0KBMfdXc+oQL1kpsc0IKYKc6lmw+pnoic2TXri0J0fF24BEIzHm+PIC52Eywbm0kfn28DkXhG525/liT5+CWTO2tlzMpT1IlKHuEfE24EBlrKxzQ3d1DG6vrwNxhc9lr6QQGppFVVm87UgAXOHrQA5+4csLeIEJ8TbjQEUEOcWzIKZuQC6AK3wdysEvfDAGSG2xlMseOc36Ii5pyRKMcbkz89PjbUSikAjC5w5z95Nx1lp3ni/2eDGJx106AFf4XFokleDQTKor4m1HAuAOdzsIV/hcWkQE62TPwm/jbUcCcHi8DUgUDm7hywskY3KZuuwnp1tf1MXbhgRgQLwNSBRiInwiMkBETnCep4qIPxbttIIBHOzi3kGMt1bnxNuGBKBfvA1IFNpdFETk58DLwIPOob7Aa+3dTisZGKd2DzrSCB7ip8ad54stXXNn5qfF24hEIBa9oaswk7SVAKq6GugRg3ZaQ26c2j3oEMH6gbXI9eeLPW6vrwOIhfAFVTXU8EJEvEC8NgTnxqndg5LTPXNr421DAuAKXwcQC+H7RET+AKSKyInAS8CbMWinNfSOU7sHJROs77rH24YEwBW+DiAWwjcTKAKWA1cAbwP/E4N2WoM7Id+OpFM/LJ26qnjbcZDjCl8H0O7Cp6q2qj6squep6rnO83gNdd0dB+2ICJ4TrUWuP19scYWvA2j3QKQisp7dzOmp6qD2bqsVuD2+duZ0z9zq1+yj423GwUz/eBuQCMQiAnPTSMcpwHlA1xi00xri5T940HK49a07zxdbusXbgESg3YVPVXfN0fB3EfkMuLm922oFrvNyO5NB3bB06qprSM2Ity0tUbduEaUfPgS2TcahPyBw5Hk7na9c8CrVy/4DlgdPWibZp1yDN9CDcMlmit+8E7WjZJ90Fcl9RqB2lMIXb6b7OX/ESkqJpdmxzxbvEhMH5sOaPCaKyJXEr+flCl87I4L3OGtJp5/nUztK8dt/R6MRVJXKL98gVLxxpzLhsq2omoRQkaoSSt+/H4CKeS9hB2vRSJiyT54EoGrxW0SrSzvC9FYLn4jMjaUhe2k3V0RWtKLcgyJylIhcKiKdysMiFsLwf00et2OCgJ4fg3Zagyt8MeAMz+edfmU3uOUb7PpGMzVUR/XSd3cqkz58Kr0uvYfAlAuJlG6hfvNKc+3Wb7FDtaA24ZLN2PXVVC3ORwHxJhNjWj0KU9Up+9uYiNwlIl+LyJ3O614i8p/9rdfhCGAecCmdzLUsFqu6xzZ5nKiqP1fVePUQXOGLAZOsbzv9PFT9xmVg2+RceBt9fn4/iEX9hmU7lUkZMBZsm6pFbyIpfsRjOlsaDWElp6NqI14fZXOewg7W0PXEXyIS28x2tK3HVy2GO0VkhYgsF5ELnHPTReStJmX/ISKXOs8LRORmZwrqV0AxYIvIAmAJ8J1TLldEPhWRxc6jmdCKyCgRWSAiX4nIMhEZ6hwf4dRzDmbe/1mnTKqIzBKRlU75u5zy3UXk3yKy0HnENERXLFZ1kzFvNrdp/ar6p/ZuqxW4wteOLE32ffdMpn9bcWmy3rDtm5fCORXRSFaKFKdU2VW+Wk/EGyVkiVUbSbZDdpIEba9H7ChJkaB6oiFJsoN47BCWhsTSiOXRiFgSVo+ExSMRtSSCSEQs5wFRRGwLiYqIbYEtKioRQcIIEYGIiEQwf6NA1PyVz97aMFIsu1vpS78Mqqp4k1W0dqPVb+jMxTZYtuCxEWvlHWsHh4vr07Te9ni6ekNZw27cWNitqk/9xvoUtZXUgWmh4Mb3vb4cr12S/0dP2pC0SM65PWuTeyfbLd2vfUNqYEZrC6cB64Fs4HXgbuBzEflfoA4oAxCRJ4DxwEkicrNzXT1QCiRjRmVVqjpJROYAE0RkOnArsAMYC3wMPCMixU57fR0b7gJ6OXVVAJsdgb3GKTMY2Axco6rvikhX4CxguKqqiGQ59dwD3K2qn4lIf+A9YERrb0RbicWq7uuYG7AICMag/taRFxAa82+77ANhCH+Ynrb8ucyM6mXJyYOjIocAh5y7xP5s+OpluSu54BCr4KOFR6UGkgf4j7CqfHbaNl9hWW3mumDUv9Gb5C9KktSQXZWSZlUm+X1lVlerkAGhInK0hGypsDO99ZFUTyiclBSOeHxEUMJ2SEJ2WMJ2mJCtErZtQrZIxLaIqMeK2t4Uu95KtYNWih3yJhP0pGjYm0qINAlGMgiG0whG/XXPeYqjNdZV55z2dd+uyfXX3/XC5CSvZV9f0Kc+laCmEJIPlm3ttnRtXXqmT6L1Xvjb9KyC8wrKai712vUrM8TjT7bsTZtrk5I80CcpSo1P6V9Ra3meWO9/6aL0mqiIHREiESQaEaLmr0TD5rkdFaJhETuC2GHBDovYERE7DHZYRM057IgI5jWq0KoE7iIyynn6DrAQEwjkScz37g7MfvlLmlySDtwGzAeWAi+o6l9FpBr4ErhdRDwYD4yG1ZsxGOELAZdh0tEOEpG/A792yowCaoHngPdVtc7pFQ/HiPIkzHtq8AaoxIjuIyKSDzT0Sk8ARjbpUWeKiF9VYzKtEgvh66uqJ8eg3rbi9vb2gQrLKn/Zn7HyFX+6bPR6RyFy2K5lDl1v2712LDh8zeCzFofTTz1hfbR0w3dbX9rmI9x/eNYRVeNrT+zuK0oZU0+obItVtm6jp6iqyqrwpnmquo3IKApN8n9T5vcXB9PTyu3klBq/Jy3cW4TsOlJqyuhaXESPyiJyagrpESoiR0rIlgqyfDVkpIdIDtTjyS4X2TmKia0hIna1hLWWsF1b9skCWFfA3S99MkZVVG2sqJUavcp/HRKxPRqKerf857xhamMFgyKIjxtLT+87K3i2r9hzlzcYXQm1EA2XkTZwCktWz/MgUJB2iBXdsZlJdY8k+QgHUwjZqRIMpxIKpRAKp0kwkkp9JI1gJF3qo6mEImnUa5oE7TTqNZWgnSoh8RMklSApEpJkwpJM2OMj7KH1n9vjMD/sQYzL2O8wYvOFc34rOwcHSQGOUtXHnf3zvxSRozEaMA74BfAw0AcjZGA6MEcChU47Dfd8LY2dii+AU4HfA7eKyE8Bn1PHckzvzu+cuxaY7JS9DzgbqBORgc77/sCpKwI8r6pVItIdeIBG/8ZrVPVzEcnDRF/qBRzivP8jgVOALcBpqhre082LhfDNFZExqro8BnW3Bbe310oKvN6NzwT8699LTwuUW9ZodjOX05T+RcbXbOzyB9MXHXadbXm6DkgO/HRANLT2q6Wlb3dfWvrxiAxvl02juhy1NjdtWL/Bds73We6qa+u3bS4pqdhoFcsGqyKtnnB/hIDXG6xITy/b4vcXl/X2l4SHpq1P8iXXdPN4In1ECOxqQ52mVpXStbRBJHdITqg4qYddkpTtqSAruaZvj0AQwOvxidcrWqlIdhdf2YoXj/EeMhLfhAlofY2pTKMCUSpmP5bmueA4Iqn1Nt272NEN6zxYona31FLW2F0kKcWOlG2yEbS6R2CBhG0hohYR2ytRTcLWZGxNRUlFyQAypO0/wMsLWleu4fMdwkRu7oXpnU0GCjAiJc7UUxLNfWnrVfVop8cH4AH+jUnMdZVzzAb+qap3iMhaoGETQlca31c9cCdGS/7bKRMAajDCuw0z5L5dVR8UkWzgUeBYzNziNuCXwGzgJ0COMwSe6tS/tyHwYKeekRgBPkdVbxCRVzHzBXsMhxcL4TsauNTZwRHE/INUVcfGoK09k1cRIS9Qg+niuzTBBnt+SsrKZwL+knkpKX1DlgymlTsGvFENpYQYAhCoKhiWUb35s2p/v6MBPL7B46ykX9vR+nmfVdfPGzq/6K3p83mL7OQ+34zuctSOHikDhmVISq/h0T69hkf7AKColktNwaZwyZZNwZJoYXlVl81EhiCNmfGSkupK0jPKtvr9xRX+jJJIWlpFsi+5rmtva0ufPrJlt1GLn04t5SmBHt5SsVXsUi/ShdL6flXzStKqSyoC6alFb3s909RWy9unb31k+7YUwmE8ffoj/kwr84prrIqbfot0zRY7VNONtDSIRD12pB7fmAmEx2cf06qbHbFriGiNhO0awna9hO2ghO0gITsiITsqYdsmbIuEbYjYXmBDq+qFD52/fsxQdxnm+7wGM78+DiM+yzAiWLnL9buKwsfAT4HfAL91jm0CZjpzhnvSimzgAswcnzj13Izp9XXDrOpuB24UkV8C1zo2v+yU/zswDSN+3wIlIlKDGcJ/yh6GwM7zd1Q1LCLLMcLdsGy/nBYiM8VC+E6JQZ37ynbMr0LCUydS+3Z62ooXMv2hb3xJw1Rk9L7UM2yzrhHzCx4VjJoAACAASURBVAvA2BUPDJl75J9rcYaeImJ5Uycf7UmZUB2ueXe2HV5zRElwy/BPtr84HLD7pB2yZFTW5OosX85YEQkIIl00I7dLNCN3bNRomI0dKZaqbzd6igs3WyWUh6we5aWpI8rLejf7vPp8tTsyMkq3+/3FlRkZpdHUtIpUn6+u62ef1Q5WxSoujtC9u9fq28dLamo4dWTGpr6HZBT2naxLWNZL2LIlim7dmGIp9BuQxLnz/6vm6e+KfSVXve+1LI/dtWdKeag6KNFIOIPkFCQ1S9Goomoh4mvxhnmtdLyka4oHaFV8tuqWiwDmsw1mmOsDopjhbU/gXkyno15VhzmLG8fvcv2FIvIPjAZEgBOB0cC/MD0xMIsTNZi5uqE09vJKMb1BMIsjipnDE0zU86EYIVqpqlERSXLqEeBGYJnT2zwP+CvQBRPFKcex4w7HviMxoj1ZVXdKfeAIYRBMfAARCTeJCWDTgrbFYufGBmfuYKgzn9AdiJeXf0ILX6HHU/ivzIxv38xIT9nu8YxGZL/TF05YrcVNX6cEy3t2L/5qdlH38dObHhfxZfgyTp9uRyu2hqtfXax26RTA2lL73fgttd9hiad+UMbYecMCk0j3BsY7QzIALCxvDw0M6xEJDJvo/PsiROu2W+WrNlrFpVutsqRKqe1lo7mhUFpOaWlaTmlp36bN06fPx7phw1z1+5NDt9xyzILrr39/UvfuvuqfXNKtQsTuu2BBra+uzmbwEB9XX92Nv95RyObNYb75qjz92t9mkdMzif+7q9DTtWtxdnl5lOhARawaMtLriURKuJ1zqdaMilKyS4roXllITl0hOaFiemgp2d5KMpNrSc8I4cuysbJbJZKGspYKOM7As52XjwGXY4a6QzE9vGmYXDNPOvf1t5jeWwNRnKGuU185JjjCXzDD5MdVdbaz+LDZGer+HpjlXL8EaJg/2wr8TFWfFZF7McL7K8ycW0MPbD1wh6p+LCK3A1eIyBBMz3Ah8DmmBxjA+Pu9hukBHu7U/0fgD46t41T1q5buUUvEwp3lfzF+O8OAxzHzC88Qn9R521sucnCxwudb/UzAv3V2Wmq3GpGRiLRr9OsxG7TZnNXIVU8d/km3Q3cgVrOgEJYn0Ds5cGnvaHjDinDNm6Ch0QC2RlPWVC05ck3VEpKs5IphmZMWDMkc5/dZqYfKbpzlvHhS+9rZY/ra2d8fCxKu2GqVrd3oKa7cLmWp1VLfX4VeAEOGDJFVq1ZRWlqa/PvffzE1O7sffn9u8p9vjWT36tXTXr16RXV9fVlyILNL8Z9vLQmUlERSU1NFPR4hGFKrvj7Kpk1hbAWvR0hPt9i2LUJRYZQxY8yiZwbVgQyqA/1bMTqtUn95KdklxXSv2tEokpSS7TEimeYP4wtg5un2iqpuBQ4REcV8vxZixEiBuZhhXhFGNJYBq53XTXnNcVo+FbPw8RgmhNzLQJLjA/hH4CPnO10FICLXYYavDSQDjzp1rQHygD9hhrMNwvc5kO/8X3c4r1/CiFxXzPA4ADyBWahIxXx352N6wFNEpGEoPwe4sqV71BKxGOqehfEZWgzmnyTxSzZ00AtfBCKz01JXPJfpr1iSkjwoYhxIh8aqvV4lRlia4rFD6bkb3ltSkHvKHqPheJIGjLYCV2k0uGhupO7TAaB9Gs6F7WBgRfmnU1eUf0qaN3PbqKwp3/ZPH9nLayXtNUNeMkmBgXaPwwbajdpeQ7Bws6ekYH1Ol7oXa1+cnJmZ6bnqqqs8Dz/8MMOGDaNHjx4A1uLFSzICgW706TOx14wZ43jkkUcoKyuTgQMvDT/y8EuhaLQ2csQR/YpWry7qcskl2Tvy80sG5N2S4yssjFgLFrQ9ELWfqiw/VVkDKGipaJFZNN07ziKBYoaPL6nqY87xp50iEeA7VT3VOf4I8JlzbrPzuAIzRH0P4+JysvO8YZR0BmYh4gbMMDfU5Po1AKp6oYgMxiwmXIOZWzwKCDsCDaZHOllVlzo+ftNV9TTHriOca99zrn0IeEhV39vb+1fVvF1eZ+zp3O6IhfCFnFUZBRCReC4uHJTCV2lJxWsZGStf9mfo+iTvKETGdUS7KSGtToruPoHTwIL8KRv7Hb/a9vj2KLoiIt6UiVM8yYfWhWven22HvzmcXRafaiOVvRYWv9trYfG7dPHlrBnV5ejNvVIHDrHE03cP1e5EOsk9hkV79xhGbyqm/Zob37uLR+99KHL0iIlbx2UPW//Uuy8M7zugfwBImTRpEl9++SXz5s2jrKyM448/nqysrkmXXXZFUjgc5sknn8wIBHKprDwlq6TkNX555Wb8/tTQFVcctWrbtmh5RnqZlZJa7fd6QzmgPUXaxZNga0sFnKHuIuflmcD5IvIxxo/vSEyP7zrMosBTGNeSi4HTm6ziPoO59/Np3C1yMmYV9VfO6wBGWBcBzzvPD8W4oQwVk1jsQ6f+czG9vGcxjtRdReQHwC2YYfStIvIT4CKMuwkiMlhV5wPzReQ0p9x7GFebj5yFi0OALapa07rb1zpiIXwvisiDQJZzYy7H+AfFg4NG+DZ6vZufzfSvezcjzV9qXE4md7QNowt0rZgPfjMEtUZ880zl16Mub7EekaRUX8ap09WeuiNU/doSjRZNYTduH2WhHUM+2/HvIYD2TB20bFTWlPLs5N6jHe//3bK1cgfX5P+FouoSonaUrNRMFvzyZS/QnzD9T51+GP/++j07f+NbdtGWHeH0jPTgmaedUfzSqy8PGjBgAI899hj19fUcd9xxZGVlceyxx/L4449zzDHHcPLJJzNnzhyf1zvp0DWrd27XsiK1aenlm/0ZJaV+f3F9ekaZNzm5JtPrDfUSoS2hvDa2XIQumFVaP8aX7V5Mj60C+DFG0G4EXsT06moww9gvaZynuxgoUNVxIjIbc/+H4WxXc/gCM/z8xmkzjNnFcT5mHu5mp/3LMb3PRU69t9EYef0EjJvKbZjh+Fs0Bi2509niJhgBXYoZmucCi52hcRFG3NuVWAifjVmGrsSM129W1fdj0E5rOGCFT0EXpiSveibTXzQ3NaV30LKG0rhNKC5MWKN7nXjPKVo0YXXwnEWh5MCEvZVrQCx/TnLmj3PsyNZvQtWv1aP1e+q5yva6dWO3161DsMK5GaMWDM86MuL3dhkvIqlNC3osD3889leM6TmMbwvXccqTP+O74gIO6Zb7fZkBgd7WHSddx0vL302+7LCzk//82v2ZfX3dVVZVb582ZFLVqAljS//vsXsPGzp0aFJxcbGkpqaSnp6OiBAO794n1ra9adVV3Q6prurGtm07j9A9nlBlenr5Fr+/uDzDXxJMTy9PSk6uCXg84d4izfzrClpx644D8jF+awpcLSI/AgY5vaQk4K+qeqaYOd73VfVZABG5UVX9znMAVHW6GN/N+apaLCIXYoa4NwNDGoasIhIELGfv/QinN7kAM5f3GGbury9mUeJtzOr/547N24EvVPXqhjehqmfv5r0pZiHjD624D/tMLITPj/EHKsUsjS/be/GYsiWObbeZoFD/Tnr68hcyM+pX+nyH2CIjW76q4xi5UVsMTTJ2+f2ZX074fRSz/alVWN7ew1OyfkUkuHRepPbj3mDv0adQsZPWVy+ftL56OV7xVQ3NnPDZ0MzDUlM86eNExJOT0Y2cjG5c9cYtzNu4hIgd5dznruYPx1xB2I4C8OPxZ6CqzN+0lJs+uJvtVUW8dvH9snT7N70i0UivU+vHMasmyD2HX1d1+St/kMuPu/CbB995aoQt6jvttNPaHC8vGvVlVlb2yKysbL7O5PXWlxkfxZJyv7842K3bptb48QUw29Hy9lKmqedM062jexqOn0LjYgQYx+IUzHx90+H3rh45qqpzRGQaZq7uaYxDs40R3B/txca4IbFKhyEiYzGOjedglsRPiElDeyMvkIxZFYqFwLcLJZZV/GJmxjevZWT4tno9o9l1K1Yn4rk7Ipu9dsu9zoWH3fBpVeaAqS2V2x2q0VCk9qMvoqHl46D5jo09keLJKByZdeSq3IzR3ZOs5JEAmyq2ce6zV/PBT5/En7z7qeYH5j/P2tKN3HnK76kMVnP1G3+iqLaMPxxzJd8Vr8efnM55YxpdU+sIFW+2StZv9BTX7rAq0moJDkTaLWryd3l5eXtd0IHv9+m+ilkwKHGG/k9gFjmedhYQzlDVsxwfvrdU9WXn2uqGhQARCWFWfN+mcW/vfRi3luswHZj/AL913FtWY3ZqNMzNLsHMKSZh5uEiInINZqh6G2boe5yqrhHzue6rqt8PpR1Xm3yMo/PtGJech1Q15mlMYykIhZjubQnxSiieVxEkL/A1e5iXihff+JLWPZvp3/RhWlrXKktGYfweOzWZNVrSGtEDGLviwWGfT76tGpE2+2+KeHxJ6Sce402dUhyqfuNTjW6