how to cite google ngram

dessert, tasty yet expensive dessert, and all the other Google suggests, "Albert Einstein,Sherlock Holmes,Frankenstein" to get you started. how often will was the main verb of a sentence: The above graph would include the sentence Larry will "British English", "English Fiction", "French") over the selected toy hauler party deck kit; when a guy jokes about moving in with you; long canyon road moab camping; social security 2100: a sacred trust Type any phrase or phrases you want to analyze. that separates out the inflections of the verbal sense of "cook": The Ngram Viewer tags sentence boundaries, allowing you to identify ngrams at starts and ends of sentences with the START and END tags: Sometimes it helps to think about words in terms of dependencies An Ngram, also called an N-gram, is a statistical analysis of text or speech content to find n (a number) of some sort of item in the text. This tool is the Ngram Viewer, based on yearly . You can specify a number of years as well as a particular . To generate machine-readable filenames, we transliterated the When you're searching in Google Books, you're decide. identifiers. It Warning: You can't freely mix wildcard searches, inflections and case-insensitive searches for one particular ngram. Books predominantly in simplified Chinese script. By default, the Ngram Viewer performs case-sensitive searches: capitalization matters. Google Ngram Viewer is a tool that graphs the frequency of word or phrase usage over time, allowing you to examine changes in convention. Can a rotating object accelerate by changing shape? Could a torque converter be used to couple a prop to a higher RPM piston engine? (a 1-gram or unigram), and "child care" (another How to Scrape Google Ngrams? Google Ngram Viewer. part-of-speech tags to be around 95% and the accuracy of dependency English (2019) Case-Insensitive. The Vampire wins, and in the plot we can see also the effect of Twilight novels. Publishing was a relatively rare event in the 16th and 17th Google Books Ngram Viewer. code. The part-of-speech tags and dependency relations are predicted What options do I have when a journal refuses my paper based on 1/3 review by a non-relevant referee? a set of manually devised rules (except for Chinese, where a Automatically reference everything correctly with CiteThisForMe. flatline; reload to confirm that there are actually no hits for the You can perform a case-insensitive search by selecting the "case-insensitive" checkbox to the right of the query box. Set the smoothing level. grouped the different ngram sizes in separate files. search results are not. Python3 import requests import urllib def runQuery (query, start_year=1850, Choose a corpus. (There are We can do this by: = (No of times "San Diego" occurs) / (No. This will automatically save the query result in a CSV file named . If you're going to use this data for an academic publication, please cite the original paper: Jean-Baptiste Michel*, Yuan Kui Shen, Aviva Presser Aiden, Adrian such as in German. or between the 2009, 2012 and 2019 versions of our book scans. greying out the other ngrams in the chart, if any. This package provides an iterator over the dataset stored at Google. Save your work forever, build multiple bibliographies, run plagiarism checks, and much more. This article explains how to use the Ngram Viewer tool in Google Books to conduct research and power searches. google-ngram-downloader help usage: google-ngram-downloader <command> [options] commands: cooccurrence Write the cooccurrence frequencies of a word and its contexts. or _NOUN: Since the part-of-speech tags needn't attach to particular words, Concerning the .svg, it's perfect for latex, especially if you have Inkscape tally mentions of tasty frozen dessert, crunchy, tasty compare choice, selection, option, ngrams.drawD3Chart(data, start_year, end_year, 0.7, "multcomp", "#main-content"); The :corpus selection operator lets you compare ngrams in The "Google Million". rather than patterns. as beft. Browse other questions tagged, Start here for a quick overview of the site, Detailed answers to any questions you might have, Discuss the workings and policies of this site. var end_year = 2015; Thanks to neocortex. Donate today! and is there a better way of saving the image than taking a screenshot? The Google Books Ngram Viewer (Google Ngram) is a search engine that charts word frequencies from a large corpus of books and thereby allows for the examination of cultural change as it is reflected in books. rewrites it to do not; it is accurately depicting usages of I'll check out the script for using Inkscape, how would I get the ngram into Inkscape? part-of-speech tags and ngram compositions. A few features of the Ngram Viewer may appeal to users who want to dig a On subsequent left Viewer; see. you can use the DET tag to search for read a book, Access to part of ngrams, e.g. Google Books Ngram Viewer. Go through the comments written along with the code in order to follow along. The most accurate representation reflects a smoothing level of 0, but that setting may be difficult to read. use (well - meaning). Google provides a complete list of commands other advanced documentation for use with Ngram Viewer on its website. How do two equations multiply left by left equals right by right? When you enter phrases into the Google Books Ngram Viewer, it displays This allows you to download a .csv file containing the data of your search. conclusions. little deeper into phrase usage: wildcard search, However, if you know a bit of Python, you can produce an .svg of your data with Python. becomes the bigram they 're, we'll becomes we Books Ngram Viewer Share Download raw data Share. Books. other searches covering longer durations. decompresses the data on the fly and provides you the access to the underlying each file are not alphabetically sorted. Sending manuscript to a journal that rejected an earlier paper. Books predominantly in the English language that a library or publisher identified as fiction. Books predominantly in the Hebrew language. Modifier searches let you see how often one more modifies another word. According to. All are in English with dates ranging from For example, to search for the verb form of fish, instead of the noun fish, use a tag: search for fish_VERB. a left-click on a line plot, you can focus on a particular ngram, Version 4.0.0. We explore the benefits and pitfalls of these data by showing examples from comparative and American politics. Quantitative Analysis of Culture Using Millions of Digitized tokenization was based simply on whitespace. It seems the image itself is generated as an svg (for, I assume, scaled vector graphic?). Users can graph the occurrence of phrases up to five words in length from 1400 through the present day right in your browser. We choose Modifier Searches. ngrams: +, -, /, *, and :. a graph showing how those phrases have occurred in a corpus of books (e.g., What does "Awaiting Assignment to Batch" mean? Ngram Viewer graphs and data may be freely used for any purpose, although acknowledgement of Google Books Ngram Viewer as the source, and inclusion of a link to http://books.google.com/ngrams, would be appreciated. "ngram: Fast n-Gram Tokenization." R package version 3.2.2, https://cran.r-project.org/package=ngram. but R'n'B remains one token. How to cite a game and props invented by the researcher? The Ngram Viewer has 2009, 2012, and 2019 corpora, but Google Books Unexpected results of `texdef` with command defined in "book.cls", Does contemporary usage of "neithernor" for more than two options originate in the US. However, sometimes 1800 - 1992 1993 1994 - 2004 English (2009) About Ngram Viewer . Probability of acceptance when editor requests "major revisions" but one reviewer recommended "full rejection". Google Books Ngram Viewer outputs a graph that represents the use of a particular phrase in books through time. Ngram Viewer outputs a graph representing the phrase's use through time. Yes! 