I am trying to read data from a csv using pandas, like so :
import pandas as p
loadData = lambda f: np.genfromtxt(open(f,'r'), delimiter=',')
print "loading data.."
traindata = list(np.array(p.read_csv('FinalCSVFin.csv', delimiter=";"))[:,2])
I wish for this to give me a list of the 2nd column of the FinalCSVFin.csv. However, it is returning the error :
---------------------------------------------------------------------------
CParserError Traceback (most recent call last)
<ipython-input-7-de5ad26b44d2> in <module>()
7
8 print "loading data.."
CParserError: Error tokenizing data. C error: Expected 5 fields in line 3, saw 16
An extract of the CSV :
url;urlid;boilerplate;label;alexarank;;;;
http://www.bloomberg.com/news/2010-12-23/ibm-predicts-holographic-calls-air-breathing-batteries-by-2015.html;4042;"{""title"":""IBM Sees Holographic Calls Air Breathing Batteries ibm sees holographic calls, air-breathing batteries"",""body"":""A sign stands outside the International Business Machines Corp IBM Almaden Research Center campus in San Jose California Photographer Tony Avelar Bloomberg Buildings stand at the International Business Machines Corp IBM Almaden Research Center campus in the Santa Teresa Hills of San Jose California Photographer Tony Avelar Bloomberg By 2015 your mobile phone will project a 3 D image of anyone who calls and your laptop will be powered by kinetic energy At least that s what International Business Machines Corp sees in its crystal ball The predictions are part of an annual tradition for the Armonk New York based company which surveys its 3 000 researchers to find five ideas expected to take root in the next five years IBM the world s largest provider of computer services looks to Silicon Valley for input gleaning many ideas from its Almaden research center in San Jose California Holographic conversations projected from mobile phones lead this year s list The predictions also include air breathing batteries computer programs that can tell when and where traffic jams will take place environmental information generated by sensors in cars and phones and cities powered by the heat thrown off by computer servers These are all stretch goals and that s good said Paul Saffo managing director of foresight at the investment advisory firm Discern in San Francisco In an era when pessimism is the new black a little dose of technological optimism is not a bad thing For IBM it s not just idle speculation The company is one of the few big corporations investing in long range research projects and it counts on innovation to fuel growth Saffo said Not all of its predictions pan out though IBM was overly optimistic about the spread of speech technology for instance When the ideas do lead to products they can have broad implications for society as well as IBM s bottom line he said Research Spending They have continued to do research when all the other grand research organizations are gone said Saffo who is also a consulting associate professor at Stanford University IBM invested 5 8 billion in research and development last year 6 1 percent of revenue While that s down from about 10 percent in the early 1990s the company spends a bigger share on research than its computing rivals Hewlett Packard Co the top maker of personal computers spent 2 4 percent last year At Almaden scientists work on projects that don t always fit in with IBM s computer business The lab s research includes efforts to develop an electric car battery that runs 500 miles on one charge a filtration system for desalination and a program that shows changes in geographic data IBM rose 9 cents to 146 04 at 11 02 a m in New York Stock Exchange composite trading The stock had gained 11 percent this year before today Citizen Science The list is meant to give a window into the company s innovation engine said Josephine Cheng a vice president at IBM s Almaden lab All this demonstrates a real culture of innovation at IBM and willingness to devote itself to solving some of the world s biggest problems she said Many of the predictions are based on projects that IBM has in the works One of this year s ideas that sensors in cars wallets and personal devices will give scientists better data about the environment is an expansion of the company s citizen science initiative Earlier this year IBM teamed up with the California State Water Resources Control Board and the City of San Jose Environmental Services to help gather information about waterways Researchers from Almaden created an application that lets smartphone users snap photos of streams and creeks and report back on conditions The hope is that these casual observations will help local and state officials who don t have the resources to do the work themselves Traffic Predictors IBM also sees data helping shorten commutes in the next five years Computer programs will use algorithms and real time traffic information to predict which roads will have backups and how to avoid getting stuck Batteries may last 10 times longer in 2015 than today IBM says Rather than using the current lithium ion technology new models could rely on energy dense metals that only need to interact with the air to recharge Some electronic devices might ditch batteries altogether and use something similar to kinetic wristwatches which only need to be shaken to generate a charge The final prediction involves recycling the heat generated by computers and data centers Almost half of the power used by data centers is currently spent keeping the computers cool IBM scientists say it would be better to harness that heat to warm houses and offices In IBM s first list of predictions compiled at the end of 2006 researchers said instantaneous speech translation would become the norm That hasn t happened yet While some programs can quickly translate electronic documents and instant messages and other apps can perform limited speech translation there s nothing widely available that acts like the universal translator in Star Trek Second Life The company also predicted that online immersive environments such as Second Life would become more widespread While immersive video games are as popular as ever Second Life s growth has slowed Internet users are flocking instead to the more 2 D environments of Facebook Inc and Twitter Inc Meanwhile a 2007 prediction that mobile phones will act as a wallet ticket broker concierge bank and shopping assistant is coming true thanks to the explosion of smartphone applications Consumers can pay bills through their banking apps buy movie tickets and get instant feedback on potential purchases all with a few taps on their phones The nice thing about the list is that it provokes thought Saffo said If everything came true they wouldn t be doing their job To contact the reporter on this story Ryan Flinn in San Francisco at rflinn bloomberg net To contact the editor responsible for this story Tom Giles at tgiles5 bloomberg net by 2015, your mobile phone will project a 3-d image of anyone who calls and your laptop will be powered by kinetic energy. at least that\u2019s what international business machines corp. sees in its crystal ball."",""url"":""bloomberg news 2010 12 23 ibm predicts holographic calls air breathing batteries by 2015 html""}";0;345;;;;
