Python data analysis :: data manipulation and complex data analysis with Python /
Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Pytho...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham :
Packt Publishing,
2017.
|
| Ausgabe: | Second edition. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries. |
| Beschreibung: | 1 online resource (v, 307 pages) : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781787127920 1787127923 |
Internformat
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-4-EBA-ocn983204704 | ||
| 003 | OCoLC | ||
| 005 | 20241004212047.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 170420s2017 enka ob 001 0 eng d | ||
| 040 | |a UMI |b eng |e rda |e pn |c UMI |d OSU |d IDEBK |d TOH |d OCLCF |d TEFOD |d OCLCQ |d N$T |d COO |d UOK |d CEF |d KSU |d DEBBG |d UAB |d UKAHL |d ESU |d OCLCO |d OCLCQ |d OCLCO |d OCLCQ | ||
| 020 | |a 9781787127920 |q (electronic bk.) | ||
| 020 | |a 1787127923 |q (electronic bk.) | ||
| 020 | |z 9781787127487 | ||
| 035 | |a (OCoLC)983204704 | ||
| 050 | 4 | |a QA76.73.P98 | |
| 072 | 7 | |a COM |x 051360 |2 bisacsh | |
| 082 | 7 | |a 005.133 |2 23 | |
| 049 | |a MAIN | ||
| 100 | 1 | |a Fandango, Armando, |e author. | |
| 245 | 1 | 0 | |a Python data analysis : |b data manipulation and complex data analysis with Python / |c Armando Fandango. |
| 250 | |a Second edition. | ||
| 264 | 1 | |a Birmingham : |b Packt Publishing, |c 2017. | |
| 300 | |a 1 online resource (v, 307 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed September 22, 2017) | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Getting started with Python libraries -- NumPy Arrays -- The Pandas Primer -- Statistics and Linear Algebra -- Retrieving, Processing, and Storing Data -- Data Visualization -- Singal Processing and Time Series -- Working with Databases -- Analyzing Textual Data and Social Media -- Predictive Analytics and Machine Learning -- Environments Outside the Python Ecosystem and Cloud Computing -- Performance Tuning, Profiling, and Concurrency | |
| 520 | 3 | |a Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries. | |
| 650 | 0 | |a Python (Computer program language) |0 http://id.loc.gov/authorities/subjects/sh96008834 | |
| 650 | 0 | |a Programming languages (Electronic computers) |0 http://id.loc.gov/authorities/subjects/sh85107313 | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 7 | |a COMPUTERS / Programming Languages / Python |2 bisacsh | |
| 650 | 7 | |a Programming languages (Electronic computers) |2 fast | |
| 650 | 7 | |a Python (Computer program language) |2 fast | |
| 856 | 4 | 0 | |l FWS01 |p ZDB-4-EBA |q FWS_PDA_EBA |u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1495814 |3 Volltext |
| 938 | |a Askews and Holts Library Services |b ASKH |n AH32239346 | ||
| 938 | |a ProQuest MyiLibrary Digital eBook Collection |b IDEB |n cis37298710 | ||
| 938 | |a EBSCOhost |b EBSC |n 1495814 | ||
| 994 | |a 92 |b GEBAY | ||
| 912 | |a ZDB-4-EBA | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBA-ocn983204704 |
|---|---|
| _version_ | 1816882386506350592 |
| adam_text | |
| any_adam_object | |
| author | Fandango, Armando |
| author_facet | Fandango, Armando |
| author_role | aut |
| author_sort | Fandango, Armando |
| author_variant | a f af |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.73.P98 |
| callnumber-search | QA76.73.P98 |
| callnumber-sort | QA 276.73 P98 |
| callnumber-subject | QA - Mathematics |
| collection | ZDB-4-EBA |
| contents | Getting started with Python libraries -- NumPy Arrays -- The Pandas Primer -- Statistics and Linear Algebra -- Retrieving, Processing, and Storing Data -- Data Visualization -- Singal Processing and Time Series -- Working with Databases -- Analyzing Textual Data and Social Media -- Predictive Analytics and Machine Learning -- Environments Outside the Python Ecosystem and Cloud Computing -- Performance Tuning, Profiling, and Concurrency |
| ctrlnum | (OCoLC)983204704 |
| dewey-full | 005.133 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.133 |
| dewey-search | 005.133 |
| dewey-sort | 15.133 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| edition | Second edition. |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03463cam a2200481 i 4500</leader><controlfield tag="001">ZDB-4-EBA-ocn983204704</controlfield><controlfield tag="003">OCoLC</controlfield><controlfield tag="005">20241004212047.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr cnu---unuuu</controlfield><controlfield tag="008">170420s2017 enka ob 001 0 eng d</controlfield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">UMI</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">UMI</subfield><subfield code="d">OSU</subfield><subfield code="d">IDEBK</subfield><subfield code="d">TOH</subfield><subfield code="d">OCLCF</subfield><subfield code="d">TEFOD</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">N$T</subfield><subfield code="d">COO</subfield><subfield code="d">UOK</subfield><subfield code="d">CEF</subfield><subfield code="d">KSU</subfield><subfield code="d">DEBBG</subfield><subfield code="d">UAB</subfield><subfield code="d">UKAHL</subfield><subfield code="d">ESU</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCQ</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781787127920</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1787127923</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">9781787127487</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)983204704</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QA76.73.P98</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">COM</subfield><subfield code="x">051360</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="082" ind1="7" ind2=" "><subfield code="a">005.133</subfield><subfield code="2">23</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">MAIN</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Fandango, Armando,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Python data analysis :</subfield><subfield code="b">data manipulation and complex data analysis with Python /</subfield><subfield code="c">Armando Fandango.</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">Second edition.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Birmingham :</subfield><subfield code="b">Packt Publishing,</subfield><subfield code="c">2017.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (v, 307 pages) :</subfield><subfield code="b">illustrations</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="588" ind1="0" ind2=" "><subfield code="a">Online resource; title from PDF title page (EBSCO, viewed September 22, 2017)</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references and index.