bgnGG3Sv10eoei0s+6LG45AMyk7ILBqQdtum3r917RN7xV/v2JHpzNyzmhWX5vHLxfQBkJmfw5Hl/BaC8vop/zn+Wh8/6Mze881cq6qv4xaQLmNBndLehdq9uQ+3Gxe1Kqd28ySrZtMkqCRZZlVlBwoORfQq+u7I1hVT1axG5DZPKNYoRoN8Aj4nI9Zh5sctaUVUScBiQCbyA2XX1/Wqqqu5wFh3eEZHLMQsXvTFi1R+41fHauAS4XkTCmI7GT1S1yBHg55v4aP4PO88hjgeSVHUcmHBZmEWXA0/4nG0pF2CWyV8Gfq6qrfqHxojFxFn4ohD9NDV1xbOBjPJFKSkDwiKDaNz3eEBw6DptCH/UIsmhih49ChfNLsyZOH1f2xMrvVty5o+m2pEdq0PVr1aita2aNwQoCxbl3vXBn3OH9e5OSubWrwvrNhZ3T+k7UsT6fpFhVeFarn/3rzx93p10SW3esfz7509w9eSf8PrKDxnTcxhnjjyBn77yB1780T3NymZqWt9R0bS+o6ImQZqidqlUr91kFW/b5CmxS6U6O0x0CEJLUwUtRjVugtK4e8LjvN7T8G2aiPwO41x8KYCIvOFcPx8zJ/8fzKruLRgn6kwR+QqjEVeq6nwReQGY6MwD/hG4VkTOx+z0eEJV7xKR32B89iKYnRuHOz3Sx4A/i8m5/QtMp+gZoLvTzuMYUf1YRIpV9dg23Is2E4se3wBMBIX99q5uJxbTul+/dqVapOp1f/rXL/szomuTkkaqSKfqdbaVCWu0tVupABjx7bOTCnsctg2xmvn9tQXLmzM0JetKosGvF4ZrP8iG6F5/MFSVFxcuIyczg2OGDaKwfuOowu0bESTaL334lyOyJgeraiPjfv7q/6TfM+MmBnVtns1xfekmdlQXM7n/OFYWribFm4wgBCOh3bTYHEGsbPUPzo76B4+LGu+fKHaoSCpXbfQUF22xSqxyqc2JYg9GdlrNXtqq+s1Q9yZMtJViR1ieBJ5S1Sed3tm9NK6G9sL05oYDbwAvq+rpzrC3obflARap6koxUVTeU9XbnONpu7Q/ETOFNR6jIYtpdK+ZCQxU1aA0xtq7BVjiLLYc59g5TkR+Blynqj906v1v4FjVnXcHxYJYbFmb2d517ieLWi7SPmzxerY+l+lf83Z6enqxxxqD2Wt4UDBsi7bJH9Njh9IGFuQvWT/wtP0Svu/rSx51uOUbEYnUffJJNLhkLMa9ohkFxWUs2rCFXgE/f/vPpwCcMmYYZTV1HiiYOGXIKl5cuDxSWFMU/d3bfwmmeFNSvR6vvH1Jo8fVX+c8wg3TfgbAGSNO4Gev/IHHvnyZa6e27KqzR/uxfD01a0TPSNYITIwHwkRqtlnlazZaxeXbrDJfrQQXtrK64zDiVQygqqVi3JsaVkmfxuyBbeA1NclFVorInpzMj8D0/sDsBHnMWR1+bTedmKOB1xv2z4rIm03OLcNEW36NxkAIR2OEElX9SESyRaTV87exoNNO+rcjSzF7E1u9ytgWFif7Vj0TyCz8LDWlZ51lDaOT5RZoL7pU7z3axe7I3fDe5A39f/Ct7UluccK+NYhY3qS0Y4/xphxZHq556xM7smkKjvNteW0dz8//iqr6IDmZGUwa2I+ph+zsa10XCvPopwspr63zZqb6OHxIdtrRgw8pTQr3XXvcIz8e7bW8qbefdC33n3kLETvCj/713zx2zu289uP728P8ZiThTe9vdzu0v90NoLDvrKmtjcwitBzvYJ9XdXddpRWRO1X1qVbUgXPNNOB04I9O73R35WOzqtpKDv5gnXkVtZhwN+1CCEL56WmLLu6VM+fQ3H7bLundc8T76WnHOKJ3UNKjXLdY2iYnXMA4NY9c9WS7T1SLlZrl8593jC/zJ5sR/wIAS4TTxo3khlOmc/XxR/H5mg1sr9g5eO/cNRvIyczg2pOm8cvpR/Lm0lXUhmu6Pr/89cOPHZWTev6kEdtvnX1PUdSOrH16yeucPeoHpMY2lWRT5rdc5Hs+xOzWyAZwhrpzgQud8xfRuD2ttRzv1IuIDAAKVfVhjD/frsFoPwNOE5EUMQtYM5zrLKCfqn6M2eaWhQlQMsexCTEh7YtVddcwWWD2A3fI9tZE6PGBGe7us09cmWWVvuzPWPWqP92zyUQlbvVE+8HA+LW6CROZt830KF46Prm+bGEwpcvh7WwWlqfbwJSsnw+Mhr5bnMm7/szUlKEAKUlecjIzqKyrp2egyfdIIBgx6SaDkShpviQsS7BECEdtqsIVPaNSydOrZ3V/Ztmy2qfOn7XQVvsQaz/nKVvJFy0XMbTjqi5gEv1gorU0iNF0dlml3aX9hc7iyFJM/MAvMbtGPJi8HA1b3e5W1XIx0ZIfdwIN1LJzSPymPIRZQd4W68WNmPnxdSryAlcCbRqvrE3yFjydmbnhg/TULhWWNaotDrkHGze+EJ09fp1O39frq9L7rF048cYBmJDnMUHVjkbq586N1i8YXlpT2/2fH3/BdSdNIyWp0d+4Phzh8c8WUlhVQzAS4eIjxzOydw5lNXU8v+ArorbNORPG8GXBZkb1zmFwj2wAu0/a0KUjs6ZUd3FiCMboLRzZd9bUtvT62g0RuRjjYzerxcKN12SoarXjnzcH+IWqLo6Zke1MovT43mmpgA3256kpXz+b6S9dkJrSP2zyAOTG3rTOz+Btul9fdn/NlsGZlevnVAYGTWsvm3ZFxPIkpR49NWKNqnzk3Z9Vn37oyOSUpKSddll8u72I3lkBrpx+JCXVtTw4Zz6DunelS3oqvzrWbH0urqqhsq6eHpkZPDf/K6K2bZ08unr8ltrVWHiCA/1j5g8PHKG7xhDcT8oxvaYOQRrDUb2tqtdjhrhP0riPd9fy02my+urwkJidRaOc60pFZIWq7lOA244mMYQvr2