Getting and Cleaning Data

Start Date: 07/05/2020

Course Type: Common Course

Course Link:

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About Course

Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data.

Deep Learning Specialization on Coursera

Course Introduction

Getting and Cleaning Data The course covers the basic elements of data analysis, data extraction, and analysis of data using Python. The course utilizes Python 3. Upon completing this course, you will be able to: 1. Describe the different data types in the Python programming environment 2. Extract data using various data types 3. Clean data by extracting data types 4. Compute data types 5. Extract data from/load/save files 6. Manipulate and manipulate data 7. Extract and display data In this course, we will focus on the elements of data that are important for extracting meaningful information from data. We will also discuss the elements of data that are used for extracting meaningful information. This will give you a good understanding on how to use data in analytical and/or other roles.Week 1: Getting Started Week 2: Extracting Data Week 3: Extracting Data and Cleaning Data Week 4: Comparing Data with Indicator Lines Global Health and Humanitarianism The course examines global humanitarianism and humanitarianism in relation to the political, institutional, and socio-economic contexts of the world. It provides an introduction to the basics of global humanitarian law and the standards of conduct that govern the conduct of humanitarian and development activities. It will also examine the origins of global humanitarianism and the evolution of humanitarian principles and norms. It will also consider the role of humanitarian

Course Tag

Data Manipulation Regular Expression (REGEX) R Programming Data Cleansing

Related Wiki Topic

Article Example
Tidy data Tidy data provide standards and concepts for data cleaning, and with tidy data there’s no need to start from scratch and reinvent new methods for data cleaning.
Cleaning Cleaning is the process of removing unwanted substances, such as dirt, infectious agents, and other impurities, from an object or environment. Cleaning occurs in many different contexts, and uses many different methods. Several occupations are devoted to cleaning.
Spray-and-vac cleaning Spray-and-vac systems first became popular for restroom cleaning. However, over the years, users of the equipment have found a variety of uses for the equipment, including cleaning chairs and tables in cafeterias, cleaning carpets and hard-surface flooring, and deep cleaning a variety of surfaces.
Data migration Automated and manual data cleaning is commonly performed in migration to improve data quality, eliminate redundant or obsolete information, and match the requirements of the new system.
Cleaning Cleaning occurs in various commercial, industrial, environmental, and domestic contexts, which differ in scale and requirements.
Commercial cleaning Commercial office cleaning companies use a wide variety of cleaning methods, chemicals, and equipment to facilitate and expedite the cleaning process. The scope of work may include all internal, general and routine cleaning - including floors, tiles, partition walls, internal walls, suspended ceilings, lighting, furniture and cleaning, window cleaning, deep cleans of sanitary conveniences and washing facilities, kitchens and dining areas, consumables and feminine hygiene facilities as well as cleaning of telephones, IT, and other periodic cleaning as required. Carpet cleaning though, even with regular vacuuming, needs hot water extraction applied every 18 to 24 months. External cleaning, litter picking, and removal of graffiti may also be incorporated.
Megasonic cleaning Megasonic Cleaning is a type of acoustic cleaning, related to ultrasonic cleaning. It is a gentler cleaning mechanism, less likely to cause damage, and is used in wafer, medical implant, and industrial part cleaning.
Carpet cleaning Wet shampoo cleaning with rotary machines, followed by thorough wet vacuuming, was widespread until about the 1970s, but industry perception of shampoo cleaning changed with the advent of encapsulation. Hot-water extraction, also regarded as preferable, had not been introduced either. Wet shampoos were once formulated from coconut oil soaps; wet shampoo residues can be foamy or sticky, and steam cleaning often reveals dirt unextracted by shampoos. Since no rinse is performed, the powerful residue can continue to collect dirt after cleaning, leading to the misconception that carpet cleaning can lead to the carpet getting "dirtier faster" after the cleaning. The best method is to combine shampoo and extraction, first shampoo with a spin brush to loosen the dirt and the pile, then extraction the carpet. But this needs time and double rinsed is necessary and the drying time is up to 24 hours.
Parts cleaning The rather general rules includes the classification in intermediate cleaning, final cleaning, precision cleaning and critical cleaning (s. table), in practice seen only as a general guideline.
Spray-and-vac cleaning Spray-and-vac cleaning is a “no-touch” method - cleaning is accomplished without the need for workers to touch soiled surfaces with their hands - used in professional cleaning in which a pressurized, diluted cleaning solution is applied to soiled or contaminated surfaces.
Parts cleaning For the activities described here the following terms are often found: metal cleaning, metal surface cleaning, component cleaning, degreasing, parts washing, parts cleaning. These are well established in technical language usage but they have their shortcomings. Metal cleaning can easily be mixed up with refinement of unpurified metals. Metal surface cleaning and metal cleaning do not consider the increasing usage of plastics and composite materials in this sector. The term component cleaning leaves out the cleaning of steel sections and sheets and finally degreasing only describes a part of the topic as in most cases also chips, fines, particles, salts etc. have to be removed..
Cleaning Cleaning is broadly achieved through mechanical action and/or solvent action; many methods rely on both processes.
Wet cleaning It is not the use of water that makes wet cleaning a safest method for cleaning clothes. Computer-controlled wet cleaning machines, special dryers, safe detergents and non-toxic spot removers are what make wet cleaning an environmentally sound method. Wet cleaning machines have controls that allow them to safely and efficiently clean a wide variety of garments in water. Detergents and spot removers are made of ingredients that are safer for workers and the environment, yet are as safe and effective at removing soils, stains and odors as dry cleaning solvents. Equipment, detergents and skill all contribute to successful wet cleaning.
Tube cleaning Tube cleaning describes the activity of, or device for, the cleaning and maintenance of fouled tubes.
Parts cleaning When choosing cleaning techniques, cleaning agents and cleaning processes, the subsequent processes, i.e. the further processing of the cleaned parts is of special interest.
Steam cleaning Steam cleaning involves using steam for cleaning. Its uses include domestic applications in cleaning flooring and household dirt removal, and industrial uses in removing grease and dirt from engines.
Parts cleaning A selection system for component cleaning developed by the University of Dortmund, assisting the users to analyse their cleaning tasks with regard to the suitable cleaning processes and cleaning agents (German only, link see below).
Cleaning Some objects and materials require specialized cleaning techniques, due to their shape, location, or the material properties of the object and contaminants.
Data profiling Additionally, data may be conducted in the data warehouse development process after data has been loaded into staging, the data marts, etc. Conducting data at these stages helps ensure that data cleaning and transformations have been done correctly and in compliance of requirements.
Wet cleaning Wet cleaning refers to methods of professional cleaning that, in contrast to traditional dry cleaning, avoids the use of chemical solvents, the most common of which is tetrachloroethylene (commonly called perchloroethylene or "perc"). Environmental groups and the United States Environmental Protection Agency have indicated that such alternative "wet cleaning" methods are better for the environment than perc, and proponents of wet cleaning state that these methods can be used without shrinking or otherwise damaging garments that typically require dry cleaning.