http://www.popsci.com/technology/article/2012-07/electronic-futuristic-starting-gun-eliminates-advantages-races;8471;"{""title"":""The Fully Electronic Futuristic Starting Gun That Eliminates Advantages in Races the fully electronic, futuristic starting gun that eliminates advantages in races the fully electronic, futuristic starting gun that eliminates advantages in races"",""body"":""And that can be carried on a plane without the hassle too The Omega E Gun Starting Pistol Omega It s easy to take for granted just how insanely close some Olympic races are and how much the minutiae of it all can matter The perfect example is the traditional starting gun Seems easy You pull a trigger and the race starts Boom What people don t consider When a conventional gun goes off the sound travels to the ears of the closest runner a fraction of a second sooner than the others That s just enough to matter and why the latest starting pistol has traded in the mechanical boom for orchestrated electronic noise Omega has been the watch company tasked as the official timekeeper of the Olympic Games since 1932 At the 2010 Vancouver games they debuted their new starting gun which is a far cry from the iconic revolvers associated with early games it s clearly electronic but still more than a button that s pressed to get the show rolling About as far away as you can get probably while still clearly being a starting gun Pull the trigger once and off the Olympians go If it s pressed twice consecutively it signals a false start Working through a speaker system is what eliminates any kind of advantage for athletes It s not a big advantage being close to a gun but the sound of the bullet traveling one meter every three milliseconds could contribute to a win Powder pistols have been connected to a speaker system before but even then runners could react to the sound of the real pistol firing rather than wait for the speaker sounds to reach them This year s setup will have speakers placed equidistant from runners forcing the sound to reach each competitor at exactly the same time It wouldn t be an enormous difference Omega Timing board member Peter H\u00fcrzeler said in an email but when you think about reaction times being measured in tiny fractions of a second placing a speaker behind each lane has eliminated any sort of advantage for any athlete They all hear the start commands and signal at exactly the same moment There s also an ulterior reason for its look In a post September 11th world a gun on its way to a major event is going to raise more than a few TSA eyebrows even if it s a realistic looking fake Rather than deal with that the e gun can be transported while still maintaining the general look of a starting gun But there s still nothing like hearing a starting gun go off at the start of a race more than signaling the runners there s probably some Pavlovian response after more than a century of Olympic games that make people want to hear the real thing not a whiny electronic noise Everyone in the stands at home thankfully will still be getting that The sound is programmable and can be synthesized to sound like almost anything H\u00fcrzeler says but we program it to sound like a pistol it s a way to use the best possible starting technology but to keep a rich tradition alive and that can be carried on a plane without the hassle, too technology,gadgets,london 2012,london olympics,olympics,omega,starting guns,summer olympics,timing,popular science,popsci"",""url"":""popsci technology article 2012 07 electronic futuristic starting gun eliminates advantages races""}";1;5304;;;;
http://www.menshealth.com/health/flu-fighting-fruits?cm_mmc=Facebook-_-MensHealth-_-Content-Health-_-FightFluWithFruit;1164;"{""title"":""Fruits that Fight the Flu fruits that fight the flu | cold & flu | men's health"",""body"":""Apples The most popular source of antioxidants in our diet one apple has an antioxidant effect equivalent to 1 500 mg of vitamin C Apples are loaded with protective flavonoids which may prevent heart disease and cancer Next Papayas With 250 percent of the RDA of vitamin C a papaya can help kick a cold right out of your system The beta carotene and vitamins C and E in papayas reduce inflammation throughout the body lessening the effects of asthma Next Cranberries Cranberries have more antioxidants than other common fruits and veggies One serving has five times the amount in broccoli Cranberries are a natural probiotic enhancing good bacteria levels in the gut and protecting it from foodborne illnesses Next Grapefruit Loaded with vitamin C grapefruit also contains natural compounds called limonoids which can lower cholesterol The red varieties are a potent source of the cancer fighting substance lycopene Next Bananas One of the top food sources of vitamin B6 bananas help reduce fatigue depression stress and insomnia Bananas are high in magnesium which keeps bones strong and potassium which helps prevent heart disease and high blood pressure Next everything you need to know about cold and flu so you don\u2019t get sick this season, at men\u2019s health.com cold, flu, infection, sore throat, sneeze, immunity, germs, allergies, stay healthy, sick, contagious, medicines, cold medicine"",""url"":""menshealth health flu fighting fruits cm mmc Facebook Mens Health Content Health Fight Flu With Fruit""}";1;2663;;;;
What have I done incorrectly here ?
1) A better way
import pandas as pd
seperator = ";"
df = pd.read_csv("FinalCSVFin.csv", sep=seperator)
2) Your code
You define a function to Read a file using genfromtxt method in numpy, and then use pandas to read you file. I suggest the latter, just use read_csv method in pandas (as was described in 1).
3) Suggestions
Here are the points you can change to get your code working.
You implement a function to read data using np.genfromtxt. The problems are inconsistency in delimiter and also the lack of dtype in genfromtxt. I edit your function as follows:
loadData = lambda f, s: np.genfromtxt(open(f,'r'), dtype=None, delimiter=s)
This gives you a list of tuples. If your file (i.e. FinalCSVFin.csv) uses ";" as delimiter, call this function as follows:
valus = loadData("test.txt", ";")
Related
I Have a csv file with two columns A for brand's names Column B with descriptions
I want to capitalize the brands names in the descriptions by checking if the name of the brand from column A is existing if yes should be capitalized if not move to the next row and so one
any solution for that, I got stack on that here is a sample from the data set
column A
& Other Stories
#HomeOffice
1-800-FLOWERS.COM, INC.
