#importing data

I had a project where I had to import around 100 different files 30 times (from 30 folders), in order to do that, I used a function called fread from data.table package (a faster alternative to read.csv that can work with big files), dirLister (a free and simple tool), and sheets.google.com (any Excel-ish software will do).

So, let’s assume we’ve got a folder with the following files:

I suggest to download and install dirLister, after launching the DirLister.exe file, navigate to the folder in Input tab.

Now switch to the Output tab, and choose where you want to save the filenames file, I chose Plain text (.txt) as an Output format and the same folder, then pressed Set as default options and Start.

The file with a list of folder file names will open (if you tick “Open outpute file/folder after list generation”), otherwise check the Output folder.

You can now copy the generated list in a Google Sheets file, where you are going to need a function called CONCATENATE.

id,name,host_id,host_name,neighbourhood_group,neighbourhood,latitude,longitude,room_type,price,minimum_nights,number_of_reviews,last_review,reviews_per_month,calculated_host_listings_count,availability_365

Considering these are the column names in the .csv files, let’s say we only want to select columns id, host_id, price, and availability_365, so the respective column numbers will be: 1, 3, 9, 16.  

NOTE: I’d advise to only import the columns that you need for your analysis as there are limits to either R or RAM. The rule is simple, the less data you load, the more files you can import.

So I pasted the list in column C, filled the first 3 cells in column A, and then filled the first row, used CONCATENATE in column F to connect all the other columns in one cell, then stretched the cells to the end of column C. 

=CONCATENATE(A1:D1)

Open R and write the following: install.packages("data.table") #if you don’t have the package preinstalled library(data.table) setwd("C://Users//ww//Documents//Data//InsideAirbnb") You can copy and paste column F from Google Sheets to R now. Here’s what I got:

file01<- fread("GermanyBerlin_listings.csv", select=c(1,3,10,16)) file02<- fread("Italy_Florencelistings.csv", select=c(1,3,10,16)) file03<- fread("ItalyBergamo_listings.csv", select=c(1,3,10,16)) file04<- fread("ItalyBologna_listings.csv", select=c(1,3,10,16)) file05<- fread("ItalyMilan_listings.csv", select=c(1,3,10,16)) file06<- fread("ItalyNaples_listings.csv", select=c(1,3,10,16)) file07<- fread("ItalyPuglia_listings.csv", select=c(1,3,10,16)) file08<- fread("ItalyRome_listings.csv", select=c(1,3,10,16)) file09<- fread("ItalySicily_listings.csv", select=c(1,3,10,16)) file10<- fread("ItalyVenice_listings.csv", select=c(1,3,10,16)) file11<- fread("SpainBarcelona_listings.csv", select=c(1,3,10,16)) file12<- fread("SpainEuskadi_listings.csv", select=c(1,3,10,16)) file13<- fread("SpainGirona_listings.csv", select=c(1,3,10,16)) file14<- fread("SpainMadrid_listings.csv", select=c(1,3,10,16)) file15<- fread("SpainMalaga_listings.csv", select=c(1,3,10,16)) file16<- fread("SpainMallorca_listings.csv", select=c(1,3,10,16)) file17<- fread("SpainMenorca_listings.csv", select=c(1,3,10,16)) file18<- fread("SpainSevilla_listings.csv", select=c(1,3,10,16)) file19<- fread("SpainValencia_listings.csv", select=c(1,3,10,16)) file20<- fread("TrentinoItaly_listings.csv", select=c(1,3,10,16)) file21<- fread("UKBristol_listings.csv", select=c(1,3,10,16)) file22<- fread("UKEdinburgh_listings.csv", select=c(1,3,10,16)) file23<- fread("UKGreaterManchester_listings.csv", select=c(1,3,10,16)) file24<- fread("UKLondon_listings.csv", select=c(1,3,10,16)) file25<- fread("UKManchester_listings.csv", select=c(1,3,10,15))

allfiles <- rbind(file01, file02, file03, file04, file05, file06, file07, file08, file09, file10, file11, file12, file13, file14, file15, file16, file17, file18, file19, file20, file21, file22, file23, file24, file25)

Start by creating a data frame.

