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Python Business Intelligence Cookbook : Leverage the Computational Power of Python with More Than 60 Recipes That Arm You with the Required Skills to Make Informed Business Decisions

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: Birmingham : Packt Publishing, 2015Description: 1 Online-Ressource (202 p)ISBN:
  • 9781785289668
Subject(s): Additional physical formats: 9781785287466 | Erscheint auch als: 9781785287466 Druck-AusgabeDDC classification:
  • 5.133
  • 005.13/3
Online resources: Summary: Cover -- Copyright -- Credits -- About the Author -- About the Reviewer -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: Getting Set Up to Gain Business Intelligence -- Introduction -- Installing Anaconda -- Learn about the Python libraries we will be using -- Installing, configuring, and running MongoDB -- Installing Rodeo -- Starting Rodeo -- Installing Robomongo -- Using Robomongo to query MongoDB -- Downloading the UK Road Safety Data dataset -- Chapter 2: Making Your Data All It Can Be -- Importing a CSV file into MongoDB -- Importing an Excel file into MongoDB -- Importing a JSON file into MongoDB -- Importing a plain text file into MongoDB -- Retrieving a single record using PyMongo -- Retrieving multiple records using PyMongo -- Inserting a single record using PyMongo -- Inserting multiple records using PyMongo -- Updating a single record using PyMongo -- Updating multiple records using PyMongo -- Deleting a single record using pymongo -- Deleting multiple records using PyMongo -- Importing a CSV file into a Pandas DataFrame -- Renaming column headers in Pandas -- Filling in missing values in Pandas -- Removing punctuation in Pandas -- Removing whitespace in Pandas -- Removing any string from within a string in Pandas -- Merging two datasets in Pandas -- Titlecasing anything -- Uppercasing a column in Pandas -- Updating values in place in Pandas -- Standardizing a Social Security number in Pandas -- Standardizing dates in Pandas -- Converting categories to numbers in Pandas for a speed boost -- Chapter 3: Learning What Your Data Truly Holds -- Creating a Pandas DataFrame from a MongoDB query -- Creating a Pandas DataFrame from a CSV file -- Creating a Pandas DataFrame from an Excel file -- Creating a Pandas DataFrame from a JSON file -- Creating a data quality report.PPN: PPN: 859364607Package identifier: Produktsigel: ZDB-30-PQE
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