10 Corso Como
100% CAPRI
ITALIA SRL
Column B
They believe in sharing stories. their concept is built around
inviting ctomers to be involved in the creative process behind the
brand. They share everything from the sketch of a shoe to the behind
the scenes of a photo shoot, and views from their ateliers in paris,
stockholm and los angeles. Words such as personal, diverse and
uncomplicated are present in everything they do. They aim to create
collections for all fashion loving women. They want to encourage
personal style with their wide range of products and make everyone
feel welcome. By keeping things uncomplicated and flexible, it’s easy
for them to adapt to new visions and different collections as fashion
always changes. That’s the beauty of it! their Collections are
designed in their three ateliers: paris, stockholm and los angeles.
They are each fantastic yet very different cities. They love the
contrast between the passionate parisian atmosphere, the minimalist,
pragmatic stockholm feel, and the laidback los angeles vibe, and
especially what happens when they all come together. Each person
working with & other stories is an essential part of their group of
creatives and valued individual within the company. They believe in
being spontaneo, personal and flexible, which makes it easy to
collaborate within all parts of their brand and enables growth, for
you and . Currently, & other stories has over 1, 500 employees and
continues to expand, opening more stores around the world.
#Homeoffice Creates a unique, original workplace with a long service life. Stainable sitting sta desks, ergonomic seats and high quality
accessories make your home workplace unique and ergonomic. Pure dutch
design. Go to http: //www. Hashtaghomeoffice. Nl for more information
and inspiration!
#Homeoffice Creates a unique, original workplace with a long service life. Stainable sitting sta desks, ergonomic seats and high quality
accessories make your home workplace unique and ergonomic. Pure dutch
design. Go to http: //www.hashtaghomeoffice. Nl for more information
and inspiration!
Founded in 1991, 10 corso como is recognized as the first concept
destination, blending culture with trends, promoting a close link
between fashion and design. Known as the first «concept store», it
turned the retail concept in a hub for lifestyle and fashion. Today,
30 years later, 10 corso como, with the new presidency and
entrepreneurship of tiziana fati, together with the artistic direction
of carla sozzani, continues the same integrity and aesthetic identity
that has made 10 corso como a symbol of milan, of creativity and made
in italy. For further information about 10 corso como visit www.
10corsocomo. Com connect with 10 corso como on instagram: #10corsocomo
The 100% capri luxury brand was born in 2000 from the idea of toni
aiello who, focing everything on quality, on rich history and on the
charm of made in italy, it is aimed at a target of ctomers who love
lifestyle and the good life, who spend the summer in capri and winter
in saint moritz, also making incursion to the caribbean. People who
like to spend, but who ask first of all. The foc straight to the
linen, why did you want an inseparable combination with 100% capri, a
little? How To do the red luxury car and the ferrari brand. Today
thanks to new technologies the tailoring is able to offer fifteen
different qualities of material, from waterproof linen at lino's garza
and offer collections for men, women, children, but also for the home.
Aiello "wears" even boats and planes. All by invoiced by tens of
millions of euros and an international presence all over the world.
From capri to the fascinating hotel de rsie in rome, from st.
Barthelemy (elegant and refined island of the french antilles) to bal
harbour in florida (the most luxurio mall in the united states), from
sicily (inside the prestigio vegetable golf) to cape town. Openings
are also scheduled for abu dhabi and hong kong.
Thanks
I have a text file which contains the information about Title, Author, Abstract, DOI etc. I want to extract only the abstract and store it in a dataframe. I tried using below code, but I'm getting Author information and DOI, I only want the middle paragraph between Author information: and DOI:. How do I get that specific paragraph and store it in a dataframe
extracted_lines=[]
extract = False
for line in open("abstract.txt"):
if extract == False and "Author information:" in line.strip():
extract = True
if extract:
extracted_lines.append(line)
if "DOI:" in line.strip():
extract = False
print("".join(extracted_lines))
**Output**
Author information:
(1)Carol Davila University of Medicine and Pharmacy, 37, Dionisie Lupu St,
Bucharest, Romania 020021.
(2)National Institute of Public Health, 1-3 Doctor Leonte Anastasievici St,
Bucharest, Romania 050463.
Dark chocolate is not the most popular chocolate; the higher concentration in
antioxidants pays tribute to the increment in bitterness. The caloric density of
dark chocolate is potentially lower but has a large variability according to
recipes and ingredients. Nevertheless, in the last decade, the interest in dark
chocolate as a potential functional food has constantly increased. In this
review, we present the nutritional composition, factors influencing the
bioavailability, and health outcomes of dark chocolate intake. We have extracted
pro- and counter-arguments to illustrate these effects from both experimental
and clinical studies in an attempt to solve the dilemma. The antioxidative and
anti-inflammatory abilities, the cardiovascular and metabolic effects, and
influences on central neural functions were selected to substantiate the main
positive consequences. Beside the caloric density, we have included reports
placing responsibility on chocolate as a migraine trigger or as an inducer of
the gastroesophagial reflux in the negative effects section. Despite an
extensive literature review, there are not large enough studies specifically
dedicated to dark chocolate that took into consideration possible confounders on
the health-related effects. Therefore, a definite answer on our initial question
is, currently, not available.
DOI: 10.5740/jaoacint.19-0132
Author information:
(1)School of Food Science and Nutrition, Faculty of Maths and Physical Sciences,
University of Leeds, Leeds LS2 9JT, UK.
(2)School of Food Science and Nutrition, Faculty of Maths and Physical Sciences,
University of Leeds, Leeds LS2 9JT, UK. Electronic address:
g.williamson#leeds.ac.uk.
Dark chocolate contains many biologically active components, such as catechins,
procyanidins and theobromine from cocoa, together with added sucrose and lipids.
