データラングリング。 データのラングリング(クレンジングと整形)

データのラングリング(クレンジングと整形)

データラングリング

この記事は Retty Advent Calendar 4日目です. 昨日はさんのでした. Webなエンジニアのための「Pythonデータラングリング」入門 Rettyでサーバサイドエンジニアをしています,nakagawa ともうします. Rettyではアライアンス関連のバックエンド開発およびデータ整備を,プライベートでは野球の統計分析をPythonを駆使してやっています. このエントリーでは明日からでも現場で使える,「Pythonデータラングリング」術を簡単に紹介したいと思います. 言いたいことを3行でまとめると• 受け取ったデータのチェックやおためし利用,APIの使い方・戻り値チェックにPythonオススメ• データ操作もAPI呼び出しもデータ保存も数行のコードでイケる• 手元にJupyter環境を用意しておくと何かと取り回しが良くて便利 データラングリング(Data Wrangling) とは データ(Data)を飼いならす(Wrangling,アメリカ英語 )という意味の造語です. 意味合い的には,データの統計分析や機械学習,ディープラーニング... といった事を行う前の,• データ取得(CSV・JSONなどの構造データ,REST APIの戻り値,得体の知れないPDF,etc... データ型を整える,行列を整える,ゴミを取る,欠損値の補填etc... ひと言で言うと「前処理」 ことを意味しています. がしかし,データサイエンティストだけでなく,Webなエンジニアも,• 外部および提携先のAPIを使ってデータを取得する&サービスに取り込む. 定期的に受信するデータ(CSVやXMLなど)をサービス内で使う. といった調査・開発の前にデータの中身をチェックしたり,処理を実装する前にお試しで動かしてみたり. といった業務・プロダクトづくりは当然の用に発生するので,必ずしもデータサイエンスのためだけのものではない!と思っています. なお,「データラングリング」という言葉は,英語圏では90年代から使われ,日本でもR界隈のコミュニティで使われていた言葉とのことです,今年オライリー・ジャパン社からでた「 」でPython界隈にも輸入されたみたいです. データラングリングとはなんぞや? 等,詳しく気になる方は上記オライリー本もしくは,上記本の書評を兼ねた解説をに載せていますので,どうぞご参考になればと思います 手前味噌. Pythonではじめるデータラングリング〜Jupyter,pandas,requestsを添えて データラングリングそのものは得意な言語・好きな環境でやるのがベストです. といいつつ,当方Pythonistaかつ,Pythonは伝統的にデータの扱いに強いかつ楽するライブラリが豊富に揃っているので,今回は以下のPythonライブラリを駆使したデータラングリング例を紹介します. Jupyter(ブラウザベースの実行環境)• pandas(データ操作ライブラリ,スプレッドシート的な処理をPythonコードでガリガリ動かせる)• requests(人間に優しいhttpクライアント) なお,インストール・実行等の例はすべてMac OS(Sierra)を想定しています. 【事前準備】Anacondaのインストール&使う 今回はPythonの実行環境・パッケージ管理としてAnacondaを使います. インストール後,以下のコマンドで仮想環境を作ります(質問はすべて「Y」で答える). 「New」ボタンをポチると,インタプリタ的な画面が立ち上がります. データラングリングをしてみる 業務のデータは使えない(察し)なので,オープンデータ等で代用します. なお,今回紹介したコードはこちらにGistとして公開しているので気になる方はぜひご活用ください. csvを取り込む・操る pandasで取り込むことにより,• 取り込み import• データ検索・加工• 出力 が割とアッサリできてしまいます. 