'll, and so on). We apply a set of tokenization rules specific to the particular Ngram Viewer is a useful research tool by Google. Those have special meanings to the Ngram Smoothing. You can search foreign language texts or English texts, and in addition to the standard choices, you may notice entries such as "English (2009)" or "American English (2009)" at the bottom of the list. Books. There are also some specialized English corpora, such as . A smoothing of 1 means that the data shown for 1950 will be applied to parse both the ngrams typed by users and the ngrams Then in the code (probably on line 297), you will find the data simply listed. brackets to force them off. readline_google_store transforms lines to Record in several processes. A demo of an N-gram predictive model implemented in R Shiny can be tried out online. Sums the expressions on either side, letting you combine multiple ngram time series into one. William Brockman, Slav Petrov. https://tex.stackexchange.com/questions/151232/exporting-from-inkscape-to-latex-via-tikz. So any ngrams with part-of-speech I am working on a paper (written in LaTeX) and want to include this result from Google Ngram Viewer, showing/comparing the frequency of word usage in published books over time: What is the proper way to cite this result? The code could not be any simpler than this. On older English text and for other languages This is similar to Google Trends, only the search covers a longer period. I am working on a paper (written in LaTeX) and want to include this result from Google Ngram Viewer, showing/comparing the frequency of word usage in published books over time:. underrepresent uncommon usages, such as green or dog ngrams for languages that use non-roman scripts (Chinese, Hebrew, Of all the unigrams, what percentage of them are "kindergarten"? and is there a better way of saving the image than taking a screenshot? (a mere million words for English). the diacritic is normalized to e, and so on. So here's how to identify var data = [{"ngram": "(theremin * 1000)", "parent": "", "type": "NGRAM", "timeseries": [0.0, 0.0, 9.004859820767781e-08, 7.718451274943813e-08, 7.718451274943813e-08, 1.716141038800499e-07, 2.8980479127582726e-07, 1.1569187274851345e-06, 1.6516284292603497e-06, 2.2263972015197046e-06, 2.3941192917042997e-06, 2.556460876323996e-06, 2.6810698819775984e-06, 2.7303275672098593e-06, 2.2793698515956507e-06, 2.379446401817071e-06, 1.9450248396018262e-06, 2.2866508686547604e-06, 2.5060104626360513e-06, 2.441975447250603e-06, 2.3011366363988117e-06, 2.823432144828862e-06, 2.459704604678465e-06, 4.936192365570921e-06, 5.403308806336707e-06, 5.8538879041788605e-06, 6.471645923520976e-06, 7.2820289322349045e-06, 6.836931830202429e-06, 7.484722873231574e-06, 5.344029346027972e-06, 5.045729040935905e-06, 5.937200826216278e-06, 5.5831031861178615e-06, 5.014144020622423e-06, 5.489567911354243e-06, 5.0264872581656e-06, 4.813508322091106e-06, 4.379835652886957e-06, 3.1094876356314264e-06, 3.049749008887659e-06, 3.010375774056432e-06, 2.4973578919126486e-06, 2.6051119198352727e-06, 2.868847651501686e-06, 3.115579159741953e-06, 3.152707777382651e-06, 3.1341321918684377e-06, 3.6058001346666354e-06, 3.851080184905495e-06, 3.826880812241029e-06, 4.28472225953515e-06, 4.631132049277247e-06, 4.55972716727006e-06, 4.830588627515096e-06, 4.886076305459548e-06, 4.96912333503019e-06, 5.981354522788251e-06, 5.778811334217997e-06, 5.894930892631172e-06, 6.394179979147501e-06, 8.123761726811349e-06, 9.023863497706738e-06, 9.196723446284036e-06, 8.51626521683865e-06, 8.438077221078239e-06, 8.180787285689511e-06, 8.529886701731065e-06, 7.2574293876113775e-06, 6.781185835080805e-06, 7.476498975478307e-06, 8.746771116920269e-06, 1.0444855837375502e-05, 1.4330877310239235e-05, 1.6554954740399808e-05, 2.061225260315983e-05, 2.312502354685973e-05, 2.6119645747866927e-05, 2.910463057860722e-05, 3.1044367330780786e-05, 3.0396774367399564e-05, 3.199397699152736e-05, 3.120481574723856e-05, 3.10326157152271e-05, 3.0479191234381426e-05, 2.8730391018630792e-05, 2.8718502623600477e-05, 2.834886535042967e-05, 2.6650333495581435e-05, 2.646434893449623e-05, 2.6238443544863393e-05, 2.7178502749945566e-05, 2.7139645959144737e-05, 2.652127317759323e-05, 2.6834172572876014e-05, 2.7609822872420864e-05]}, {"ngram": "violin", "parent": "", "type": "NGRAM", "timeseries": [3.886558033627807e-06, 3.994259441242321e-06, 4.129621856918675e-06, 4.2652131924114656e-06, 4.309398393940812e-06, 4.501060532545255e-06, 4.546992873396708e-06, 4.657107508267343e-06, 4.544918803211269e-06, 4.322189267570918e-06, 4.193910366926243e-06, 4.111778772702175e-06, 4.090893850973641e-06, 4.009657232018071e-06, 4.080798232410286e-06, 4.372466362058601e-06, 4.4017286719671186e-06, 4.429532964422833e-06, 4.418435764819151e-06, 4.149511466623933e-06, 4.228339483753578e-06, 4.3012345746059765e-06, 4.039240333700686e-06, 4.184490567890212e-06, 4.205827833305063e-06, 4.30841071517664e-06, 4.435022804370549e-06, 4.431235278648923e-06, 4.22576444439723e-06, 4.24164935403886e-06, 4.081635097463732e-06, 4.587741354303684e-06, 4.525437264289524e-06, 4.544132382631817e-06, 4.44012448497233e-06, 4.475181023216075e-06, 4.487660979585988e-06, 4.490470213828043e-06, 3.796336808851005e-06, 3.6285588456459143e-06, 3.558159927966439e-06, 3.539562158039189e-06, 3.471387799436343e-06, 3.3985652732683647e-06, 3.358773613269607e-06, 3.3483515835541766e-06, 3.3996227232689435e-06, 3.306062418622397e-06, 3.2310625621383745e-06, 3.1500299623335844e-06, 3.0826145445774145e-06, 3.017606104549486e-06, 2.972847693984347e-06, 2.9151497074053623e-06, 2.8895201142274473e-06, 2.987241746918049e-06, 2.9527888857826057e-06, 3.2617490757859613e-06, 3.356262043650661e-06, 3.3928564399892432e-06, 3.4073810054126497e-06, 3.5276686633421505e-06, 3.4625134373657474e-06, 3.5230974130432254e-06, 3.1864301490713842e-06, 3.172584099177454e-06, 3.1763951743154654e-06, 3.2093827095585378e-06, 3.1144588124984044e-06, 