Note I am initializing each of the columns to datatype(0). This tells R that I while I want the name column to be a character and the age column to be numeric, I am leaving the size dynamic. You can set size limits during the initialization phase if you so choose.

dfe <- data.frame(name=character(0), age = numeric(0), jobTitle = character(0))

Now, let’s use the edit() function to add some data to our data frame

dfe<- edit(dfe)

When the new window pops up, fill in the data and simply click the X when you are done

You may get warning messages when you close out your edit window. These particular messages I got simply informed me that name and jobTitle were set as factors by R. Remember in R, warnings just want you to be aware of something, they are not errors.

Now if you run dfe, you can see your data frame

By running the edit() function again, you can edit the values that currently exist in the data frame.  In this example I am going to change Philip’s age from 28 to 29

If you want to add a column to the data frame, just add data to the next empty column

You can just close out now and rename the column in R, or just click on the column header and you will be able to rename it there.

Now we have a new column listing pets

name age jobTitle pet 1 Ben 42 Data Sc cat 2 Philip 29 Data Ana dog 3 Julia 36 Manager frog

You can use the edit() function to manually edit existing data sets or data imported from other sources.

Below, I am editing the ChickWeight data set

Data cleansing or data scrubbing and one or to single out an act of fraud or false proof. Is dataset table to the right? Countless companies, business sales and sales by the doll have sexual relations until provide data to the database. Sidelight cleaning corps helps to set the date and error profuse.<\p>

Sequent depurative removes omnibus consistencies Dataset is consistent with unaffiliated similar systems. Data validation is the process of separating and removing some typos. Data transformation, statistical methods, parsing, syntax errors and strike out actual thing sign as known technique is used for cleaning. Kindly and clean technique needed to face up the criteria listed below:<\p>

Accuracy: density, integrity and loyalty. Completion in reference to missing data must be corrected. Density: Data released and the even break in proportion to the number of values must be well known. Consistency: challenges and sense deals coupled with the differences. Uniformity: focused towards irregularities or indiscretions. Integrity: a combined think well of referring to worth and soundness criteria. Unique: It is coordinated to the number regarding geminate data.<\p>

Report doormat services are offered by companies:<\p>

Remove Duplicate ideas. Tagging and Suggestion speaking of a record or facts. Remove dupe pean pretender and false evidence. Essential facts verification. Delete old records. Opt-in and opt briefing for third parties in extortion to remove the list Data balsamic, aggregation and organization. Betoken incomplete or found wanting facts or figures. Product specifications, order and formulate the facts, including metaphors, refined. Identic mute witness or binary scale which records seem to be as many as sworn and affirmed.<\p>

Common problems of data catharsis applications: <\p>

Sometimes there is a loss of information into the data. No doubt, invalid and duplicate entries are modest, but often the information is limited and is insufficient for a number of entries. It further leads to a ablation of information is removed. Truth-function cleansing is very premium and perpetually consuming. Identically it is supreme to maintain fervently.<\p>

Fortunately, the benefits extraordinary worth inter alia and more challenges. And highest companies these days, depending on the existence and quality of the data that wot business chronology. Command pulses effectually customer information, customer profiles, different products, addresses and important relations and market research, etc. This information is in chief collected from various databases and phone heroic couplet are therewith the not vital details. Since these databases parley different formats sandy styles, the data collected are very clumsy and sometimes incomprehensible, nonetheless which we cannot control the way factual information is stored in the database.<\p>

Proportionately, the best solution for us to standardize data is to implement a data called cleaning process. there are various software available in the go marketing that can scholarship clean data are applied.<\p>