以下は野球のデータ(メジャーリーグのオープンデータ,)を用いた例です. csv' データのカラムを確認する df. csv' Jupyterだとこれらのコードの実行結果を見ながら対話的に確認ができます,楽ですね! 実際の業務では,• 貰ったCSVやデータのdumpを読み込み,件数・中身をチェック• 適当にQUERYを書いたり,filterしてみたりして欠損値や異常値を見つける• プロダクト Webアプリやバッチ を作る前に簡単なプロトタイプを実装・確認する• 設計・実装が確定する前のお試しとして,凄くやりやすいのでオススメです. 必ずしもデータサイエンティストの道具ではない!Webのエンジニアでも使えるんだぜ!!と覚えてもらえるとうれしいです. なお,JupyterのKernel 実行エンジンのこと,OSのことではない を別に入れる事により,Python以外の言語 Rubyなど でも可能です. REST APIを呼ぶ Pythonにはrequestsという「人間に優しい」Interfaceを持ったhttpクライアントがあり,その場で中身をチェックできるJupyterと共に使うとデバッグがとてもはかどります. Rettyでももくもく会などでお世話になっているを使った例です. responseはjsonなので,Pythonのjsonライブラリ(標準ライブラリです)でDictionaryにして扱っています. loads response. text notebookにするとこんな感じです. pandasの時と同様,その場でチェックできるのがすごく楽です! 結び 今回はcsvおよびAPIの扱いという簡単な例でのご紹介でした. コマンドプロンプトやシェルでやるのもOKですが,ブラウザで手軽に対話的に データを見ながらやれるJupyter(とPythonのエコシステム)をちょっと覚えるだけで面倒くさいデータの確認やデバッグがはかどるのでオススメです! Rettyでは徐々にPythonを使える・興味あるエンジニアが増えており,私が主催しているにも有志の社員が参加・運営に協力してもらっているなど,(Kotlin勢に負けず劣らず 盛り上がってきています. 個人的にはPythonを今以上に社内公用語にするのと,ちょっとしたコードの共有や設計・アルゴリズムの議論をJupyter notebookでできるようなコミュニケーションが沢山できるよう,普及活動頑張りたいと思っています. 明日はさんの「」です• むしろ「野球の人」と言ったほうが通りが良いかも? 「Python 野球」もしくは「セイバーメトリクス」でググろう• この話は別の日のエントリーにて!• 他にも「頑張ってなんとかする」という意味もあるそうです. なお,イギリス英語ではニュアンスが異なるので用法には注意が必要とのこと. Python界隈では初かもしれないけど,英語圏では90年代から,R界隈では2,3年前から言われていたみたいですよー... というご指摘を頂いたので訂正させてもらいました. Pythonでデータを扱う人は必読と言っていいくらいの名著だと思ってます• このデータの全容および,何ができるのかについてはPyConJP 2014「」で紹介させてもらいました,気になる方はどうぞ. 「ワイ,機械学習エンジニアになるンゴ」志望の方はこれぐらいスラで触れないと辛いことは覚えておいたほうが良いと思う,TensorFlowのチュートリアルとかをやる前に. Jupyter上でPHPを触れるらしく,この記事用に試す構想がありましたがタイムアップのため断念orz メインのプロダクトがPHPなのでこれ触れるともっと楽できそう. 毎度毎度応募人数オーバーで嬉しい悲鳴ですありがとうございます!.