All of these can directly or indirectly affect the cardiovascular system by
multiple mechanisms. Intervention studies on healthy and
metabolically-dysfunctional volunteers have suggested that cocoa improves blood
pressure, platelet aggregation and endothelial function. The effect of chocolate
is more convoluted since the sucrose and lipid may transiently and negatively
impact on endothelial function, partly through insulin signalling and nitric
oxide bioavailability. However, few studies have attempted to dissect out the
role of the individual components and have not explored their possible
interactions. For intervention studies, the situation is complex since suitable
placebos are often not available, and some benefits may only be observed in
individuals showing mild metabolic dysfunction. For chocolate, the effects of
some of the components, such as sugar and epicatechin on FMD, may oppose each
other, or alternatively in some cases may act together, such as theobromine and
epicatechin. Although clearly cocoa provides some cardiovascular benefits
according to many human intervention studies, the exact components, their
interactions and molecular mechanisms are still under debate.
Copyright © 2015 Elsevier Inc. All rights reserved.
DOI: 10.1016/j.vph.2015.05.011
Expected Output
Index Abstract
0 Dark chocolate is not the most popular chocola...
1 Dark chocolate contains many biologically acti...
You can try:
retrieving the whole content of the file as a string
splitting on 'Author information:\n', to retrieve infos about every single paper
getting the index 1 of your papers, to retrieve the abstracts
Here's the code:
with open("abstract.txt") as f:
contents = f.read()
papers = [p for p in contents.split('Author information:\n')]
abstracts = [p.split("\n\n")[1] for p in papers[1:]
Does it work for you?
I am trying to convert a input sentence Review into a CountVectorizer. I am struggling to handle the sentences that are passed through. How do I deal with the sentences and add vectors to these? Any assistance will be highly appreciated.
Input Data:
Sentiment Review
Neg The new Ford Focus came highly recommended to me when I was looking to buy my first new car I researched its history and found that it received great reviews for comfort and safety during its European release Test driving the car I found it to be comfortable well equipped and stylish I have now driven the car for for 6 months and have put only 5000 miles on it While I have been happy with the overall performance of the car I have been sorely disappointed with the workmanship involved Realizing that new models are notorious for having manufacturing bugs I felt somewhat reassured that these would have been worked out from 1998 1999 during the first European release I was wrong My car has been in the repair shop a total of five times for manufacturers defects including a flooded passenger compartment repaired twice to date faulty master clutch cylinder misaligned striker plate on seat back latch broken break switch and cruise control While I really love my car I would hesitate to recommend it to any but my worst enemies Time will tell if the problems my Focus has had are unique or are related to intrinsic design flaws
Neg We bought the Focus ZTS sedan because my wife needed an economical car to haul the grandkids around with We traded in a 94 Explorer with a 5 speed just before the Firestone tire fiasco became public My wife loves driving the car Although it is a bit small for me 6 1 290lbs it is OK The car handles great and with the Zetec engine it has adequate performance although I wouldnt want any less go than its got Now for the problems the main one of which is because I do my own oil changes A particular sore point for me with most cars is that the manufacturers dont make it easy to change the oil and filter without creating a mess This new Focus is particularly bad First the owners manual indicates a Motocraft FL2005 filter The car had an FL801 on it which some ham fisted factory idiot had torqued to about a million foot pounds I had to use some very large pliers and turn the filter almost 3 4 turn before it was loose enough to move by hand Poor quality control The filter happens to be mounted in a horizontal position and is almost flush with the side of the engine When I finally got it loose oil ran down the side of the engine onto the drive axle onto the frame down my arm and all over the driveway Very bad design On other cars I have been able to use a cut off soda bottle placed over the filter to catch the drips On the Focus it wont work The hood on this car is aluminum It bends very easy mine already has a dent in it and I didnt have an accident A minor problem is the power windows They wont operate with the key in the accessory position Tilt wheel also difficult to operate Bottom line only 3 000 miles on this car but its going to get traded off as soon as possible for a vehicle with a little more substance and which is easier to maintain ive owned 9 Fords since 1986 still have 3 If all the newer Fords are made this way the Focus may be the last Ford product I buy
Neg Recently I had the need to rent a car I picked the Ford Focus I was amazed with this car I liked it better than my own more expensive 1999 Toyota Corolla LE The steering wheel is not only height adjustable but also telescopes something you do not normally find on such a reasonably priced car The drivers seat also adjusted forward and back and in height nice feature for someone tall like myself The front seats were roomy and comfortable and the back seat had I think the most leg room I HAVE EVER SEEN in a compact car The stereo sounded good considering it was stock and the face of the radio has an upward tilt to it so that it is driver friendly All the bells and whistles were located within easy reach and the air worked well In addition to having a roomy trunk there are 60 40 split rear seats Child safety seat anchors and shoulder harness seat belts for 5 passengers I rented the 4 door sedan but there are 3 body styles The 4 door sedan 4 door wagon and a sporty little hatch back I have read the safety ratings for the hatch back and from what I recall it got 5 stars This car is definately on my list of cars to consider purchasing in the near future you should take a look at it too
Pos Cruising In My Big T I have had my 91 Thunderbird for 4 years now bought it way back in my freshman year and it has served me well throughout college I am a horrible Northern driver and brutal on my vehicles but this piece of Ford craftsmanship refuses to bail out on me Its a rough and tumble vehicle that remains an incredible deal for the price especially when bought used from a reputable dealer The Advantages 1 Seat Space These are big seats people with the kind of legroom that only those pretentious you know whats in first class usually get their hands on And that spaciousness isnt just about spoiling the people up front either it extends to the back seat as well which means that everyone feels just a little bit more comfortable and relaxed when you get to wherever you re going And not only are the seats big but the generous amount of padding in each makes for an especially comfortable ride 2 Appearance ive gt to admit it to you I just love the look of the Thunderbird though it is an acquired taste to be sure I can best describe the style as Italian sleek in a chunky way and available in colors like burgundy that make it look like a cross between a hit mobile and a hearse 3 Smooth Ride Riding in my Thunderbird has always seemed quite smooth to me especially when you consider how low to the ground it is Why so low That kind of positioning allows the Thunderbird to provide the rider with great control as your feel for the road is significantly enhanced In the same arena as the ride is the ease of use of the console which for me equals smoothness and ease The Thunderbirds radio and air console is incredibly well designed with everything within reach and intuitively organized Seem trivial to you Try changing the station at 75 miles an hour and see how important knob placement is 4 Trunk This is a important feature for me as I seem to move every 3 6 months The trunk on the Thunderbird is big enough for all of your luggage not to mention the corpse of Vinnie The Chin from a rival family My Defense I have read another review of this vehicle that criticizes the brake quality and I have to vehemently disagree with it I ride my brakes hard and I have never had a lockup or other incident The brakes do tend to squeek a bit but the noise is no indication of a performance issue The Final Verdict The bottom line is that the Thunderbird is a comfortable and well designed car at a reasonable price As long as you like burgundy vehicles and live in an area thats at least 30 Italian the Thunderbird is a great option