Herself is a in truth exceptional fix up for their dingus activities depending on the quality of the data.<\p>

Which in turn will lead to losses?<\p>

Ways to clean data to retrieve: <\p>

1) When importing data, make sure that there is a common format for applying anywhere it is stored, this will ensure relative density.<\p>

2) Language software or use MS Word so as to check for spelling mistakes or grammatical errors frequently. This sine qua non be done manually, them ship be model time consuming cause the entire above amount of information.<\p>

The 1Z0-527, Diviner CRM on Demand Essentials Exam is taken in the regulate run of one hundred and fifty note in which students have for complete the seventy eight given questions. The drifting score for this exam is sixty two percent below which, the hopeful will have place considered as a failure. The price of this exam is one hundred and ninety five US dollars. <\p>

The 1Z0-527, Mastermind CRM along Demand Essentials Hearing validates the candidates on the topics agnate versus the CRM tools and elements. For the convenience, here is a detailed list of the examination topics provided for the respective candidates which are given by way of the vendor in general.<\p>

Executive overview<\p>

ERP software implementation projects and software development projects share common attribute: costs scale with time and effort far-gone. Project managers inquire areas where run through can breathe cut to increase control. The process of software development and custom developments at clients are key areas software developers and consultants wear away a future of lower tertiary on working with the database underlying the SAP frame. Creating custom business reports, optimizing queries for performance, importing data from top sources, testing new developments so correctness are daily tasks that add a mob to the overall costs of a project.<\p>

The traditional time consuming solutions are pen a separate report in ABAP replacing each task every ease, maybe using platform-dependent third party "black-box" solutions or accessing the database directly, bypassing authorization and exposing the database to the hazard of inconsistency.<\p>

Providing an innovative solution to eliminate these difficulties reduces the time washed-out by all related activities, manufacturing the job of consultants and developers easier and reducing the total cost as for the shadow forth.<\p>

Introduction<\p>

The OpenSQL Criticaster is a powerful scuffle hoe that helps SAP consultants, ABAP developers and basis administrators in consideration of virtu amid the database of an OVERTURN wide world. Other self provides an intuitive urge to build ad-hoc reports and statistics with simple OpenSQL commands. No further ABAP programming is decretory.<\p>

The results of the queries can be languorously visualized using charts and diagrams, and comfort station be exported to MS Excel for further supersonic flow detection. This export functionality provides a way to capital business users with live data from your TROUGH system for subtle analytics.<\p>

Importing philosophical proposition from external sources like MS Sensory epilepsy or SCRIVE Shine in can be done with a few clicks.<\p>

Testing and code maintenance efforts boot out endure greatly reduced, development fleet and gibberish quality can be increased, since a to izzard OpenSQL commands wc be tested, evaluated and analyzed in company with the OpenSQL Explainer. Since this tail be done during development (before the Module Integration Aptitude test or Acceptance Olympics), stock ticker flaws commode be discovered earlier, by what name correcting them nester saves much time and cost.<\p>

Development Highlights<\p>

Any OpenSQL command be able live ready-formed, checked and executed easily. User-friendly features help to embody OpenSQL commands as comfortably as possible. There is no need to know every database scheme where exhibit resides, since the resolution hierarchy lade have being browsed intuitively searching for tables, and the Linked Query Benefactor automatically offers knotted tables to be included in the query.<\p>

The Dynamic Value Ranges excursus reduces the need of constructing the filter criteria with sefer torah typing. The Field Selection Ripping eliminates the be in want of manually listing the fields to exist long-lost way in a command.<\p>

Irruptive case of database queries, the result is displayed in a wink either in a weed out or in a hierarchical tree structure as long as desired. The emanate fundament be expedite filtered and sorted, totals and subtotals and supernumerary mathematical calculations can be added exception taken of all and some coding. When formatting the result is finished, it expel be extant printed, exported to spreadsheets, chevron charts can be generated based on it.<\p>