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[データラングリング編]0から本当に機械学習を理解するために学ぶべきこと~一流のデータサイエンティストを例に~

データラングリング

Restructuring data into a desired format Data wrangling, sometimes referred to as data munging, is the process of transforming and from one "" data form into another with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics. A data wrangler is a person who performs these transformation operations. This may include further , , data aggregation, training a , as well as many other potential uses. Data munging as a process typically follows a set of general steps which begin with extracting the data in a raw form from the data source, "munging" the raw data using algorithms e. sorting or parsing the data into predefined data structures, and finally depositing the resulting content into a data sink for storage and future use. Contents• Background [ ] The "wrangler" non-technical term is often said to derive from work done by the 's NDIIPP and their program partner the Libraries based MetaArchive Partnership. The term "mung" has roots in as described in the. The term "Data Wrangler" was also suggested as the best analogy to coder for someone working with data. The terms data wrangling and data wrangler had sporadic use in the 1990s and early 2000s. This can occur in areas like major projects and the making of with a large amount of complex. In research, this involves both from research instrument to storage grid or storage facility as well as data manipulation for re-analysis via high performance computing instruments or access via cyberinfrastructure-based. Typical use [ ] The data transformations are typically applied to distinct entities e. fields, rows, columns, data values etc. within a data set, and could include such actions as extractions, parsing, joining, standardizing, augmenting, cleansing, consolidating and filtering to create desired wrangling outputs that can be leveraged downstream. The recipients could be individuals, such as or who will investigate the data further, business users who will consume the data directly in reports, or systems that will further process the data and write it into targets such as , or downstream applications. Modus operandi [ ] Depending on the amount and format of the incoming data, data wrangling has traditionally been performed manually e. via spreadsheets such as Excel or via scripts in languages such as or. , a language often used in data mining and statistical data analysis, is now also often used for data wrangling. Visual data wrangling systems were developed to make data wrangling accessible for non-programmers, and simpler for programmers. Some of these also include embedded AI and facilities to provide user assistance, and techniques to autogenerate scalable dataflow code. Other terms for these processes have included data franchising , and data munging. See also [ ]• References [ ]• Parsons, MA, MJ Brodzik, and NJ Rutter. 2004. Data management for the cold land processes experiment: improving hydrological science. HYDROL PROCESS. 18:3637-653. Kandel, Sean; Paepcke, Andreas May 2011. "Wrangler: Interactive Visual Specification of Data Transformation Scripts". SIGCHI.

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機械学習はどうやって使うのか――意外と地道な積み重ね (1/4)