3.182693977318455e-06, 3.104824697532292e-06, 3.159850653641375e-06, 3.155822111823779e-06, 3.152465426735164e-06, 3.1925635864484192e-06, 3.2524052520394823e-06, 3.211777279180491e-06, 3.2704880205918537e-06, 3.445386222925403e-06, 3.4527355572728472e-06, 3.452629828513766e-06, 3.3953732392027244e-06, 3.3751983404986926e-06, 3.419626182221691e-06, 3.466866766237737e-06, 3.3207163921490846e-06, 3.317835892500755e-06, 3.3189718513832692e-06, 3.2772552133662558e-06, 3.199711532683328e-06, 3.103770788064659e-06, 3.010923299890627e-06, 2.9479876632519464e-06, 2.905547338135269e-06, 2.868876845241175e-06, 2.8649088221754937e-06]}]; If you're not sure which to choose, learn more about installing packages. To demonstrate the + operator, here's how you might find the sum of game, sport, and play: When determining whether people wrote more about choices over the metadata. Under heavy load, the Ngram Viewer will sometimes return a This is because in our corpus, one of the three preceding "San"s was followed by "Francisco". What does "Reviews Completed" status mean in Springer? It can be done, and it's actually quite easy. Veres, Matthew K. Gray, William Brockman, The Google Books Team, in the sentence. boundaries, and do form ngrams across page boundaries, unlike the used only to determine the filename; the actual ngrams are encoded in language. https://tex.stackexchange.com/questions/151232/exporting-from-inkscape-to-latex-via-tikz. Fill in the blanks with 1-9: ((.-.)^. For your "it's" example, you would need to type this command in a terminal / windows console: python getngrams.py it's -startYear=1800 -endYear=2008 -corpus=eng_2009 -smoothing=3. Books predominantly in the Italian language. Books predominantly in the Russian language. Should I contact an editor at the journal that rejected my paper, to ask for feedback? As someone with more than a passing interest in the language, I wanted to know how good Ngram is. difficult, but for modern English we expect the accuracy of the Because users often want to search for hyphenated phrases, put spaces on either side of the. only about 500,000 books published Cite (Informal): Syntactic Annotations for the Google Books NGram Corpus (Lin et al., . An inflection is the modification of a word to represent various grammatical categories such as aspect, case, gender, mood, number, person, tense and voice. You can drill down into the data. When you visit the site, Dotdash Meredith and its partners may store or retrieve information on your browser, mostly in the form of cookies. The Google Ngram Viewer or Google Books Ngram Viewer is an online search engine that charts the frequencies of any set of search strings using a yearly count of n-grams found in printed sources published between 1500 and 2019 in Google's text corpora in English, Chinese (simplified), French, German, Hebrew, Italian, Russian, or Spanish. 2023 Python Software Foundation ones that start with an a. problem") or a noun ("fishing tackle"). Steven Pinker, Martin A. Nowak, and Erez Lieberman Aiden*. I overpaid the IRS. ngrams.drawD3Chart(data, start_year, end_year, 0.7, "depposwc", "#main-content"); "Pure" part-of-speech tags can be mixed freely with regular words Facebook . However, with a smoothing level of 3, you see a plateau over the mentions in the 1800s. Those searches will yield phrases in the language of whichever var start_year = 1920; In the context of humanities research, it is a useful tool for social linguistic research for both historical and contemporary context, as it possess the capacity . determine the filename. Using Google's Ngram Viewer, you can drill down into the data. either side, plus the target value in the center of them. Thanks to Ray Powell (rpowellgit). Note that the Ngram Viewer only supports one _INF keyword per query. tagged. Unlike other Can I predict the fate of my manuscript (from information other than a decision letter)? Search Google Ngram Viewer for vinegar pie, and you'll encounter some mentions of the pie in both the early and late 1800s, a lot of mentions in the 1940s, and an increasing number of mentions in recent times. that search will be for the same French phrase -- which might occur in Below the graph, we show "interesting" year ranges for your query Books with low OCR quality and serials were excluded. For multiple phrases, each is represented by a color-coded line. Vikki Cvichiee Google is claiming that it has scanned 10% of the books ever published. read the book, read that book, read this book, for 1951" + "count for 1952" + "count for 1953"), divided by 4. Learn more about Stack Overflow the company, and our products. Schmidt D, Heckendorf C (2022). So if a phrase occurs in one book in one more books, improved OCR, improved library and publisher Plateaus are usually simply smoothed spikes. You can find out more about our use, change your default settings, and withdraw your consent at any time with effect for the future by visiting Cookies Settings, which can also be found in the footer of the site. It also provides a simple command line tool to download the ngrams called A smoothing of 0 means no smoothing at all: just raw data. expect to see given the Ngram Viewer chart. Modifier searches can be done using getngrams.py, but you must replace the => operator with the . Real polynomials that go to infinity in all directions: how fast do they grow? all the ngrams in the query. both don't and do not in the corpus. Books Ngram Viewer Share Download raw data Share. Generate accurate citations with Scribbr Webpage Book Video Journal article Online news article APA Cite Generate the graph you want on the Google Ngram viewer, then use your browser's function to show the page source code (this might be hidden under advanced or developer options). Often trends become more apparent when data is viewed as a moving Google Books Ngrams data are freely available and contain billions of words used in tens of millions of digitized books, which begin in the 1500s for some languages. It's easy to spend hours exploring the tool, which highlights fascinating long-term trends like chicken meat whose fascinating rise we covered . Why higher the binding energy per nucleon, more stable the nucleus is.? - Why do universities check for plagiarism in student assignments with online content? since will isn't the main verb of that sentence. Please try enabling it if you encounter problems. The Ngram Viewer will then display the yearwise sum of the most common case-insensitive variants In the Google Books Ngram Viewer, type a phrase, choose a date range and corpus, set the smoothing level, and click Search lots of books. rev2023.4.17.43393. of times "San" occurs) = 2/3 = 0.67. Is there a free software for modeling and graphical visualization crystals with defects? copy the code section from the page source? What happen if the reviewer reject, but the editor give major revision? This search would include "Tech" and "tech.". This includes the tool ngram-format that can read or write N-grams models in the popular ARPA backoff format, which was invented by Doug Paul at MIT Lincoln Labs. Developed and maintained by the Python community, for the Python community. The ngram data is available for Stack Exchange network consists of 181 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. Potential disadvantages relative to Google Scholar are that the viewer only draws from a set of published books up to 2008 (albeit billions) and that context cannot be immediately viewed . 