</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">Getting started with Python libraries -- NumPy Arrays -- The Pandas Primer -- Statistics and Linear Algebra -- Retrieving, Processing, and Storing Data -- Data Visualization -- Singal Processing and Time Series -- Working with Databases -- Analyzing Textual Data and Social Media -- Predictive Analytics and Machine Learning -- Environments Outside the Python Ecosystem and Cloud Computing -- Performance Tuning, Profiling, and Concurrency</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Python (Computer program language)</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh96008834</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Programming languages (Electronic computers)</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh85107313</subfield></datafield><datafield tag="650" ind1=" " ind2="6"><subfield code="a">Python (Langage de programmation)</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">COMPUTERS / Programming Languages / Python</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Programming languages (Electronic computers)</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Python (Computer program language)</subfield><subfield code="2">fast</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="l">FWS01</subfield><subfield code="p">ZDB-4-EBA</subfield><subfield code="q">FWS_PDA_EBA</subfield><subfield code="u">https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1495814</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">Askews and Holts Library Services</subfield><subfield code="b">ASKH</subfield><subfield code="n">AH32239346</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">ProQuest MyiLibrary Digital eBook Collection</subfield><subfield code="b">IDEB</subfield><subfield code="n">cis37298710</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">EBSCOhost</subfield><subfield code="b">EBSC</subfield><subfield code="n">1495814</subfield></datafield><datafield tag="994" ind1=" " ind2=" "><subfield code="a">92</subfield><subfield code="b">GEBAY</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-4-EBA</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-863</subfield></datafield></record></collection> |
| id | ZDB-4-EBA-ocn983204704 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:27:47Z |
| institution | BVB |
| isbn | 9781787127920 1787127923 |
| language | English |
| oclc_num | 983204704 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (v, 307 pages) : illustrations |
| psigel | ZDB-4-EBA |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Packt Publishing, |
| record_format | marc |
| spelling | Fandango, Armando, author. Python data analysis : data manipulation and complex data analysis with Python / Armando Fandango. Second edition. Birmingham : Packt Publishing, 2017. 1 online resource (v, 307 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Online resource; title from PDF title page (EBSCO, viewed September 22, 2017) Includes bibliographical references and index. Getting started with Python libraries -- NumPy Arrays -- The Pandas Primer -- Statistics and Linear Algebra -- Retrieving, Processing, and Storing Data -- Data Visualization -- Singal Processing and Time Series -- Working with Databases -- Analyzing Textual Data and Social Media -- Predictive Analytics and Machine Learning -- Environments Outside the Python Ecosystem and Cloud Computing -- Performance Tuning, Profiling, and Concurrency Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Programming languages (Electronic computers) http://id.loc.gov/authorities/subjects/sh85107313 Python (Langage de programmation) COMPUTERS / Programming Languages / Python bisacsh Programming languages (Electronic computers) fast Python (Computer program language) fast FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1495814 Volltext |
| spellingShingle | Fandango, Armando Python data analysis : data manipulation and complex data analysis with Python / Getting started with Python libraries -- NumPy Arrays -- The Pandas Primer -- Statistics and Linear Algebra -- Retrieving, Processing, and Storing Data -- Data Visualization -- Singal Processing and Time Series -- Working with Databases -- Analyzing Textual Data and Social Media -- Predictive Analytics and Machine Learning -- Environments Outside the Python Ecosystem and Cloud Computing -- Performance Tuning, Profiling, and Concurrency Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Programming languages (Electronic computers) http://id.loc.gov/authorities/subjects/sh85107313 Python (Langage de programmation) COMPUTERS / Programming Languages / Python bisacsh Programming languages (Electronic computers) fast Python (Computer program language) fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh96008834 http://id.loc.gov/authorities/subjects/sh85107313 |
| title | Python data analysis : data manipulation and complex data analysis with Python / |
| title_auth | Python data analysis : data manipulation and complex data analysis with Python / |
| title_exact_search | Python data analysis : data manipulation and complex data analysis with Python / |
| title_full | Python data analysis : data manipulation and complex data analysis with Python / Armando Fandango. |
| title_fullStr | Python data analysis : data manipulation and complex data analysis with Python / Armando Fandango. |
| title_full_unstemmed | Python data analysis : data manipulation and complex data analysis with Python / Armando Fandango. |
| title_short | Python data analysis : |
| title_sort | python data analysis data manipulation and complex data analysis with python |
| title_sub | data manipulation and complex data analysis with Python / |
| topic | Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Programming languages (Electronic computers) http://id.loc.gov/authorities/subjects/sh85107313 Python (Langage de programmation) COMPUTERS / Programming Languages / Python bisacsh Programming languages (Electronic computers) fast Python (Computer program language) fast |
| topic_facet | Python (Computer program language) Programming languages (Electronic computers) Python (Langage de programmation) COMPUTERS / Programming Languages / Python |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1495814 |
| work_keys_str_mv | AT fandangoarmando pythondataanalysisdatamanipulationandcomplexdataanalysiswithpython |