Pos I arrived in the states from Australia at the end of March 1999 to stay there for a year and come home at the end of March 2000 I stayed with friends in South Carolina who is a Ford man as I have always owned GM or Chevs they lent me a 1979 red corvette until I bought myself a car so after 3 months I did buy a 1985 Z28 Camaro 350 to fix up and use for the 9 months after looking at it I thought this was a bad idea so looked in the local paper and found a red 1991 V8 Thunderbird with 114 000 miles on it for 3000 After taking it for a test drive offered the lady 2800 and drove it home it had a slight water leak from the water pump so while replacing it I installed a set of under drive pulleys which I could notice the power increase the first time I drove it put a K amp N air cleaner in as well I had a friend come over from Australia so we drove from Greenville SC across to Sequin TX did about 3000 miles in that trip we took the long way and had no trouble at all and got 27 MPG sitting on 80 MPH had a radar detector it has a highway ratio in it 2 75 My brother came over from Australia so we went from Greenville SC down to Daytona Beach and back then drove across America to California which we did about 4600 miles trouble free When we left Williams AZ the car was buried under snow as we had a cold snap and snow dig the snow away and turn the key starting the engine at once and never missing a beat The car came with the premium sound system but the radio cassette was playing up so replaced it with a Pioneer radio CD I went to the wreckers and bought an electric motor seat assembly for the right hand side so when converting to RHD will have an electric adjustment Also bought a sports instrument cluster and centre handbrake assy out of a super coupe These cars were never made for export or for Right Hand Drive so have to get all the parts needed now for conversion I did 18 000 miles in 9 months without the car stopping or letting me down I gave the car 4 oil changes added fuel octane booster with every tank of gas it has the factory 15 alloy wheels with Michelin tyres I found the car very easy to drive and steer but did experience brake shudder which appears to be a common problem due to thin brake rotors I added a rear spoiler and had the windows tinted which makes the car look sporty as in Australia the only 2 door cars are mainly Jap imports so in the end I shipped the car back to Australia where I have to convert it over to Right Hand Drive for our road rules this cars owes me 10 000 Australia 5200 US landed back at my house in Australia which when converted to RHD they sell from 35 000 to 40 000 18 000 to 21 000 US BEST CAR I HAVE EVER OWNED
Pos This review is about Ford Mustang 3 8L Coupe with stick shift I test drove when I considered buying it I say considered because I did not buy it and here is why Test Drive The dealer talked too much during the test drive They always try to do that to distract you but I noticed the following things Styling You can argue but I think it could be better The car looks bulky the C pillars are thick which increases blind spots I was afraid to run over somebody while backing up the standard wheels look crude The previous Mustang looked more balanced Engine The 3 8L 193 hp engine does not seem all that powerful even with stick We went on the freeway onramp and I was disappointed Strange considering the 220 lb ft of torque rating at as low as 2800 rpm European and Japanese manufacturers manage to extract more than 200 hp out of 3 0 liter engines Note the A C was on during the test drive and was very efficient It might eat some power but not that much Transmission The shifter has quite short travel which is good but the clutch does not provide any feedback you cannot feel it engage by the pedal pressure or the dealer talked too much The clutch also engaged very high in the pedal travel I drove some Eastern European cars for several years and never had complaints like this one Or maybe im getting old and grumpy Suspension The suspension is not only stiff but creates a lot of unnecessary up and down motions The car uses live axle in the rear so I didnt expect much anyway Standard Equipment The list of standard equipment looks good It includes power windows mirrors locks and remote keyless entry alloy ugly wheels AM FM CD cassette player A C dual vanity mirrors etc Interior Interior materials fit and finish looks cheap I did not expect walnut for 16K but Ford could have done better As I said the C pillars are wide in coupe and the interior room is smaller than Id like The steering wheel tilts but does not telescope which might be a problem for the tall people Insurance and Safety Insurance rates are high especially if you are a male younger than 25 The crash test results are not encouraging either the overall rating is Acceptable with Poor death rate and Marginal injury rate Fuel Economy I didnt get a chance to see the actual fuel consumption myself but on paper its 19 MPG city 29 MPG highway Not impressive for the car of this size with manual transmission Warranty and Reliability Consumer Reports magazine says that Mustang has poor reliability Ford provides 36 000 mile 3 year warranty and 5 year corrosion warranty Majority of other manufacturers offers 60 000 mile 5 year powertrain warranty 100 000 mile 10 year warranty for Hyundai Kia The last three safety fuel economy and reliability also depend on the way you drive Pricing The price was good in theory I know that you can get the car for less than 16K at CarsDirect com for example but the particular dealership I went to wanted more than 17K and did not want to negotiate the price at all Besides they were very pushy and rude Needles to say they did not earn my business they didnt even try The dealer was constantly asking what monthly payment I can afford Well I can afford the payment I need to get better car I walked after which they called me several times asking how they can make me buy the car today I was unable to produce any kind of positive reply on this one I In car buying a lot depends on personal taste If you like Mustangs styling and features and decide to buy it it is a good deal providing you with electric everything remote keyless entry radio CD cassette V6 engine and alloy wheels for less than 16 If you want refinement fit and finish safety and reliability get ready to pay more for something else I
Code attempt:
from sklearn.feature_extraction.text import CountVectorizer
#instantiate the class
cv = CountVectorizer()
#list of sentences
for i in range(len(df['clean_Review'])):
text=df.loc[i, "clean_Review"]
#tokenize and build vocab
cv.fit(text)
print(cv.vocabulary_)
#transform the text
vector = cv.transform(text)
print(vector.toarray())
#df.loc[i,"porter"]=test
i=i+1
You don't need the looping. From the documentation:
from sklearn.feature_extraction.text import CountVectorizer
#instantiate the class
cv = CountVectorizer()
#vector is a sparse matrix storing individual words as "bag of words" model
vector = cv.fit_transform(df["clean_Review"].copy())
I assume that you have performed corpus cleaning step (lowercase, ascii encoding, stopword removal, etc) before using CountVectorizer to convert your model to bag of words, therefore I have kept the arguments of CountVectorizer() empty.