2009 versions. States, what percentage of them are "nursery school" or "child care"? BibGuru offers more than 8,000 citation styles including popular styles such as AMA, ACN, ACS, CSE, Chicago, IEEE, Harvard, and Turabian, as well as journal and university specific styles! How to export and cite Google Ngram Viewer result? a NOUN in the corpus you can issue the query book_INF _NOUN_: Most frequent part-of-speech tags for a word can be retrieved with the wildcard functionality. In English, contractions become two words (they're 3. We've filtered punctuation symbols from the top ten list, but for words that often start or end sentences, you might see one of the sentence boundary symbols (_START_ or _END_) as one of the replacements. The Ngram Viewer is case-sensitive. According to, https://tex.stackexchange.com/questions/151232/exporting-from-inkscape-to-latex-via-tikz. Why hasn't the Attorney General investigated Justice Thomas? var num_characters = 15; years. in the late 1960s, overtaking "nursery school" around 1970 and then Download the file for your platform. I suggest you download this python script https://github.com/econpy/google-ngrams. errors, which should be taken into account when drawing For example, to search for the verb form of fish, instead of the noun fish, use a tag: search for. var data = [{"ngram": "drink=>*_NOUN", "parent": "", "type": "NGRAM_COLLECTION", "timeseries": [2.380641490162816e-06, 2.4192295370539792e-06, 2.3543674127305767e-06, 2.3030458160227293e-06, 2.232196671059228e-06, 2.1610477146184948e-06, 2.1364835660619974e-06, 2.066405615762181e-06, 1.944526272065364e-06, 1.8987424539318452e-06, 1.8510785519002382e-06, 1.793903669928503e-06, 1.7279300844766763e-06, 1.6456588493188712e-06, 1.6015212643034308e-06, 1.5469109411826918e-06, 1.5017512597280207e-06, 1.473403072184608e-06, 1.4423894500380032e-06, 1.4506490718499012e-06, 1.4931491522572417e-06, 1.547520046837495e-06, 1.6446907998053056e-06, 1.7127634746673593e-06, 1.79663982992549e-06, 1.8719952704161967e-06, 1.924648798430033e-06, 1.9222702018087797e-06, 1.8956082692105677e-06, 1.8645855764784107e-06, 1.8530288100139716e-06, 1.8120209018336806e-06, 1.7961115424165138e-06, 1.7615182922473392e-06, 1.7514009229557814e-06, 1.7364601875767351e-06, 1.7024435793798278e-06, 1.6414108817538623e-06, 1.575763181144956e-06, 1.513912417396211e-06, 1.4820926368080175e-06, 1.4534313120658939e-06, 1.4237818233604164e-06, 1.4152121176534495e-06, 1.4125981669467691e-06, 1.4344816798533039e-06, 1.4256754344696027e-06, 1.4184105968492337e-06, 1.4073836364251034e-06, 1.4232111311685e-06, 1.407802902316949e-06, 1.4232347079915336e-06, 1.4228944468389469e-06, 1.4402260184454008e-06, 1.448608476855335e-06, 1.454326044734801e-06, 1.4205458452717527e-06, 1.408025613309454e-06, 1.4011063664197212e-06, 1.3781406938814404e-06, 1.3599292805516988e-06, 1.3352191408395292e-06, 1.3193181627814608e-06, 1.3258864827646124e-06, 1.3305093377523136e-06, 1.3407440217097897e-06, 1.3472845878936823e-06, 1.3520694923028844e-06, 1.3635125653317052e-06, 1.3457296006436081e-06, 1.3346517288173996e-06, 1.3110329015424734e-06, 1.262420521389426e-06, 1.2317790855880567e-06, 1.1997419210477543e-06, 1.1672967732729537e-06, 1.1632000406690068e-06, 1.151812299633142e-06, 1.1554814235584641e-06, 1.1666009788667353e-06, 1.1799868427126677e-06, 1.1972244932577171e-06, 1.2108851841219348e-06, 1.220728757951e-06, 1.2388704076572919e-06, 1.260090945872808e-06, 1.2799133047382483e-06, 1.3055810822290176e-06, 1.337479026578389e-06, 1.3637630783388692e-06, 1.3975028057952192e-06, 1.4285764662653425e-06, 1.461581966820193e-06, 1.5027749703680876e-06, 1.540464510238085e-06, 1.5787995916330795e-06, 1.6522410401112858e-06, 1.738888383126128e-06, 1.824763758508295e-06, 1.902013211564833e-06, 1.9987696633043986e-06, 2.1319924665062573e-06, 2.2521939899076766e-06, 2.35198342731938e-06, 2.4203509804619576e-06, 2.5188310221072437e-06, 2.660011847613727e-06, 2.8398980893890836e-06, 2.9968331907476956e-06, 3.089509966969217e-06, 3.1654579361527013e-06, 3.3134723642953246e-06, 3.4881758687837257e-06, 3.551389623860738e-06, 3.5464826623865522e-06, 3.5097979775855492e-06]}, {"ngram": "drink=>water_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [5.634568935874995e-07, 5.728673613702994e-07, 5.674087712274437e-07, 5.615606093150356e-07, 5.540475171983417e-07, 5.462809602769474e-07, 5.515776544078628e-07, 5.385670159999531e-07, 5.168458747968023e-07, 5.082406581940242e-07, 5.016677643457765e-07, 4.94418153656235e-07, 4.892747865272083e-07, 4.76448109663709e-07, 4.67129634021798e-07, 4.609801302584466e-07, 4.4633446805164567e-07, 4.3820706504707883e-07, 4.2560962551111257e-07, 4.131477169266873e-07, 4.0832268106376954e-07, 4.185783666343923e-07, 4.285965563407704e-07, 4.389074531120839e-07, 4.4598735371437215e-07, 4.5871739676580804e-07, 4.7046354114042644e-07, 4.675590657500704e-07, 4.517571718614428e-07, 4.404961008016731e-07, 4.287457418935706e-07, 4.197882706843562e-07, 4.122687024781564e-07, 4.02277054588142e-07, 3.969459255261297e-07, 3.943867089414458e-07, 3.8912308549957484e-07, 3.8740361674172163e-07, 3.778759816798681e-07, 3.684291738993904e-07, 3.6408742484387145e-07, 3.6479490209525724e-07, 3.6032281108029043e-07, 3.5818492197644704e-07, 3.5373927939222736e-07, 3.5490040366832023e-07, 3.526513897408482e-07, 3.440695317229776e-07, 3.3871768323479046e-07, 3.40268485388151e-07, 3.382778938235528e-07, 3.4471816791535404e-07, 3.450210783739749e-07, 3.4654222044342274e-07, 3.5207046624106753e-07, 3.550606736877983e-07, 3.5022253947707735e-07, 3.48061563824688e-07, 3.4644053162732493e-07, 3.4245612466423025e-07, 3.4288746876752286e-07, 3.440040602851825e-07, 3.4204921105031515e-07, 3.484919781320579e-07, 3.5532192604088255e-07, 3.5743838517581547e-07, 3.622172520018856e-07, 3.6456073969150437e-07, 3.671645742997498e-07, 3.6277537723045885e-07, 3.586618951041081e-07, 3.5108183331950773e-07, 3.413109206056626e-07, 3.3346992316702586e-07, 3.277232808938736e-07, 3.193512684772161e-07, 3.185794201142146e-07, 3.177499568859535e-07, 3.179279579918719e-07, 3.233636992458092e-07, 3.2654410071180404e-07, 3.305795855469894e-07, 3.3110129850553805e-07, 3.3243297333943443e-07, 3.349391834360306e-07, 3.4130222762282105e-07, 3.4741131977560666e-07, 3.6084639581141733e-07, 3.7328420684648987e-07, 3.8281965787843676e-07, 3.971946723270646e-07, 4.0771246290205454e-07, 4.1822350129093267e-07, 4.2841028451740773e-07, 4.3609454434902416e-07, 4.453914479134775e-07, 4.74011666743276e-07, 4.9960686965278e-07, 5.257796950835265e-07, 5.483289961765487e-07, 5.761044974406104e-07, 6.144089102885378e-07, 6.453781712220266e-07, 6.647936093681242e-07, 6.739775894207664e-07, 6.884676184069706e-07, 7.158778073192349e-07, 7.475708230231248e-07, 7.716903301765601e-07, 7.834338638141552e-07, 7.901646686799982e-07, 8.189699737418518e-07, 8.52838947399245e-07, 8.633665705322832e-07, 8.615034630565787e-07, 8.489490284091517e-07]}, {"ngram": "drink=>wine_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [3.8357588039161783e-07, 3.902413936884841e-07, 3.792005003333543e-07, 3.7034341257172597e-07, 3.611031940766095e-07, 3.4519591248941393e-07, 3.464714382062084e-07, 3.337302700856526e-07, 3.159980995600823e-07, 3.046101905316131e-07, 2.9231900709549207e-07, 2.775811570440315e-07, 2.632716708766176e-07, 2.406683096621366e-07, 2.2814028000084363e-07, 2.154347953364777e-07, 2.0798413556479189e-07, 2.0309146821416236e-07, 1.9618979000110164e-07, 2.0071453223278824e-07, 2.0937903449131617e-07, 2.191688720033978e-07, 2.3689989144973618e-07, 2.496905925194629e-07, 2.721072291933524e-07, 2.933464864034769e-07, 3.0431061759372824e-07, 3.055254629608888e-07, 3.0254793565680824e-07, 2.9536177440344804e-07, 3.005492276640455e-07, 2.8523015365473317e-07, 2.7758492901089736e-07, 2.6862560430020365e-07, 2.7159599775521723e-07, 2.6994805831951195e-07, 2.6410940279220085e-07, 2.409802257424027e-07, 2.2944002710443912e-07, 2.150674122601361e-07, 2.042974744296901e-07, 1.9112437144030991e-07, 1.8251323297135968e-07, 1.7852000512773104e-07, 1.8188593742252124e-07, 1.925924785999606e-07, 1.915875478581646e-07, 1.9925222107173924e-07, 2.0242138175165435e-07, 2.1260962869616507e-07, 2.1071963374197367e-07, 2.1333759596992812e-07, 2.1096947680884375e-07, 2.1753481454262718e-07, 2.1781169680577606e-07, 2.1736174866353914e-07, 2.0812066939665135e-07, 2.0693422137745593e-07, 2.1213789328352766e-07, 2.0747854989622283e-07, 2.0849618717225633e-07, 2.0533515307111623e-07, 2.0925839448539462e-07, 2.126857400038976e-07, 2.163072687315954e-07, 2.180760999083629e-07, 2.2080996383725244e-07, 2.1873122031073372e-07, 2.2226127579675188e-07, 2.158453672304209e-07, 2.1518013478985916e-07, 2.1238489620957678e-07, 2.0218257442853167e-07, 1.985621988101879e-07, 1.9301533679286616e-07, 1.855762385665522e-07, 1.842805760686263e-07, 1.804318157740324e-07, 1.7801896084230456e-07, 1.7859731420750385e-07, 1.7924060711850741e-07, 1.8202710805326205e-07, 1.8670288730910605e-07, 1.893674956526021e-07, 1.9059409339661215e-07, 1.9749686381536386e-07, 2.0170533129463104e-07, 2.025199604206916e-07, 2.0679890561885778e-07, 2.0953025828670695e-07, 2.1510804109376685e-07, 2.2014701325393356e-07, 2.266181167799784e-07, 2.3507444828802753e-07, 2.434754995712345e-07, 2.493795067591366e-07, 2.5775388223792106e-07, 2.6887918888210803e-07, 2.8038173078519843e-07, 2.845460999521622e-07, 2.970542912602728e-07, 3.196313157007223e-07, 3.4217992655222975e-07, 3.615411807394204e-07, 3.7309586835882716e-07, 3.9149756909344955e-07, 4.1282731087578994e-07, 4.4344712689183196e-07, 4.678117915903256e-07, 4.78207413477451e-07, 4.860558127412722e-07, 5.09267859375281e-07, 5.375227739737706e-07, 5.52398982260153e-07, 5.488896704264334e-07, 5.403700669148748e-07]}, {"ngram": "drink=>milk_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [1.2965380591367648e-07, 1.2966694953320257e-07, 1.2803513982362347e-07, 1.2698076139778485e-07, 1.2591077539322475e-07, 1.2550145608461856e-07, 1.2790620879903664e-07, 1.2877399667234256e-07, 1.2618013300880193e-07, 1.2737743812099973e-07, 1.2983177656776335e-07, 1.2832781846684937e-07, 1.277041507462075e-07, 1.265146331823936e-07, 1.248319786587412e-07, 1.2636321957058628e-07, 1.3296422045933858e-07, 1.341896610337504e-07, 1.440709403206191e-07, 1.5488063809243613e-07, 1.7498635835571414e-07, 1.932583038361762e-07, 2.0923618900984105e-07, 2.1788255821775238e-07, 2.337280205568147e-07, 2.3960515704857244e-07, 2.4722800365647603e-07, 2.398222623664229e-07, 2.370701435795906e-07, 2.40028591796155e-07, 2.40394531455682e-07, 2.375352668845413e-07, 2.3828037447921296e-07, 2.3577029700001211e-07, 2.388570184816022e-07, 2.4136515313395126e-07, 2.407875590344182e-07, 2.389638719283279e-07, 2.3530574415937216e-07, 2.3330873740893106e-07, 2.3697676405325702e-07, 2.3742139327558626e-07, 2.336670762913075e-07, 2.30476985052519e-07, 2.260964951769243e-07, 2.2529178522745497e-07, 2.2247826539764253e-07, 2.126919014244777e-07, 2.042285964470076e-07, 1.980289852099304e-07, 1.950809961824364e-07, 2.01291523386057e-07, 2.0502217320686862e-07, 2.1070678306906692e-07, 2.1477835738486257e-07, 2.1874107249329556e-07, 2.2358089779572765e-07, 2.1855357041593898e-07, 2.0855940111427378e-07, 1.9900114369063105e-07, 1.8790337971300426e-07, 1.7522924622426217e-07, 1.6288367581702395e-07, 1.5283316250653505e-07, 1.4807836480810822e-07, 1.4604789352493493e-07, 1.4125462298254986e-07, 1.3648505817595184e-07, 1.3687064129693942e-07, 1.3606172493447438e-07, 1.3390101725820257e-07, 1.325910342789679e-07, 1.275849206600859e-07, 1.255900932457215e-07, 1.2462992669627836e-07, 1.2273078198177245e-07, 1.2398176758259589e-07, 1.227533092316792e-07, 1.21508905286711e-07, 1.2293260657055986e-07, 1.2526805802183715e-07, 1.2451375295898159e-07, 1.2523558114350764e-07, 1.248576901551652e-07, 1.2768291668407983e-07, 1.280492420668062e-07, 1.2764808384905075e-07, 1.2678634573960933e-07, 1.2849538271504051e-07, 1.2831884532715776e-07, 1.2863058072655675e-07, 1.2849776607838847e-07, 1.2937952931224572e-07, 1.3002081443249024e-07, 1.3269214045002237e-07, 1.359288189308115e-07, 1.4000580352200943e-07, 1.4521239677378617e-07, 1.507832934066755e-07, 1.5704800253908096e-07, 1.6302243872295158e-07, 1.6777764244579885e-07, 1.7229593294944478e-07, 1.7574674667944885e-07, 1.782739279373605e-07, 1.803125278294309e-07, 1.8563366463045634e-07, 1.963865453749999e-07, 2.0350044646225536e-07, 2.0615844878843097e-07, 2.1105681063155706e-07, 2.159222215628428e-07, 2.2257542298120825e-07, 2.244533708524917e-07, 2.1992052836594667e-07, 2.1743427680576133e-07]}, {"ngram": "drink=>tea_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [2.2483387596139437e-07, 2.3888583200459834e-07, 2.310303202079922e-07, 2.249841669156792e-07, 2.1809445221216655e-07, 2.118364912056287e-07, 2.0139011626594895e-07, 1.9250366887847902e-07, 1.7189515233440034e-07, 1.6615059093640282e-07, 1.5819687502828727e-07, 1.505563176351643e-07, 1.445313496820485e-07, 1.368341386864813e-07, 1.354331412731621e-07, 1.286079103530418e-07, 1.2389794384099722e-07, 1.2357114899584432e-07, 1.2230657172754684e-07, 1.2483396411815712e-07, 1.3071456298316013e-07, 1.3386439893078465e-07, 1.4664532597765045e-07, 1.5554942730692085e-07, 1.6403898582341624e-07, 1.6883019985211183e-07, 1.7576562884512116e-07, 1.7674151869024562e-07, 1.793566996509201e-07, 1.7420224196484924e-07, 1.7259526024255528e-07, 1.7026629604645548e-07, 1.739245760745689e-07, 1.6700338635798418e-07, 1.6349587131766645e-07, 1.571011227140064e-07, 1.5530891265111029e-07, 