IDeYFV7JKurlak5s2M9BUv+jMiq01U4jFxsrDzoqr+uv0P5jp2xUMjP5tyeyUime1h1u6IRiM8+sGszKNGXcjEUSdsCle/ukXt8u9X1hcWbOK44UMQEbr50+mankZhZQ39s7O+r+OdFd9y8uhhfLZ6PYf1703X9DT+8/VqLjpyPDbR5LVVXx2xtuorJ4bg4QsGZ47PSDYxBPdnvvyjvrOmRvfnvbeRK4Duqtqw6NEQjqrVqOp/wfdOx/cQv2DD+0RiCJ/hHWDEdo9n+/OZGd+9lZGeVmiiEh8Rb8M6M/2LWC/t4GztC1d167ljweztPY+Y3g5mNUNVefaTu+iZ1Z/jx54H0C85cHm/aHjd0nB1vg/CI7qkpbJ6RzGDunelqj5IUVU12RmNLmprC0sIpKbQ3Z9OKGIjIiYwQbS5JpkYgp9NXVH+GWke/7aRWVO+G5AxsqfX8u3LIld+aws6oZ2uw6yKLsPshngMs2GgCLhMVTc6W9UqMUGBewI3qOrLztxcOiYU1O2q+gKO47LjoPykqr7ttPUE8CZNUl46CyrPO+0tYOcVW6+IPInx7/sOs4Mj5rsw9oXEmOMDHvh7v6MfD2Q+WCsy4vuwFC4tctZc+/MffWK3S/TsqOWtn3P030rU8uzTQsneWLttOXe/cQ29uw6kofN1+qSfUlpdCKo6eVCPucWlHw19ceHSHpX1QVSV40YMZsIAswtPVXlozgJ+PPkw0nxJ7Kis4rl5X2GrcvaE0QzstsdIWDuR5euxdnTW0Zt7pQ0aZImnuXd0cxTo3XfW1BYjCTmuIa/Q3HH55SaOy6c7jsJPYATuAhzHZVUd4tTTdL9ug+PyOBE5CzhTVS8REyp/LSbC0hE4Q10x4eWLVfVPIjIDE2aqIb3EeuBoNekfH8Ps3LirVTeug0kY4Rvz5BgvJux16z7BLgDc8nTkkxGbaV1GsVawod+Jc9cOPnOv6StjhWqoJlzz3kI7vHoSu+xGiAU5qbnLR2cdVZad3GdUg+vJbljYd9bUVuVCEZGrgZ6qelOTY8VArybhqLapajdH+JqGo6pqEo6qqfBNAS5R1StEJAUTtGAIphd4vqpe1HSOz9ledraqrnOuL8WIYwYwR1X7O8ePA36jqu0eS689OPj9+ByWX7I8QmPWdpdWMqCw3SKPANB/0/uTPZH6uOzdFvGl+zJOm56c+bMKsbI/J8ZOtDvqCsZ8uO3ZaS8V3JU5vyh/YWWoZO5uhn4vtqHKWDsu12OSGJ2E6Sn+qxVt7O14p+1VJYzwObwQbwMOJDxRDac6OXTbCwEZterxPWa47wjEk9krOXDJUUkZ561EkmOe+F6xkwqqVxz+zpZHpryy4W57Weknn9dFqr9U1TBt+0zG1HHZ4V8YH8Cp7H7Bo6kz8insvHWwvzRGBv/RPtjSYSTS4gaYf+Q2aJ4wx6U5Q7eyVsz8ULvSrWTFoSn1JQvqU7L3O93l/uBJ6jfKk3UVkfpFcyN1c/qDxjzCdUTDGasq5h21qmIeKZ70d6567oVNLV9l6ADHZTBRWp7CzAnuLirDLZhQU4uBT9g5VP4q4BIxqSdW00bf2Y4kYeb4Ghjz5Jg7MNtpXFrgoo+jc86YpzHxvatO67V+weE39cXMS8Ud1Uh9uPb9+XZo1QQ6zjXjZ9e+8NajHdRWM/bFcflgIdGGumCW/l1awZj1GrPV74zabQOzKtbMjVX9bUXEm+JLP+WY5MAvasXT41MaY93FilpMbtm4oarPJKLoQQIK3/JLln9LG/ZFJjJ9SugZy/pHf/3wGFQrYtlGWxEro0dy5sVTff4LVyOpS2LY1KvXvvDW7jbqu3QAiTbH18CjQIenZzyQ8IW11heJbZRoX7ima6/tc2dv63XU9D2V+WjZy8z95m0EoXfXgVw8/QaSvL7vz/977j/5bqsJFxeK1FNdV86dl73BjvJNPPHhbdh2lAumXsOgnqOI2lH++fZMrjjpVnwtRF2xvL2HpWT9kkhw2YJI7Uc5YA9on3f9Pfe1c30ubSBRhe9ZTHKTNoda2l82P7qZqq+q8GZ6GXqbyb298Z8bCW0z88jR2iieNA9Dbm2+mFq1rIptz20DG7pM60L3HxrzNz2wifrN9fjH+el5rumkFb5eSEq/FDIP27cdYqM26BoxOVRjyrDvXpy8PefIzWo1TxheXlPEJyte5abzH8PnTebR9//EorUfceSwk78vc86UX33/fPaKV9lcvAaAz1a+yelH/Ixsf09en/8Ig3qO4tOVb3D40BNaFL2meJPHTvL4RoUitR9/Eg0ta1MCpL0w/9oX3nJHHXEk4Ya6AMsvWV4P/CMebXc5ugu51+budKz/r/oz5NYhDLl1CJkTM8mc2Fys1Fa2Pr2V3N/lMuQvQ6iYX0H9lnrqN9UDMPTPQ6n9rpZobZRweZi6dXX7LHrQcg7d9sLSSPLgda/tcWUzakcJR4JE7SihSD2BtD27FS5a8xEThphoRh7LSzgSIhQJ4rE81AarWbHhC4445AdtttEkQDrhmOTAlRHx9J6DCWy7P9y9n9e77CcJKXwO99EB2Zx2JX1YOp703Ue4UlUqFlYQOKJ5p6JuXR3JOcn4eviwvBaBIwJULakCD2hYUVvRiIIFha8U0uPs/UtsN2qDdthqa//NH032ROq+3vV4Vnp3jj/0PP747I+46enzSPVlMKLfxN3WUVq1g5Kq7QzrPR6AaaPO4KNlL/OvOXdz0vj/4p1FT3HS+Iv2a7eiWGnZyZkXTvP5Ly5A0vc1msoG4N/7bEQbEJE7ReRrJxoLItJLRP4jIr1F5OWOsKGzkrDCt/yS5SV0shXe2u9q8WZ6Se7ZPNpRuCxMUtdGLfJ28RIuC5PSO4Wkrkms/d+1BA4PENphhsypA1L3y5ac8n0LPLqvjP760WarqLXBKpYXzOWW/