Example:
from sklearn.feature_extraction.text import CountVectorizer
import pandas as pd
#sample text corpus
corpus = pd.Series(["aa bb cc dd ee","bb cc dd ee","cc dd ee","dd ee","ee","ee ff"])
#instantiate the class
cv = CountVectorizer()
vector = cv.fit_transform(corpus)
print(corpus)
0 aa bb cc dd ee
1 bb cc dd ee
2 cc dd ee
3 dd ee
4 ee
5 ee ff
dtype: object
print(vector.toarray())
array([[1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 0],
[0, 0, 1, 1, 1, 0],
[0, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 1, 1]])
I am trying to use Big Bird Pegasus to summarize various long texts. The output is repeating the same concept in each sentence.
Here is my code using a news article I copied from NPR. The text is longer than the 4096 token limit, so it takes the first few thousand words from my input.
from transformers import BigBirdPegasusForConditionalGeneration, AutoTokenizer, AutoModelForSeq2SeqLM
model = BigBirdPegasusForConditionalGeneration.from_pretrained("google/bigbird-pegasus-large-arxiv")
tokenizer = AutoTokenizer.from_pretrained("google/bigbird-pegasus-large-arxiv")
src_text = '''
On a sleepy cul-de-sac amid the bucolic vineyards and grassy hills of California's Sonoma Valley, a $4 million house has become the epicenter of a summer-long spat between angry neighbors and a new venture capital-backed startup buying up homes around the nation. The company is called Pacaso. It says it's the fastest company in American history to achieve the "unicorn" status of a billion-dollar valuation — but its quarrels in wine country, one of the first regions where it's begun operations, foreshadow business troubles ahead.
Brad Day and his wife, Holly Kulak, were first introduced to Pacaso in May after a romantic sunset dinner in their yard. "And we just saw this drone, coming up and over our backyard," Day says. "And we're like, what is that?"
Pacaso denies directing or paying a drone operator to film the neighborhood. But its website does have drone photos of the house in question, located at 1405 Old Winery Court. It says it bought the photos after the fact.
Nonetheless, after the drone incident, Day and Kulak got suspicious about what was going on in their neighborhood. About a week later, their neighbors told them they were moving and selling their house to a limited liability corporation, or LLC. But they were super vague about it.
Day and Kulak began speaking with other residents on their cul-de-sac. One of them, Nancy Gardner, had learned from a friend in nearby Napa Valley about a new company called Pacaso that was buying houses in the area. The company was co-founded by a Napa resident, and it converts houses into LLCs. Pacaso then sells shares of these corporate houses to multiple investors. Gardner Googled Pacaso, and, sure enough, the house on their cul-de-sac was on its website. The company had named the house "Chardonnay" and was now selling investors the chance to buy a one-eighth share of it for $606,000.
Pacaso was founded in October 2020 by Austin Allison and Spencer Rascoff, two former executives at Zillow. The company is based in San Francisco, and as is typical of tech startups in the Silicon Valley area, its founders tell a lofty story about their business that's about more than just making money. The company says the motivation for the venture began when Allison and his wife, both based in Napa, bought a second home in Lake Tahoe. The night after they closed on the house, Allison says in a promotional video, he and his wife sat around a fire "thinking how appreciative we were to be second homeowners. And, from that moment, I've always been inspired about making the dream of second home ownership possible for more people."
To make second home ownership possible for more people — and, of course, make money — Pacaso uses a "fractional home ownership" model. They buy a house, lightly refurbish it, furnish it and then create an LLC for it. They then divvy up ownership of this corporatized house into eight fractions and sell those shares on their website.
If you buy a share in a house, you're able to stay in it 44 nights per year in increments that can't exceed 14 consecutive days per visit. You can also "gift" these stays to friends or family. Pacaso offers an app to handle the logistics of booking stays. It oversees management, maintenance and cleaning of the property. In exchange for all this, it charges 12% of the home's purchase price upfront and monthly fees going forward. If you buy a share in a house, you have to hold on to it for a year. After that, you can sell it and profit from any appreciation in the home's value (or be on the hook for any depreciation).
When Day, Kulak and their neighbors learned about Pacaso's business model, they were appalled. They saw the venture capital-backed company as invading their community and converting their neighbor's house into a revolving carousel of vacationers. They imagined endless parties, noise and cars overflowing their cul-de-sac. They worried those staying at "Chardonnay" would drive too fast and fail to heed local concerns about wildfires and droughts. But, most of all, they feared the Pacaso house and more like it would destroy their sense of community and turn their neighborhood into an "adult Disneyland."