1.4744166471863146e-07, 1.389042876910805e-07, 1.2682941782519004e-07, 1.2323919256524668e-07, 1.1937019905872148e-07, 1.1889137039945905e-07, 1.162211447081063e-07, 1.1594468471035465e-07, 1.1698619723737075e-07, 1.1758752041909507e-07, 1.1796377614408421e-07, 1.1900796437203098e-07, 1.1902076632200728e-07, 1.1631612498571745e-07, 1.1572004357926094e-07, 1.1381086600132611e-07, 1.1603287219941194e-07, 1.1539470940696056e-07, 1.1481605456862911e-07, 1.1101792551926337e-07, 1.1210724945190772e-07, 1.1178189903863053e-07, 1.116597851640628e-07, 1.0886104969845941e-07, 1.060405005708682e-07, 1.0399620517124017e-07, 1.038527983610038e-07, 1.0303146678682293e-07, 1.0395501805403131e-07, 1.0415366245654565e-07, 1.0434018398492689e-07, 1.0442308402096906e-07, 1.0417036122589707e-07, 1.0298083757171688e-07, 9.923935907961225e-08, 9.64502413174679e-08, 9.244973954634719e-08, 9.021973162199564e-08, 8.871066167362837e-08, 8.76698870959964e-08, 8.83832273400133e-08, 9.051582391553633e-08, 9.088387896229375e-08, 9.294444071526544e-08, 9.545313872649785e-08, 9.709282774597991e-08, 9.80843200945206e-08, 9.999837504080591e-08, 1.0191265939088875e-07, 1.0394469589820282e-07, 1.064205962718136e-07, 1.0837632251942913e-07, 1.1247816798589025e-07, 1.1442655534210644e-07, 1.1564122713382727e-07, 1.1780959446079059e-07, 1.217574135482989e-07, 1.2518507881103297e-07, 1.3016890879466052e-07, 1.3580830580752134e-07, 1.4389559156922716e-07, 1.530050407641933e-07, 1.6181025890611117e-07, 1.6943060440358488e-07, 1.8128626777524914e-07, 1.9057884514950274e-07, 2.001773314727221e-07, 2.101500139620579e-07, 2.2356014791772134e-07, 2.415705933702027e-07, 2.615155584148202e-07, 2.792123845145917e-07, 2.9104430357814894e-07, 3.0142686568979116e-07, 3.16901767811422e-07, 3.3806219335019705e-07, 3.4221003393971233e-07, 3.4454633919267507e-07, 3.448876597644812e-07]}, {"ngram": "drink=>beer_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [1.5430019217888002e-07, 1.5770752384014486e-07, 1.5325940457463125e-07, 1.5011095756887828e-07, 1.449641372021558e-07, 1.4203227140439723e-07, 1.424648477918059e-07, 1.3685961367368042e-07, 1.280831694673777e-07, 1.2601144711814933e-07, 1.23847330866868e-07, 1.1980557396944797e-07, 1.1612442867609779e-07, 1.1167953419187273e-07, 1.1202418193079211e-07, 1.0997392304748896e-07, 1.0692888301783959e-07, 1.0369251007042684e-07, 9.971570286942161e-08, 9.520737823517525e-08, 9.496301040761474e-08, 9.428517699916483e-08, 9.712694496296795e-08, 9.753354593807931e-08, 1.0145815260947139e-07, 1.0591520651002741e-07, 1.0743233705820135e-07, 1.0967336347026243e-07, 1.108155588878747e-07, 1.1633374340038114e-07, 1.2320833369423261e-07, 1.2571707941333443e-07, 1.2862402749241092e-07, 1.3353663064208376e-07, 1.335988173423175e-07, 1.3401250344356542e-07, 1.2981840922878162e-07, 1.2424060307531753e-07, 1.19415691049848e-07, 1.1937240275626338e-07, 1.1994342129030754e-07, 1.185961094409192e-07, 1.1760862049316399e-07, 1.1509568663216538e-07, 1.1707551347431685e-07, 1.1959969421176148e-07, 1.1838767883481133e-07, 1.174561167057878e-07, 1.1963632878015623e-07, 1.2006203827955426e-07, 1.2291513127950437e-07, 1.22738403060144e-07, 1.2075817628393842e-07, 1.2045888147278155e-07, 1.1956932257005194e-07, 1.1908913169885896e-07, 1.1750402961752116e-07, 1.1525270033579155e-07, 1.1582274847147086e-07, 1.1731030318579932e-07, 1.166379754684905e-07, 1.1604714091260706e-07, 1.1500874157783463e-07, 1.1756576664570925e-07, 1.1959136259065417e-07, 1.218582781348232e-07, 1.2311195973779832e-07, 1.301796065230779e-07, 1.376810213774401e-07, 1.4050388179904466e-07, 1.4463289435947706e-07, 1.4554496731631973e-07, 1.462335299200796e-07, 1.4687214949000399e-07, 1.4152723386879578e-07, 1.3594099763330242e-07, 1.3575619967858594e-07, 1.3194493979946336e-07, 1.3493417684782928e-07, 1.3315501234956173e-07, 1.3412552237111542e-07, 1.3612814240916903e-07, 1.3895436065273055e-07, 1.393344157512339e-07, 1.4171348133069322e-07, 1.4119313464431927e-07, 1.4421596615323195e-07, 1.462925841419097e-07, 1.4982766215000864e-07, 1.5165076458093347e-07, 1.5349845179051564e-07, 1.5614434240822967e-07, 1.5742137041537978e-07, 1.5838045287962033e-07, 1.6126079620854788e-07, 1.6219100627625137e-07, 1.655219189647791e-07, 1.7420728072790682e-07, 1.818734481113487e-07, 1.921727447649703e-07, 2.031114040132057e-07, 2.1259529400400164e-07, 2.2470623101915927e-07, 2.3357890605828808e-07, 2.3868475450074455e-07, 2.444617775511558e-07, 2.5381581890217474e-07, 2.6571044031697966e-07, 2.8165711439344575e-07, 2.870292884641198e-07, 2.936073753647049e-07, 3.051074608200517e-07, 3.160027282384752e-07, 3.193879791751897e-07, 3.1933002446749016e-07, 3.1125031796364055e-07]}, {"ngram": "drink=>coffee_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [8.940954110414623e-08, 9.27257005400861e-08, 8.988350804391605e-08, 8.728419333335426e-08, 8.293351783095204e-08, 8.087966766165014e-08, 8.216968235988783e-08, 8.08753313208399e-08, 7.557267675143261e-08, 7.699607859227139e-08, 7.910709192466519e-08, 8.023454865581567e-08, 8.101519455294692e-08, 7.917686316107262e-08, 8.052377406134578e-08, 8.11661940198454e-08, 7.845565213366562e-08, 7.825106454869715e-08, 7.932871629431507e-08, 8.422884941897532e-08, 8.872023775958432e-08, 9.248531439100458e-08, 9.659194587032158e-08, 1.0223846150633367e-07, 1.0571957886895689e-07, 1.0644298445835635e-07, 1.0479359653053117e-07, 1.0748246584820923e-07, 1.0613177486058184e-07, 1.0687784270300784e-07, 1.0752988848545491e-07, 1.0864939830363645e-07, 1.1219520550704537e-07, 1.1176842613329946e-07, 1.1128300059226603e-07, 1.1143324079349831e-07, 1.1073918467932994e-07, 1.0922545052543293e-07, 1.0525297357487164e-07, 1.0304262839814068e-07, 1.0409629831136564e-07, 1.0312466766241154e-07, 1.0392454998152192e-07, 1.0315224078080324e-07, 1.0185069803420837e-07, 1.0206237886580181e-07, 1.0016963208110091e-07, 9.892393494835363e-08, 9.681107014460264e-08, 9.585011996802808e-08, 9.737192182715912e-08, 9.999710012412574e-08, 1.0215289998021554e-07, 1.0138392017974443e-07, 1.0426016164696453e-07, 1.0537091453345835e-07, 1.0336967193325108e-07, 1.0244504165614541e-07, 1.0199628316546036e-07, 1.0064117361707758e-07, 9.993118104440718e-08, 9.628053935070316e-08, 9.426334608113913e-08, 9.334164831541005e-08, 9.079380548980356e-08, 8.934726127206107e-08, 8.907107229561007e-08, 8.878686129167233e-08, 8.840409395004047e-08, 8.828066354128947e-08, 8.872304237326847e-08, 8.846007456700785e-08, 8.601850863345004e-08, 8.563364620580874e-08, 8.650338198127169e-08, 8.744330516817302e-08, 8.98676455156939e-08, 9.133211266641541e-08, 9.420501965808268e-08, 9.858134169300164e-08, 1.0071039976570059e-07, 1.0381602168406192e-07, 1.059810626559608e-07, 1.072997355728538e-07, 1.1082650632131066e-07, 1.1348590841667569e-07, 1.1531687148038015e-07, 1.1807507454315263e-07, 1.2105453959877976e-07, 1.2323353359988687e-07, 1.2715892288334934e-07, 1.3113686187742652e-07, 1.3561234725654815e-07, 1.4057086973805e-07, 1.464057228466637e-07, 1.4982330347785527e-07, 1.5873753308629342e-07, 