データラングリング

英語版原本には日本語表記はありません。 リアルタイム更新ではありません。 同社発行の市場リサーチレポート及びリサーチサービスに関するお問い合わせは弊社までお願い致します。 でご確認いただけます。 Global Industry Analystsが発行した当調査レポートでは、データラングリングの世界市場について調査・分析し、データラングリングの世界市場規模、世界市場動向、世界市場予測、セグメント別分析、主要地域分析・市場規模予測、関連企業情報などをお届けいたします。 3 Billion, driven by a compounded growth of 20. Tools, one of the segments analyzed and sized in this study, displays the potential to grow at over 21. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 3 Billion by the year 2025, Tools will bring in healthy gains adding significant momentum to global growth. 3 Million worth of projected demand in the region will come from other emerging Eastern European markets. 5 Million by the close of the analysis period. 7 Million in terms of addressable opportunity for the picking by aspiring businesses and their astute leaders. Presented in visually rich graphics are these and many more need-to-know quantitative data important in ensuring quality of strategy decisions, be it entry into new markets or allocation of resources within a portfolio. Several macroeconomic factors and internal market forces will shape growth and development of demand patterns in emerging countries in Asia-Pacific, Latin America and the Middle East. All research viewpoints presented are based on validated engagements from influencers in the market, whose opinions supersede all other research methodologies. - Competitors identified in this market include among others, Alteryx, Inc. USA ; Brillio USA ; Cooladata Ltd. Israel ; Dataiku SAS France ; Datameer, Inc. USA ; Datawatch Corporation USA ; Hitachi Vantara Corporation USA ; IBM Corporation USA ; Ideata Analytics India ; Impetus Technologies, Inc. USA ; Infogix, Inc. USA ; Informatica LLC USA ; Innovative Routines International IRI , Inc. USA ; Onedot AG Switzerland ; Oracle Corporation USA ; Paxata, Inc. USA ; Rapid Insight. USA ; SAS Institute, Inc. USA ; Talend SA France ; Teradata USA ; TIBCO Software, Inc. USA ; Tmmdata USA ; Trifacta USA ; Unifi Software Inc. USA I. METHODOLOGY II. EXECUTIVE SUMMARY 1. FOCUS ON SELECT PLAYERS 3. COMPETITION ALTERYX, INC. BRILLIO COOLADATA LTD. DATAIKU SAS DATAMEER DATAWATCH CORPORATION HITACHI VANTARA CORPORATION IBM CORPORATION IDEATA ANALYTICS IMPETUS TECHNOLOGIES INFOGIX INFORMATICA INNOVATIVE ROUTINES INTERNATIONAL IRI ONEDOT AG ORACLE CORPORATION PAXATA RAPID INSIGHT. SAS INSTITUTE TALEND SA TIBCO SOFTWARE TMMDATA TERADATA CORPORATION TRIFACTA UNIFI SOFTWARE INC. 3 Billion, driven by a compounded growth of 15. Solutions, one of the segments analyzed and sized in this study, displays the potential to grow at over 14. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 6 Billion by the year 2025, Solutions will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 16. Within Europe,... 9 Billion, driven by a compounded growth of 21. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 7 Billion by the year 2025, Platform will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 23. Within Europe,... 5 Billion, driven by a compounded growth of 20. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 4 Billion by the year 2025, Tools will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 22. Within... 8 Billion, driven by a compounded growth of 22. Solution, one of the segments analyzed and sized in this study, displays the potential to grow at over 19. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 4 Billion by the year 2025, Solution will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 25. Within... 3 Billion, driven by a compounded growth of 31. Solution, one of the segments analyzed and sized in this study, displays the potential to grow at over 28. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 4 Million by the year 2025, Solution will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 35. Within Europe,... 5 Billion, driven by a compounded growth of 13. Tools, one of the segments analyzed and sized in this study, displays the potential to grow at over 13. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 8 Billion by the year 2025, Tools will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 14. Within Europe,... 4 Billion, driven by a compounded growth of 12. Technology Type, one of the segments analyzed and sized in this study, displays the potential to grow at over 12. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 4 Billion by the year 2025, Technology Type will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 13. 3 Billion, driven by a compounded growth of 23. Software, one of the segments analyzed and sized in this study, displays the potential to grow at over 24. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 8 Billion by the year 2025, Software will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 26. Within Europe,... 7 Billion, driven by a compounded growth of 19. Cloud, one of the segments analyzed and sized in this study, displays the potential to grow at over 22. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 8 Billion by the year 2025, Cloud will bring in healthy gains adding significant momentum to global growth. Within Europe,... 7 Billion, driven by a compounded growth of 27. On-Premises, one of the segments analyzed and sized in this study, displays the potential to grow at over 26. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 1 Billion by the year 2025, On-Premises will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 30. Within Europe,... On-Premise, one of the segments analyzed and sized in this study, displays the potential to grow at over 17. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 1 Billion by the year 2025, On-Premise will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 20. Within Europe, which... 2 Billion, driven by a compounded growth of 26. Solutions, one of the segments analyzed and sized in this study, displays the potential to grow at over 25. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 6 Billion by the year 2025, Solutions will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 29. Within Europe, which... 8 Billion, driven by a compounded growth of 20. Hardware, one of the segments analyzed and sized in this study, displays the potential to grow at over 19. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 7 Billion by the year 2025, Hardware will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 21. Within Europe,... 3 Billion, driven by a compounded growth of 8. Software, one of the segments analyzed and sized in this study, displays the potential to grow at over 7. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. - Representing the developed world, the United States will maintain a 9. Within Europe,... 7 Billion, driven by a compounded growth of 24. Services, one of the segments analyzed and sized in this study, displays the potential to grow at over 25. The shifting dynamics supporting this growth makes it critical for businesses in this space to keep abreast of the changing pulse of the market. 3 Billion by the year 2025, Services will bring in healthy gains adding significant momentum to global growth. - Representing the developed world, the United States will maintain a 27. Within Europe,...

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