The county, Day says, had designated their neighborhood an "exclusion zone," which bans Airbnb-style, short-term rentals to preserve the "residential character" of communities. But Pacaso argues that its clients are not short-term renters. They are co-owners of an LLC. This also means they don't have to pay the typical taxes on short-term rentals. Likewise, in the nearby town of St. Helena, Pacaso was trying to circumnavigate a city ban against timeshares with the same argument. Day says he and his neighbors saw Pacaso's newfangled business model as nothing more than a "glorified timeshare" with a legal strategy aimed at "skirting regulations that are designed to keep communities intact."
The cul-de-sac sprang into action. It formed an organization called Sonomans Together Opposing Pacaso, which, not coincidentally, has the acronym STOP. It contacted the county Board of Supervisors. It created an anti-Pacaso website and circulated an online petition. It flooded the local newspaper with op-eds and letters to the editor. It lobbied local real estate agents not to work with Pacaso. "It feels like we're waging a war by land, air and sea," Day says.
Protest signs festoon the neighborhood's lawns, fences and cars. They say things such as "Stop Pacaso" and "Not here, Pacaso!" Day's favorite sign reads, "The Pacaso house is the big one on the right with no soul."
The signs, of course, make the prospect of buying a share in the Pacaso house awkward, to say the least. Alfred Miller, however, bought a share in "Chardonnay" before ever seeing it in person. Miller is a risk management consultant based in Los Angeles. He believes in Pacaso's business model. And he likes wine and Sonoma's climate. As he researched "Chardonnay" online, he liked the modern architecture and pool, and he decided he'd buy a one-eighth share of the house. It wasn't until a couple weeks after he made the purchase that he first drove up to Sonoma and witnessed the spectacle around his new investment.
"So, imagine me as a new owner driving up, and I get to the corner of Old Winery Court," Miller says. "There's a full-on, professionally printed sign that says 'No Pacaso.' '' Miller then turned right onto Old Winery Court "and the more I drive into the neighborhood, the more signs I see. Brad Day has three vehicles in front of his house, and each vehicle has an anti-Pacaso sign on it. I pull into the driveway — there are two signs on each side of the property. I mean, it was not what I would call very welcoming."
As it did on Old Winery Court, controversy erupted in Napa after the company bought a home worth $1.13 million. That's about 35% higher than Napa's median home price. Pacaso insists it only buys luxury and ultra-luxury houses, and it therefore isn't competing with local middle-class families in the housing market. But this home, located two blocks from a high school, didn't quite fit its talking points. Some Napans were pissed. Pacaso says the house was the victim of trespassing and "illegal signage." Pacaso even claims it had to file a police report after a local wrote to the company and said, "I will burn down any home you buy in Napa. This is no joke."
Pacaso's CEO, who lives in Napa, saw firsthand how angry Napans were, and the company responded. In June, Pacaso agreed to sell the Napa home in a traditional manner "to a whole home buyer" rather than convert it into a corporation and sell it to multiple people. The company also pledged to beef up its "Owner Code Of Conduct" to include "decibel limits on all home sound systems," create a "local liaison" dedicated to assisting neighbors, not buy any homes in the area for under $2 million, and, for each house sold in Napa and Sonoma counties, donate $20,000 to a local nonprofit dedicated to affordable housing.
But while it has been trying to placate local communities with business reforms, Pacaso has waged a court battle with the town of St. Helena over whether its homes should be classified as timeshares. Pacaso is dead set against that classification. One reason might be that timeshares have a bad rap: While they're a popular way to go on vacations, their costs and associated fees tend to make them money losers rather than a profitable investment.
Potentially even more damaging to Pacaso's ambitions, however: Timeshares are banned in many vacation communities around the nation. Hence, Pacaso has strong reasons to insist its homes are not timeshares.
"Unlike a timeshare model, the co-owners that Pacaso serves collectively own real estate, not time," says Ellen Haberle, director of community and government relations for Pacaso.
St. Helena disagrees, declaring Pacaso homes are not allowed in the town because of a city ordinance against timesharing. "Simply calling them co-ownership arrangements does not change that fact," City Attorney Ethan Walsh said. In response to the ban, Pacaso sued the town in federal court. The lawsuit is still pending.
Pacaso says it plans to expand across North America and Europe. Given the company's billion-dollar valuation, investors seem to believe that many people will be attracted to its model of fractional second home ownership. But local residents will likely continue to fight the unicorn stampeding into their towns.
'''
device = 'cuda' if torch.cuda.is_available() else 'cpu'
batch = tokenizer(src_text, truncation=True, padding='longest', return_tensors="pt").to(device)
translated = model.generate(**batch)
tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)
Here is the output. It doesn't mention anything but the topic of fractional ownership. I repeated for another input text and got similar results - each sentence was a slight variation of each other.
tgt_text
['the notion of a fractional ownership in a real property was introduced in the 19th century.<n> fractional ownership in a real property was defined to be the fraction of the value of the property minus the cost of its construction.<n> the fractional ownership of a real property was defined to be the fraction of the value of the property minus the cost of its construction.<n> the fractional ownership of a home is defined to be the fraction of the value of the home minus the cost of its construction. <n> the notion of a fractional ownership in a real property was introduced in the 19th century.<n> the fractional ownership of a home is the fraction of the value of the home minus the cost of its construction.<n> the fractional ownership of a real property was defined to be the fraction of the value of the home minus the cost of its construction.<n> the fractional ownership of a home is the fraction of the value of the home minus the cost of its construction.<n> the fractional ownership of a real property was defined to be the fraction of the value of the home minus the cost of its construction.<n> the fractional ownership of a home was defined to be the fraction of the value of the home minus the cost of its construction.<n> the']
Have you tried to use no_repeat_ngram_size to generate the summarization? E.g.,
translated = model.generate(**batch, no_repeat_ngram_size=3)
This will generate following text:
the notion of a fractional ownership in a real property was introduced in the 19th century.<n> fractional ownership refers to a property that is more than one half of the value of the property. in recent years<n>, fractional ownership has been used to describe a variety of real
estate phenomena, such as the construction of bridges and tunnels, the development of canals and other drainages, as well as the movement of people and goods. here<n> we consider the fractional ownership
of a home, which can be thought of as the difference between the values of the two halves of the home.