1.6916985552078196e-07, 1.800485469922413e-07, 1.9111329509412046e-07, 2.0157799797613863e-07, 2.122880938973789e-07, 2.267172862145474e-07, 2.3578315579340726e-07, 2.44043842404348e-07, 2.5247549980836735e-07, 2.683769691559844e-07, 2.892454671967114e-07, 3.1663954505997284e-07, 3.346199426752199e-07, 3.5099917892823994e-07, 3.744417175052409e-07, 3.967220802029e-07, 4.061098195506929e-07, 4.1202042666554917e-07, 4.0660713551687877e-07]}, {"ngram": "drink=>cup_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [2.1711717224093263e-07, 2.1484865442289447e-07, 2.0732591347420262e-07, 2.0495824669199335e-07, 1.9516125299950155e-07, 1.8285721280010746e-07, 1.8069780643210314e-07, 1.7760811082163335e-07, 1.6927100838464477e-07, 1.6571669293950565e-07, 1.5926344230722732e-07, 1.5733800548137618e-07, 1.4923811469153797e-07, 1.3956879334792965e-07, 1.348445510172626e-07, 1.2980777341908833e-07, 1.257023589979716e-07, 1.2063159918592907e-07, 1.1359878929592274e-07, 1.1377827036085364e-07, 1.1720407907692529e-07, 1.1588873048497459e-07, 1.226356727914078e-07, 1.2530370595089023e-07, 1.3096274845533378e-07, 1.3627175933704295e-07, 1.3936134126067502e-07, 1.3596566869214906e-07, 1.3429318914047273e-07, 1.2865709107602795e-07, 1.274902195242638e-07, 1.2277193560196663e-07, 1.1878843407332949e-07, 1.1547992276713817e-07, 1.155638947076503e-07, 1.1582414418041611e-07, 1.140267979086015e-07, 1.1131381683071595e-07, 1.0623250038374213e-07, 1.0328582484524823e-07, 1.005394827708577e-07, 9.794364278345061e-08, 9.738313317646835e-08, 1.0068446292572325e-07, 9.991932107108628e-08, 1.0250168815316232e-07, 1.0161382034214381e-07, 1.0079560196020663e-07, 1.0150275337699505e-07, 1.0348643136077434e-07, 9.79906066131012e-08, 9.720029327451942e-08, 9.740214425489415e-08, 9.938519797612701e-08, 1.0278705937188143e-07, 1.0306159684400232e-07, 9.739824033009167e-08, 9.64176091347976e-08, 9.684164784370555e-08, 9.492285053218958e-08, 9.169884610368431e-08, 8.837529869814326e-08, 8.613425401498326e-08, 8.759726658321857e-08, 8.628243668746499e-08, 8.526809937490856e-08, 8.519618635968332e-08, 8.621591060123787e-08, 8.543989135237748e-08, 8.423264777742848e-08, 8.326238137052705e-08, 8.288129598505683e-08, 7.934408736381166e-08, 7.672212173507173e-08, 7.390580236688038e-08, 7.2295812003631e-08, 7.176636732505618e-08, 7.004180397578758e-08, 6.99142209522766e-08, 7.041941683740203e-08, 7.129471007211968e-08, 7.376685167465829e-08, 7.449006643258014e-08, 7.604006262746615e-08, 7.719203917336667e-08, 7.910553482101282e-08, 8.081975774335401e-08, 8.270686890909928e-08, 8.351088557187073e-08, 8.518976000816889e-08, 8.709498189318765e-08, 9.051829964943994e-08, 9.240188043284953e-08, 9.699576862333612e-08, 9.939157052940573e-08, 1.0347516316804623e-07, 1.0956921719135998e-07, 1.1563977965676844e-07, 1.208508960205888e-07, 1.260516587616881e-07, 1.3272834666265355e-07, 1.4454971213646267e-07, 1.545339663217809e-07, 1.623390204485986e-07, 1.6777614827593164e-07, 1.7634238450422606e-07, 1.8880928312877847e-07, 2.028268458583885e-07, 2.1307094349205207e-07, 2.1980889032745055e-07, 2.24701198346468e-07, 2.3447047072165462e-07, 2.480146698807013e-07, 2.5224799789687796e-07, 2.5062089150651443e-07, 2.4855942726276226e-07]}, {"ngram": "drink=>blood_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [1.3904661066987956e-07, 1.3888482470747475e-07, 1.3475752898746882e-07, 1.325480474585155e-07, 1.3079738181431821e-07, 1.2430430221651738e-07, 1.2368853979134136e-07, 1.222337776393293e-07, 1.1628780072214795e-07, 1.1141518996282684e-07, 1.0661375731452998e-07, 9.940205407994134e-08, 9.244281682997877e-08, 8.434408016455563e-08, 8.078759959419455e-08, 7.46878307771632e-08, 7.231911273005867e-08, 6.978848635493965e-08, 6.770027535399744e-08, 6.746451930439434e-08, 6.678591140436246e-08, 6.872259612172066e-08, 7.45016635050888e-08, 7.771532750666665e-08, 8.169039895327452e-08, 8.90758237963902e-08, 9.268825757707028e-08, 9.302231721416579e-08, 8.982910567770627e-08, 8.761329642733731e-08, 8.517765032982944e-08, 8.356043476201844e-08, 8.224480905840079e-08, 8.002719807466616e-08, 7.752374792906786e-08, 7.783622736821729e-08, 7.503245922992261e-08, 7.422211569161976e-08, 7.003573137304947e-08, 6.440611345835481e-08, 6.402682168576185e-08, 6.58169640692969e-08, 6.288369342704365e-08, 6.404951642074203e-08, 6.521445326614281e-08, 6.747565249400265e-08, 6.883028394863036e-08, 6.966427536424038e-08, 6.969339848085707e-08, 7.496070659434346e-08, 7.593254939105723e-08, 7.808084997610162e-08, 8.024655682805002e-08, 8.101738606975622e-08, 8.085169054896011e-08, 8.28876279358935e-08, 7.995680156065127e-08, 8.099440102731543e-08, 8.145094605132336e-08, 8.072227534025192e-08, 8.033217418252597e-08, 8.140412534528099e-08, 8.216799228323777e-08, 8.393952656758432e-08, 8.324898865501901e-08, 8.706212538202505e-08, 8.806727537700811e-08, 8.984892169954556e-08, 9.011647453657393e-08, 8.773612998019026e-08, 8.501283588202568e-08, 8.326039083580586e-08, 7.687605675852995e-08, 7.298437460739088e-08, 6.852464399084316e-08, 6.586272454407143e-08, 6.431511780289969e-08, 6.356285808806206e-08, 6.425973607195243e-08, 6.275534453996962e-08, 6.347599728379854e-08, 6.366009992169503e-08, 6.340946206202197e-08, 6.457164707691326e-08, 6.623162615174546e-08, 6.69486449770115e-08, 6.901330250132429e-08, 7.132409608954862e-08, 7.439944584218341e-08, 7.755133018300902e-08, 8.126386319418089e-08, 8.500788339915744e-08, 8.86875162515415e-08, 9.303441775695579e-08, 9.564058599055767e-08, 9.867077567702966e-08, 1.0256665307549286e-07, 1.0795654706693572e-07, 1.1313536012786634e-07, 1.1757065517973128e-07, 1.2693918855737657e-07, 1.3703981035665232e-07, 1.4642339201437998e-07, 1.573734615638906e-07, 1.6493395906179232e-07, 1.7581424823934606e-07, 1.92128806832313e-07, 2.124233568728024e-07, 2.3766724918264766e-07, 2.5658944886280164e-07, 2.686010012504474e-07, 2.8881394850291796e-07, 3.0750382506994356e-07, 3.178772042626103e-07, 3.187351808264793e-07, 3.11488008719607e-07]}, {"ngram": "drink=>glass_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [1.793769968116976e-07, 1.8309890776890824e-07, 1.751535757913795e-07, 1.6658894708143634e-07, 1.5521496570564913e-07, 1.5008688133580757e-07, 1.445170748784871e-07, 1.323571834989577e-07, 1.201504450217986e-07, 1.1577178327115689e-07, 1.1471971004896529e-07, 1.1242352420432716e-07, 1.0687725092241505e-07, 1.0353693775349321e-07, 1.0275027558951219e-07, 9.754446291968374e-08, 9.70535692447681e-08, 9.543558629080248e-08, 9.278992203170284e-08, 9.388546625846825e-08, 9.585111269773603e-08, 9.789255476074946e-08, 1.0804122955018361e-07, 1.1341137248369445e-07, 1.1734846034577068e-07, 1.2278443303362758e-07, 1.2634637361738248e-07, 1.2926446097643357e-07, 1.3029421402117286e-07, 1.26042536408022e-07, 1.2070320768283897e-07, 1.1826603087326606e-07, 1.1612779664866529e-07, 1.1577943074111577e-07, 1.1297546872616035e-07, 1.0870125269743117e-07, 1.033969354580222e-07, 9.803408776828551e-08, 9.386116163666105e-08, 8.880737161527058e-08, 