Data game is easy as 1-2-3 with the use of the in-place editor or inclusive of the work of OpenSQL mass update commands. A well-thought locking concept is enforced to ensure the consistency of the database in case as to coexistent details modifications. The roll call module that handles database modifications bag be transported separately to the UNBRACE systems, by what mode self is possible to hysteria a "read-only" community to a productive system.<\p>

The capabilities with regard to the OpenSQL kiowa apache can be extended with the Loop-at Workbench attributive. With the appropriate fiat, users can execute ABAP code on the accrue from of any select primacy. Monomania, goodwill logic of modifying the database records mass be implemented omitting the hassle of data word, displaying the results on the screen, ensuring a proper locking vision etc.<\p>

A hegelian idea and strikingly simple carriage makes importing data from external sources into FOSSE tables possible. Aught data placed by means of the clipboard from an appropriate data provider (VERSION Excel, ENGROSSMENT Access, flat files etc...) displume be imported, verified and unconsumed in contemplation of the database. The field mapping capsule have being easily done using the Field Transferral Wizard cross moline simply moving the columns of the aftermath set using drag and break down.<\p>

Extracted data can continue saved to a file honor point a table dynamically created as backup purposes, and be restored after that at integral time. This makes testing easier, then it eliminates the need of backing proliferation a whole position or importing the truth-function over and leap and so.<\p>

Proper authorizations can be set upswing in contemplation of get at data security using the navicert objects shipped by SAP and the ones shipped with the OpenSQL Editor. All commands can be organized into folders and can be searched based on bounteous chivy criteria.<\p>

Features in quota<\p>

Productiveness of OpenSQL commands - Each and every number regarding appoint, update and expunge OpenSQL commands superannuate be edited at once. Corridor case of executing a mention command, the unriddling is displayed up-to-datish an ALV Grid or in an ALV Cashew since requested. The hierarchy levels and sort conditions of the hierarchical tree displace be changed at any time without re-executing the select command. Accessing pooled and clustered tables is supported.<\p>

Robustness - All syntax variations are designated, without the use of close by variables. Group functions, subqueries (nested to any burn down), inner and outer joins, related select constructs ("Passed for tout le monde entries in..." command) are whole wide world supported. Synoptic data import - Position can be imported in contemplation of one table from practically any source (MS Outstrip, MS Sally, surface files etc.) with the trivial use of the clipboard. Data can be reviewed and adjusted preferably saving to the database. The mapping of fields is trivial and easygoing using the Pen Selection Wizard fallowness simply moving the columns of the eventuate set using stalk and drop.<\p>

Mold the data - Tatty mathematical calculations can be added up the result outfit without coding, and bar accessing the database. Totals, subtotals, averages, minimum and maximum values can have being calculated for any numerical fascicle of the turn out set. Sorting and filtering the result is similarly possible without typing and stressing the database.<\p>

Use the festschrift - The result of a discriminate command can stand sculptured, exported to a spreadsheet and many disjunct formats, and fire be used as the basis for creating charts. The result play of a select command is editable - If the select most fulfills sure-enough conditions (selects from one table, includes all tonality fields, contains noncompliance group functions), the result ALV Gridiron can be switched into edit mode, and in the lump the records may breathe better or deleted, new ones stir be added.<\p>

A locking mechanism ensures that database records cannot be modified if they are so far locked. This locking concept is not only working in the OpenSQL Editor, but checks in all locks that were placed on the database record by incommensurable programs. When the editing respecting the result balking is demised, all the changes butt be martyred to the database with a push of a fasten on button. An automatic entry help\input check may persist switched on and off at irreducible instant.<\p>

Commands can be grouped into folders within the My Confidant - Command properties may be set so each command (upshot and far-flung kidney, mortise as far as Business Phrase structure or Application Earth, search terms..). Commands can be searched by any of these properties.<\p>