3qW2y5+kVCkjgXfvb/b6xet/YhxA6dhWeZHpas/h2tO/xvXnfUPfN4UKmpLyMnqx5Mf3c5j79/KjvJWu881w/L2GJySdcXEpLRTvgTP2jZefue1L7wV2efG28YVwGFO6ClworCo6lZVPbeDbOiUJKzwOfyN/R+2tBsV8yrIOiJr9yf34m7Z66JeDLl1CN1O6WZ6e2f1oPCNQjbet5HS2aVttiOjVsu8Nu09mb9XsstWjUmtK5rX9Ng3mxeT7e+JPzULj8fLoQOnsn7H7ne7LVozm4lDjtvtuTcXPMYPD7+M2Ste5fAhx3PqxEt4Z9HT+22zJ3nExOSsqwd4kg+bA7TmRu/ALKy1iIj8RESWichSEXlaRAaIyIfOsQ9FpGFP7BMicq+IzBWRdSJyrnO8aRSWC5xqT8ZEOM4VkRVOOY+I3CUiy526r3aOzxKRlc6xu5xj3UXk3yKy0Hm0S/CKeJDQwrf8kuXrMdEt4o5GlYpFux/mAiR1TSJc2rjTK1IWIanLzqPRysWVpA5MxQ7aBLcE6X9Vf8rnlmMH2+aSNrbAbEDvaMYuu78XTXYLdM3owfrCVYTC9agq325ZTE6X/s2u21G+idpgFQNzmmcXWL11KYH0bHoE+hKOBBGxsCyLUKS+XWw2CZCmT0sO/Mpjeft/Auxt0OE76QAAFHFJREFUO97d177wVosNS2P6yONU9VDgt5g56adUdSxmce7eJpc0pI/8IU4wUVU9HahT1XGq+oIThWXYbnJc/wIYCIxvqNvZCncWMMo59men7D2YcPKHY7KmPdLSe+msJLTwOdwM1MXbiOqvq0nulbzTcLYpqQNTCe4IEioKYUdsKuZX4B/fmE9CI0rJ+yV0O6Ubdshu3JKu5lxbmLhaq1ou1f6k1+0Y0KX8u+9XO3NzRjB+4DTueOVK/vLSz1BVjhoxg7cWPs6ygkbf5y+dRY1d5+9UlXcXP8MpE34MwFEjZvD6god55D95HH/o+e1qu1gpAZ//3GN8mZdsxcpcsJsiW9hZrPZGs/SRGPer55zzT2OEroHXVNV2RK016SObcgLwgKpGmrRVCdQDj4jI2TTOhZ8A/MOJ0PIGJul4hyQHam8Sbsva7hjz5JjbMYmQY86m+zdR800NkeoI3kwvPc7sQddjurL54c2kDU6j63GNUbPCZWG2PL6F3N/lAlC11LizqK10mdqFHqc3LmAUv1eMJ91Dl6O7oKpsfmAz9Vvq8Y/10/P8tvkh33dfZEH3SuKyjzbsTSv/9Ki/QmMy6gOSaGjNknDN22kQaQhM+tNrX3irVXPKIvIboIeq/k+TY7uGn9qqqt2d8FNvqerLTrmmIaeaPr8V/n97Zx4dZZXm4ecNgQAuUcQFUNlkCVjIprgv5dL2jI3TKqJ226U9pxU77d7aPW69qK02djuio+UyHqIiirb2cOwz6oiyKsqAwIcmQCCgEGQbkCCEJFXv/HFvSKWoJJWkkq8qdZ9z6qTqW+59i/Pxq7u+P5ao6jsi0s/ec6KIvA08o6ofxsWQh0lgcBVmW1vQxnBcrZ9uJuOEDwgUBfIxSRcbypmWVbz+aM3mHG2w5dDmrBw0cc7GPmenLAegX6hqtKby0wWRykUKkfPufOPdpMYcbFf3HeA0Vd1uu55TgTdV9RURuQ64VFV/3Azh+wS4WFV3xQnfJExL7ipVrbF1VQHdVXWL/Vyqqj1E5DXgC1WtnSUemcBsPCNwXV3AC3nfAX/yO4504IjvdJOfogcwqPSt0yRak6y5dtoiIjmdu51+VtfDb30oWdEDk4UFqM3CsgwzCXcLcL0Yi8ZrMeN+ycaRKAtLLS9iMqwst3Vdg/G2fdfWNQe43V57CzDWTnh8BUxKNoZ0w7X4LIGiQBdgKXGGRNnGBV9EP7vhvajvPiQbep+9cNXgiac2fWXa81+F4aCvWYizOQtLQ7gWn8ULeVWYGa6s/iUYXZoe4zfHls89Nbd6z3K/42gle4E7/A4im7OwNIQTvhi8kDefDJ6iTwUnlGub2T82lxO/fCHTTdzvLwwHfVka5GgcJ3wHcjfQpONVh0RV8/e03kM3VfTYuWp4tz2b0yZnXzP5FLcnN21xwheHF/J2YgZxs45jt7FeYrKP3LtpE2eWrmZ8WV2j5b2KXfyobC3DV5aworLxXnFElcvWlXHThrrtYXeVl/MvZWU8sXXr/mPPbtvGrIrESwdP8p45njrj60yhEvh5YTjY1slMHS3ECV8CvJD3Jg07THVYRq/R8tjPP87P5/lj61vDDuqSx5Q+fRjbrem9wK/s2MHALnX7jldWmk0Lf+/fn8V791ARibC1pgavci/nH5J4HWz3vduO7bGjeGHCk+nL7wvDwRK/g3A0jBO+hrkRyKrxmVFrtN52q7Hdu5Pfqf4jMjAvj/5dDkyiEM+31dXM+X43l+fXbcHLFWGfRomqUq1KjghPbdvKr3o2nhZx+FcvjcTsKMgEFgJpaaLtqMMJXwN4IW8XxiLPVyvE9qTfZk2Z2fqjW7bw6yOPIidmF9nAvDx6de7M5evXcfEhh/B1VRUKDOvaeGLQzjV784/dOLvNbSBTwHZgYmE4mDaJLxyJccLXCF7I+xy43+842oOcqNZ035caD93Zu3fTI7cTwxMI2r8ddTTv9OvP9T2O4KltW7m5Z0/C27dxe/lG3ty5s8EyT1jz9ukSrSlLRXxthAI/LQwHv27ySofvOOFrmj+T2Fi5QzFgE2sEWpfEz7Jk7x4+3r2bC9aUcmd5OZ/t2cPd5fWGD5lVUcHwrt3YE1VK9+3jid59mLnrO/ZGE88H5Gi08+DVM7akIr424uHCcPA9v4NwJIcTvibwQp5iuryr/I6lLRlbGk2ZqNxx5FF8PPAEPhx4An/p3Ztx3bvz596995+vVuXVnTv4eY8eVEajiE0lo/ZcQ/TZtGBcbvX3y1IVZwqZBfzO7yAcyeOELwm8kLcD+BHQLj4UfjCi7EDB+XX5Rq5ev551VVWct6aUv+3cyYcVFZy3ppSllZXctGEDv/jGLFXZUlPNjRuSy2o8fccOLj00n245OQzJy0NRLi0rY1S3bhzaqfE1y4EVz3cmvfZZrgWucUtXMgu3V7cZBIoCQUy3t8O50738eM3KrtUMafpK/1l48n0L9hzUKx2y/24HTi8MBzt0b6Aj4lp8zcALeR8Bv/I7jlTTpVr35lWnz46NpjjJe7YfqqlJodxyKoHxTvQyEyd8zcQLec/RwVJYDdmgpZJBrdhuldv7HLF9RaJswu1FFDODm6nb6bIeJ3wtwAt592L8BzoEY1e3j4duKhlePHUUGt3mU/V3FIaD7WIR6WgbnPC1EC/k3QY873ccqeDE9ZpxWVByI5WHHv/NrMSWa23LPYXhYIf50ctWnPC1jpuAV/0OorUcs4PeTV+Vfgwom3l6TrS6ub62reGBwnDwkXasz9FGOOFrBV7IiwLXUed+lXF0r9TvciP08zuOlpCj0dwhq17f3k7V3VMYDj7YTnU52hgnfK3EC3kRjAfCs37H0hJGrNO1UmdGmXH0+nbhKZ2rKr5o42rudC29joUTvhTghbyoF/J+SZ3xcsYwZrV+53cMrWXEiue6o9oWC4irgGsLw8G/JnOxdTJrd0Skn4isSOK650Qk4fpHERkvIu1isRpT5+72rC8WJ3wpxAt592PG/TImO8fQb7Tx1CgZQP6usiEHf78x1aKzA7ioMBxMegxXVU9vbaUi0pYTTeMwabMOQFVnZpMvhxO+FOOFvDBwKZARLameu+jrdwypYIQXHojqnhQVtxazI2NOc24Skd1imCwiK0TEE5GJ9ty5IvJuzLVPW39cRGSdiDwgIvOBCSIyW0QeE5HPRWSViJxlr+snIvNEZIl9HSC0IjLc3rfU2kAOsscLgFWqGhGRW0TkK3v+dXv+OhF52r4fKCILRWSRiPyxtmVmv8McEZlh43pURH5i6/NEZKC9rq+IzLLlzxKR4+3x/iLyqS3X1/HSDiN89mH7UkRqzY57icgHItJbRN5qRjn1HtCW4IW8fwCnAMWtKaetObxCt3RSevkdRyroum9Hr57bli1KQVELgVNbkUH5MmAkcBLGqHuyiCTzb1ypqmeqam3m71xVPQW4jboECFuAC1V1NDARmJKgnEnAk6o6EhgLbLDHfwjUZo/5LTBKVUeQ2Bv3SVvGyUB53LmTMJ6+AczY9mAb54vAzfaap4GXbfnTYuJ8EnjWluurr02HET5MxuTRqnqX/Xwx8L6qlqvqFe0djBfyVmG6Fu+0d93JMnKtrvM7hlQyrOTlMWirssw8CZxTGA5ubfLKhjkTmK6qEVXdjDHkPjmJ+96I+/y2/bsY9s+6dwZeEBEPeBMYlqCcT4F7ROQ3QF/V/XahP6BO+JYD06zfbk2CMk6z5cOBKxYWqeomNT4oa4AP7HEvJs7TYu57BfNvAnAGMD3muG+khfCJyM9ss3iZiLzSSFN5qohMEZFPRGStiFxhj88EDgI+q+1aYITvv2MHfkWkk4g8bpvly0XkZnv8YhEpsV2Ny2LiOkhEXrJN8y9E5NLmfC8v5FUAlwP3YbY5pRVjSlPWNUwLciP7Du779QcrW3DrTuCywnDwtsJwsKqVYTQ0Q15D/f9v8WOr38d9rjVYilC3nfB2YDOm1TUW6BJfiaq+BozHePq+LyJBEekOHKa631Pln4H/AMYAi0WkOdsVY42fojGfozS87VEbeO8bvgufiAwH7gWCqlrbjG6oqQzQC/MLcgnwKICqjgf2qupIVX3DDhAPUdX4lf03AP2pa+ZPE5GuwAuYtFNnAcfEXH8v8JFtmp+H6bYc1Jzv54U89ULew8C5wLrm3NvWDNqoB/sdQ6oZUPbu6TmRqtXNuOV/gdGF4WCqWuZzgYn2R/ZI4Gzgc2A9MExE8kQkHzi/BWXnA5vUzGBfCxwwESIiA4C1qjoFmAmMwDy7H9vzOcBxqvoxxkr1MCD+OViI+cEGuKoFcX4Sc99PgPn2/YK4477hu/ABQeAtVd0GoMZUpqGmMsDfVTVqRe3oBsocByTaxH4BEFbVmpi6hgJlqrpaTY6u2Fm8i4DfishSYDbmV/r45n9F8ELePMxD+FJL7m8L8r9ngN8xpBpBOw1dOS2ZiaUIMBk4ozAcTFVKe8UMbSwHlgEfAXer6req+g0ww56bBrRk7eEzQEhEFgKDObCVCGbsb4V9ZocCL1N/fK8T8KrtLn8BPKGq8Tn/bwPuEJHPMQ2N5k7U3QJcLyLLMQJ9qz1+K1AoIouIsTH1A9/z8YnILcBRqnpfzLFtQC9VrRaRzkC5qh4pIlOBd1X1LXvdblXTaol7/yCwRFXfEZF+9p4TReRt4BlV/TCmrpGYgdxz7OfxwA2qeomILAauUdWWdJ8aJFAUGI9pZR6VynKbQ6/t+vWTz0daJOKZwPzT/rS4Ki9/TAOnPeBfC8PBVEyGACAiR2CeubSbJReRJcA4VU3KOMt2jfeqqorIVcDVqtqsYZ50Jx1afLOAK+2Dg4j0oOGmcrKcb8uN5wNgUu2Yhq2rBOhfOxWPSTNfy/vAzSIi9vpRzYwjIV7ImwmcCBTh05jH6DW60Y9624sRK8KHJljUXIWZIR2TYtHrjZlUSEtbSVUdnazoWcYAS22L7ZfAnW0TmX/4noNNVb8UkYeBOSISwTS/bwFeEpG7gK3A9cmWZ8dVKlV1V4LTL2K6CMtFpBp4QVWfFpEbgH/YluZ8jCgBPAj8u71eMGN0l7Tke8bjhbytwHWBosDzmIHmkakoN1lGrdHWDuKnNYdWfD3okN3fzKs45Piz7KEFwI2F4eCXqa7LThoMTnW5fqGq8zATKB0W37u6qcZO0R+bSavQA0WBTpj1VA9hBpvbnP98ombZIZUd++Gu7HLY5k9Oe/D/kJw/FIaD8ctFHFlMhxO+TCZQFDgSs7j0JlJk9ZiInKhGpj8WqRSzBKijsgN4BJhSUFK8r6mLHdmFE740JFAU6AXcA/wCyEt1+QM26epHp0YGpbrcNGEv8BTwSEFJccMO5Y6sxglfGhMoChyHWUt4HSkUwAnzIvMnzNczm74yo9iMGSt9tqCk2K+U9I4MwQlfBhAoChyN2ZI3CVq/t/ahopq5g8s5u9WBpQce8ATwmuvSOpLFCV8GESgKdAYmYGa9x7W0nKLHa4q7VVOQssDaH8UsNfprQUnx//gdjCPzcMKXoQSKAiMxaxyvBvoke19uje6bNjmSI2bDe6bhAa8DbxSUFLen14ajg+GEL8MJFAVyMPtBrwGuAA5v7Prh66Nf/u616PD2iC1FrMJkLnm9oKTYD1c1RwfECV8HwnaFz8CkILoYswi1XraQn30YmXvJIk3n8b0aYAlm582bBSXFbe2n4chCnPB1YOykyEXAhZjEDydMfrFmft+tpNOMbhWwCJPVZA6woKCk2DcvBkd24IQviwgUBXpOebZm9DE7ORkYZV/9aT+XtUrM3ugv7esz4NOCkuK9jd7lcKQYJ3xZTvHQgi7AcZh0W7V/j4/5fDBmDWHsKza5hQIVmGSe8a8tmCy9pfbv1wUlxRljxOTouDjhczSb4qEFuZjsv7nA7oKS4rTLLu1wNIYTPofDkXWkQz4+h8PhaFec8Dl8QURSbQCebL37zaeauO45ETmjkfOzRWRsguOx/rRTaw2xHOmFEz6HL6jqAWbYzcWaSrUV4zCmO44OiBM+hy+IyG4xTBaRFdbyc6I9V8/UXUSeFpHr7Pt1IvKAtQKdYFtej4nI5yKySkTOstf1E5F5IrLEvg4QWhEZbu9bau1GB9njBZgdI4Ot4Q4xZS5PUM71tu45mAXksVxg41glIinJ3u1oPb6nnndkNZdhUu6fBPQEFonI3CTuq1Q1abVEZBKQq6qniMg/YTw1LsAspblQVSutoE3HeNHGMgljNDVNRLpQZ9f4Q+A9VS0WkS4iMkBV12IczGbEFiAivYA/YHwqvsPYOMbuNukHnAMMBD4WkRNUtTKJ7+hoQ1yLz+EnZwLTVTWiqpsxOzdOTuK++DTyb9u/izFCAyYJwwvWRvFNYFiCcj4F7hGR3wB9VbV2IfUPqLNjnAFcad9PTFD3OGC2qm5V1aoE52dYO9TVwFqM5aPDZ5zwOfykoR0jNdR/NrvGnY/3k63NwxehrhdzOyY56UmYll6X+EpU9TVgPCZr8/siErTWiodZAyEwQnaliAw2t2gis/LG1oTFn3Prx9IAJ3wOP5kLTBSRTtYd72zgc2A9MExE8kQkH2MX2lzygU1qLCavpa4bux8RGQCsVdUpwEyM4ft5mO4qAKq6BiOo93Ngaw7MtrtzReQI6wE9Ie78BBHJsfalA4CUejQ7WoYb43P4hQLvYJInLLOf71bVbwFEZAawHFhN/TGzZHkG+JuITMAIWXwrEUzX9afWavRb4I/29VbcdW8AkzH7mut/CdVNIvJ7TLd5EyazTKzIrsR04Y8GJrnxvfTA7dxwtDvWPH6Jqvb1O5Z4RGQJMK6ZBtyODMO1+Bztioj0BmYDj/scSkJUdbTfMTjaHtficzgcWYeb3HA4HFmHEz6Hw5F1OOFzOBxZhxM+h8ORdTjhczgcWYcTPofDkXU44XM4HFmHEz6Hw5F1OOFzOBxZhxM+h8ORdTjhczgcWYcTPofDkXU44XM4HFmHEz6Hw5F1OOFzOBxZx/8DbKyJgamI99IAAAAASUVORK5CYII=\n", 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\n", 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" ] @@ -3001,6 +4066,15 @@ "df.venue.value_counts().plot(kind='pie', autopct='%1.1f%%')" ] }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "df.to_excel(FILTERED_PAPERS_FILE, index=False)" + ] + }, { "cell_type": "code", "execution_count": null, diff --git a/src/util.py b/src/util.py index aa7128a..de85fe2 100644 --- a/src/util.py +++ b/src/util.py @@ -13,11 +13,12 @@ # Files PROJECTS_FILE = RESOURCE_DIR + os.sep + 'projects.xlsx' -FILTERED_FILE = RESOURCE_DIR + os.sep + 'filtered.xlsx' +FILTERED_FILE = RESOURCE_DIR + os.sep + 'filtered_projects.xlsx' ANNOTATED_FILE = RESOURCE_DIR + os.sep + 'annotated.xlsx' DBLP_FILE = RESOURCE_DIR + os.sep + 'dblp.xml' VENUE_KEYS = RESOURCE_DIR + os.sep + 'venue_keys.txt' PAPERS_FILE = RESOURCE_DIR + os.sep + 'papers.xlsx' +FILTERED_PAPERS_FILE = RESOURCE_DIR + os.sep + 'filtered_papers.xlsx' SCHEMA_FILE = RESOURCE_DIR + os.sep + 'create-database.sql' DATABASE_FILE = RESOURCE_DIR + os.sep + 'db-mining.db'