I am parsing some news data with spaCy and am noticing a consistent failure regarding sentence segmentation where there is a quote. Has anyone else solved this issue?
Here is a reproducible example - note sentence 4 in the output below. spaCy fails to split at the start of the quote, and this is consistent through other news articles I'm working with.
Thanks a lot.
Example:
Raw data:
u'body': u'\n LONDON Nov 4 Britons hurt by lower incomes and rising food prices after the financial crisis have cut back on fruit and vegetables and turned instead to fatty, sugary, processed food, an academic study showed on Monday.Britain has seen food prices rise much more sharply than most other developed economies between 2005 and 2012, while wage growth has been low and unemployment has risen.The net effect has been that Britons are spending 8.5 percent less in real terms on food purchased at home than before the recession - with the trend even greater for pensioners and families with young children.The research is likely to be politically sensitive at a time when Britain\'s Conservative-led government is under pressure from the opposition Labour Party, over declining standards of living and sharply rising demand at food banks which hand out free food to the poorest Britons. People have economised by buying less food, measured in number of calories, but also on its quality, picking products that are less nutritious and higher in saturated fat and sugar."Various measures of nutritional quality declined over this period, with bigger decreases for pensioner households and households with young children," said the Institute for Fiscal Studies, an economics research body.OBESITY Families with children were prone to switching to more sugary food, while pensioners favoured food high in saturated fat, the study showed. Both groups often have lower incomes.While the economy is starting to show signs of growth after suffering the biggest hit to economic growth since records began during the 2008-09 recession, households\' disposable incomes are no higher than a decade ago. However, the IFS said a lower-quality diet was not an inevitable consequence of having less money, and that some households had been able to eat as healthily as before while spending less. More research was needed to see why this was not the case for other households, the researchers added.The study looked at data on more than 15,000 households\' shopping habits collected by market research company Kantar Worldpanel between 2005 and 2012.The figures do not include meals purchased or provided away from home, for example in restaurants or at schools, which in England provide free lunches for poorer pupils.The study was released alongside a piece of longer-term research from the IFS, which showed the English now consume 15-30 percent fewer calories than in 1980, despite higher obesity rates probably due to less physical activity.This contrasts with the United States, where calorie consumption has risen as well as obesity. The IFS said it was were researching further into trends in Britons\' physical activity over the period.',
Code to split:
from __future__ import unicode_literals
import spacy
nlp = spacy.load('en')
doc1 = nlp(article_to_json['body'].decode('utf-8'), parse=True)
for number, sent in enumerate(doc1.sents):
print number, sent, "\n"
Output:
0 LONDON Nov 4 Britons hurt by lower incomes and rising food
prices after the financial crisis have cut back on fruit and
vegetables and turned instead to fatty, sugary, processed food, an
academic study showed on Monday.
1 Britain has seen food prices rise much more sharply than most other
developed economies between 2005 and 2012, while wage growth has been
low and unemployment has risen.
2 The net effect has been that Britons are spending 8.5 percent less
in real terms on food purchased at home than before the recession -
with the trend even greater for pensioners and families with young
children.
3 The research is likely to be politically sensitive at a time when
Britain's Conservative-led government is under pressure from the
opposition Labour Party, over declining standards of living and
sharply rising demand at food banks which hand out free food to the
poorest Britons.
4 People have economised by buying less food, measured in number of calories, but also on its quality, picking products that are less
nutritious and higher in saturated fat and sugar."Various measures of
nutritional quality declined over this period, with bigger decreases
for pensioner households and households with young children," said the
Institute for Fiscal Studies, an economics research body.
5 OBESITY Families with children
were prone to switching to more sugary food, while pensioners favoured
food high in saturated fat, the study showed.
6 Both groups often have lower incomes.
7 While the economy is starting to show signs of growth after
suffering the biggest hit to economic growth since records began
during the 2008-09 recession, households' disposable incomes are no
higher than a decade ago.
8 However, the IFS said a lower-quality diet was not an inevitable
consequence of having less money, and that some households had been
able to eat as healthily as before while spending less.
9 More research was needed to see why this was not the case for other
households, the researchers added.
10 The study looked at data on more than 15,000 households' shopping
habits collected by market research company Kantar Worldpanel between
2005 and 2012.The figures do not include meals purchased or provided
away from home, for example in restaurants or at schools, which in
England provide free lunches for poorer pupils.
11 The study was released alongside a piece of longer-term research
from the IFS, which showed the English now consume 15-30 percent fewer
calories than in 1980, despite higher obesity rates probably due to
less physical activity.
12 This contrasts with the United States, where calorie consumption
has risen as well as obesity.
13 The IFS said it was were researching further into trends in
Britons' physical activity over the period.
I googled the original news article to try to figure out why your data looks like it does (missing whitespace between sentences where I wouldn't expect it in a formal news article), and it looks like the original problem is that no whitespace is inserted between HTML paragraphs. If you can fix that problem with how the article is extracted from the original HTML (insert whitespace when you run into <p> or </p>), you won't have this problem with spacy or other tools.
The models available in standard tools will often be trained on news data and it's reasonable to expect them to work well for data like this, but they expect whitespace between sentences. Unless you retrain the models with data including missing whitespace between sentences (or preprocess your data as suggested in a comment), you're going have these kinds of problems.