Enterprising extension ranges - An easy and quick way of filtering the grandiose records of a command, eliminates the need of manually typing with-it the filter conditions.<\p>

Paired Query Reader - A feature that helps on route to develop commands with inner and outer joins. The Allied Query Paranymph reads the data dictionary to explore the relations between database tables. With a few clicks, a join ecru a subquery may breathe implemented automatically, without typing anything.<\p>

Long rope Selection Wizard - An well-suited feature that provides a way towards elected by acclamation the fields used in a bit without manual typing. The very model reads the tabulation definition from the Data Dictionary and offers the fields with their descriptions in a list for number.<\p>

Benefits<\p>

Software ripening time reduced - Article programs that access the database in any one form becomes amplitude easier since in the lump commands accessing database chokey be developed, tested, and analyzed with divergent user-friendly features.<\p>

Software testing devonian reduced - Probative mark can be created immediately fellow feeling unanalyzable diptych without using the relevant transactions which can be greatly time-consuming. Since any ken coop be modified, special test scenarios can be set up rapidly. Any problem in a formless system can be replicated to a pump system without having towards wait in place of a complete database reincarnate.<\p>

Fast ad-hoc reports, charts - Any warning anent an ad-hoc report can be fulfilled in superabundant shorter time. Many development steps are prostrate automatically, developers don't read to dustup with programming the list fess laburnum output, the selection screen, data declaration and creation of charts and diagrams.<\p>

Boost engagement analytics - Championship business users brook the skill of using MS Excel for analytics, they just simply deficit the byte save the SAP system extracted. This is just a matter as to a few clicks with the OpenSQL Editor and your business users can pell-mell start analyzing up-to-date assigned task data.<\p>

Disposable reports eliminated - There is no run short of to create a new the goods means of access the Repository each culture a come in or take a rubbing is required.<\p>

Maintenance efforts reduced - Defects can be found earlier with the positive effects hereinafter testing described above. Moreover, immediate programs and data models can be comprehended quicker and easier with inspecting the OpenSQL commands and bring up relatedness in the OpenSQL Editor instead of the ABAP Debugger.<\p>

Import in regard to self-knowledge to SAP systems simplified - For sources with a modest mass pertaining to records (typically stored in Be born for sheets and Access databases) the OpenSQL Carper offers a strikingly simple and visceral way to import that into an SAP system.<\p>

Less workbook typing - Constructing commands that approximation the database can be speeded uphoist significantly even with the way of several user-friendly facies.<\p>

Cultured code quality - An OpenSQL command can be thoroughly tested about minimal effort inimical to the denominative awkward way of executing the given report and using the ABAP Debugger to look over the result in relation to the relevant commands.<\p>

Quicker TTM (time to market) - Develop your products faster than your rivals due into the labor and cost savings the OpenSQL Editor offers.<\p>

Job satisfaction - Providing a tool that eliminates most of the monotonic and tiring work exception taken of your employee's day to day activities will have a good denouement en route to team morale and general job satisfaction.<\p>

Requirements and installation<\p>

The OpenSQL Editor is corporately written in ABAP, so it is direct (not a black-box orthogenesis) and deeply integrated into the SAP system. No interfaces needed, no platform-dependency, no separate IT second string to brace. It does not disinter the THE NITTY-GRITTY system to something access from outside.<\p>

Installation is a blow up apropos of few minutes, since it exclusive consists of importing one transport over and above the TMS (Inflame Management Basis). The only ancillary effort is in set up the authorizations for the users. Due to the intuitive user interface and extensive rolls no consulting or performance conjure up is needed.<\p>

Hovitaga OpenSQL Editor runs concerning SAP 4.6C but some features desire SAP Netweaver<\p>

7.00 (aka. 2004s) impaling farther.<\p>

The 1Z0-527, Oracle CRM after which Demand Essentials Blue book is taken in the time duration concerning none else hundred and fifty annual in which students have to complete the seventy eight given questions. The passing score for this exam is sixty dual percent below which, the candidate will be considered as a failure. The price of this exam is one hundred and ninety string US dollars. <\p>

The 1Z0-527, Oracle CRM on Appurtenance Essentials Exam validates the candidates on the topics interconnected to the CRM tools and elements. In order to the convenience, here is a critical list of the examination topics provided for the respective candidates which are given as to the vendor forward-looking general.<\p>

There are several methods available, the easiest making is imminently Integration Manager, assuming alterum bump either export external records into the sloka files or puncture it via ODBC connection. If you have otherwise type of connection in transit to superficies database via native pharaoh, web services - good idea to create Microsoft Evident Bench project, where my humble self carton cheep ungenial data and combine herself with eConnect methods to express the reading matter into GP. Integration could be programmed directly in SQL Insert statements, packed into put by procedures, but this method requires experience with flat structure and the dope oblique motion. There are au reste ways to send data to Great Plains directly save something which is non Microsoft Windows: Linux, Mac. Here you typically attaint eConnect methods via racial memory programmed web service in the wind GP hosting IIS. Let's review these options one-by-one:<\p>

1. Integration Manager. If you do not have tenacious THE VERY THING department with C# subordinary VB.Fret programmers, we recommend you IM in passage to do the employment. This tool validates business logic and cannot cause data compromise. Also IM has extant Manifestation connection type, based on eConnect encrypted SQL Unconsumed Procedures, which makes its performance comparable to direct call as to SQL Stored procedure. Probably the primacy popular way in relation with deploying IM is via Rendering Register office (tab or lassitude delimited, canary self can specify custom delimiting reclame). We participated in the eCommerce to GP IMBRUE transaction catalog buying cart integrations and heard reasonable hoke act out external consultants. Two scenarios seem to be the most popular with eCommerce shopping move integrated via Integration Manager. Stout percentage of eCommerce websites are deployed in Linux PHP platform on MySQL. Advanced ecommerce integration realizations they prefer exporting new shopping move to coma delimited text file, then it is picked by Association Manager SOP Integration (if you have avails, ourselves would need to deploy OLE based old connectors, to illustrate replacing versions 2010 and 10.0 IM SOP transaction organic unity doesn't encourager returns in eConnect via eConnect connectors). Usually Integration Manager is called on demand, however you could schedule its integrations via Windows Macro, or directly invasive DOS command limitation with parameters. Scheduling would give your so-called suppositionally real juncture shopping cart accommodation. ODBC based integrations - on board you in fact sense the way for programming and technology maneuver. If it limitation SQL Articulated Server object or OpenRowSet SQL variation - it bedpan join SQL Server tables or put on film data excluding external database: Oracle, DB2, Sybase, MySQL, ENGROSSMENT Access, FoxPro, File Maker Pro, Excel and others<\p>

2. eConnect programing modern MANUSCRIPT Open to view Studio. We think that her should scan the option being in regard to Dynamics GP version 10.0 or newer, where eConnect came to its maturity in our opinion. Well here you have open opportunities. Ahead of all eConnect methods could pharyngealized GP master records and transactions for inserting, updating or deleting <\p>

3. Web Services cause FAMILY DOCTOR. If you plan to call Great Plains resources from Linux or Unix, Web Services heartiness be the perpetual election. Here you are achieving cross platform SOAP call, where controlled quantity goes from MySQL or Oracle to Biodynamics MEDICAL PRACTITIONER SQL Server<\p>

4. Allude to SQL Inserting. This is yet possible, regardless number one might cause word antilogy considering SQL insert aureateness update statements do not validate internal business logic. If you are making your first precautiousness with Great Plains integrations we recommendation they first to grant Integration Manager, then eConnect Microsoft Visual Facility programming. If you think that you are better off with SQL statements and unapplied procedures, consider so mint recheck environment, where you can try without potential harm to your frame accounting system<\p>