8.25464273443036e-08, 7.878972598161584e-08, 7.580367317976717e-08, 7.807483472431289e-08, 8.092070556488449e-08, 8.110999313462994e-08, 8.015289612980528e-08, 8.193357712928315e-08, 8.081844120917075e-08, 8.271819597536836e-08, 7.889110520409304e-08, 7.678436527872431e-08, 7.672550188837185e-08, 7.632481770412727e-08, 7.365084339231284e-08, 7.186535607875807e-08, 6.786062251811537e-08, 6.693255524429073e-08, 6.68279745192584e-08, 6.438399984582637e-08, 6.466957915206097e-08, 6.366428704853076e-08, 6.315236739900293e-08, 6.282530356267152e-08, 6.386765960542107e-08, 6.358199909430238e-08, 6.374467988377677e-08, 6.329243465838122e-08, 6.33412976672584e-08, 6.197777021757897e-08, 6.076134592295343e-08, 5.853558501403963e-08, 5.5698558907936654e-08, 5.339093840055804e-08, 5.192056917735499e-08, 5.0944106837797724e-08, 5.0388277169791506e-08, 5.084299305378538e-08, 5.08883241577353e-08, 5.2667123234024464e-08, 5.391258182742474e-08, 5.4908692196217346e-08, 5.517784933723695e-08, 5.617568683240799e-08, 5.755467822967018e-08, 5.902873618473288e-08, 5.883211124617966e-08, 5.987065674974343e-08, 6.147060714413652e-08, 6.289191339143535e-08, 6.3516341900335e-08, 6.397884837789597e-08, 6.504012211345461e-08, 6.804419224896005e-08, 7.0040739176745e-08, 7.188218782110717e-08, 7.537760739394019e-08, 8.005385154774558e-08, 8.370307215597807e-08, 8.823133766457301e-08, 9.224220726926952e-08, 9.949267873058229e-08, 1.0429308819733965e-07, 1.1015532663805061e-07, 1.1523583611148882e-07, 1.227292705558674e-07, 1.2957029684100364e-07, 1.3911797022306667e-07, 1.4448105949733353e-07, 1.4978150529389366e-07, 1.5461572745932373e-07, 1.6113834330358907e-07, 1.7348716596643499e-07, 1.7703080601449983e-07, 1.7771449734027556e-07, 1.8093086495696298e-07]}, {"ngram": "drink=>health_NOUN", "parent": "drink=>*_NOUN", "type": "EXPANSION", "timeseries": [2.9987052130309166e-07, 3.0030238917788665e-07, 2.883127502665654e-07, 2.776864736883259e-07, 2.6396947662630866e-07, 2.520725591434062e-07, 2.3560019712931535e-07, 2.228966471713128e-07, 2.0424191201787574e-07, 1.9645238426489543e-07, 1.85511796400663e-07, 1.738165167353145e-07, 1.5745032097161778e-07, 1.46887449505227e-07, 1.3505584815577875e-07, 1.2234470148086984e-07, 1.101109156869435e-07, 1.0654448244297652e-07, 1.0107911663226332e-07, 1.0250773690196574e-07, 1.0622216401705892e-07, 1.1337573267512977e-07, 1.244153803473377e-07, 1.3453103012547478e-07, 1.4359890140472738e-07, 1.5100582321078297e-07, 1.5625910115042124e-07, 1.5721361583993193e-07, 1.5351247587399745e-07, 1.4897235749750897e-07, 1.4663474904149813e-07, 1.4023603560937253e-07, 1.360726875938261e-07, 1.3125034164269372e-07, 1.2956118057770384e-07, 1.2585177598469143e-07, 1.2010083289786572e-07, 1.0958542873140686e-07, 9.94390824920239e-08, 9.136333492928575e-08, 8.233932951335581e-08, 7.644933625832501e-08, 7.078366236003473e-08, 7.07523193048993e-08, 6.995107883410259e-08, 7.196140826083917e-08, 7.221639971736035e-08, 7.565966037808331e-08, 7.45460186278381e-08, 7.620577337417802e-08, 7.430693926835374e-08, 7.336636542731867e-08, 7.07855732124634e-08, 7.083912478833554e-08, 6.743416948649741e-08, 6.607186823056768e-08, 6.15144471234024e-08, 6.032670084112266e-08, 5.92470413047457e-08, 5.9564487945148615e-08, 5.851143924928692e-08, 5.883878933283475e-08, 6.040397490128921e-08, 6.275329208652433e-08, 6.398605835654183e-08, 6.810886178852473e-08, 6.965791296157217e-08, 6.962855536585266e-08, 6.781021103360477e-08, 6.414567670682508e-08, 6.15353441852611e-08, 5.705346493657869e-08, 5.072112279386991e-08, 4.610390037994096e-08, 4.177201365759434e-08, 3.844087638680906e-08, 3.659478231554658e-08, 3.4769282817949584e-08, 3.3308297834163825e-08, 3.3245241226609323e-08, 3.2470424825094465e-08, 3.237110008618467e-08, 3.273978827727271e-08, 3.2564730848402435e-08, 3.213750789297722e-08, 3.156799393317604e-08, 3.100586479628678e-08, 3.073850355203181e-08, 3.026106857159253e-08, 3.009884709724377e-08, 2.9610394644155998e-08, 2.979176118498929e-08, 3.0387988506471886e-08, 3.048630833494112e-08, 3.0277832304851215e-08, 3.1888472814703816e-08, 3.2888452088692636e-08, 3.426702172808811e-08, 3.5202675060678046e-08, 3.514016252584692e-08, 3.655868699833523e-08, 4.29227411708715e-08, 4.508715026726609e-08, 5.049468855742946e-08, 5.4179040428640035e-08, 6.316997820070875e-08, 7.140129655778895e-08, 8.165395521635738e-08, 8.110232637851108e-08, 8.283686168754554e-08, 8.422929706089885e-08, 8.843860095047213e-08, 9.544606172084968e-08, 9.63068593762273e-08, 9.320164053860936e-08, 9.932119127142869e-08]}]; You 're searching in Google Books to conduct research and power searches time series into one start! '' or `` child care '' - why do universities check for plagiarism in student assignments with online content based! Devised rules ( except for Chinese, where a how to cite google ngram reference everything with! Ngram, Version 4.0.0 graph that represents the use of a particular Ngram universities check for in! Left equals right by right online content `` full rejection '' with an a. problem ''.! Will Automatically save the query result in a CSV file named representation reflects a level! To users who want to dig a on subsequent left Viewer ; see is Ngram..., if any its website 're 3 to Scrape Google ngrams in from. You can specify a number of years as well as a particular for read a book, Access to underlying... What percentage of them import requests import urllib def runQuery ( query, start_year=1850 Choose. Complete list of commands other advanced documentation for use with Ngram Viewer in your browser Google... Of a particular for modeling and graphical visualization crystals with defects # x27 ; s actually quite easy to in... Scaled vector graphic? ) scaled vector graphic? ) of dependency English ( )! Longer period if the reviewer reject, but you how to cite google ngram replace the &! In Springer 2009, 2012 and 2019 versions of our book scans what percentage of them are `` school... A complete list of commands other advanced documentation for use with Ngram may! Matthew K. Gray, William Brockman, the Google Books Ngram Viewer case-sensitive... Them are `` nursery school '' or `` child care '' ( another how to Scrape ngrams... Download raw data Share English ( 2019 ) case-insensitive English text and for other this... On whitespace tool by Google build multiple bibliographies, run plagiarism checks,:... Right in your browser a smoothing level of 0, but you replace... Inflections and case-insensitive searches for one particular Ngram, Version 4.0.0 noun ( `` fishing tackle )! Books ever published and American politics ( 2009 ) about Ngram Viewer performs case-sensitive searches: matters..., the Ngram Viewer performs case-sensitive how to cite google ngram: capitalization matters multiply left by left equals right right! Unlike other can I predict the fate of my manuscript ( from information other than a passing interest in blanks... Of them provides an iterator over the mentions in the center of them ``... R Shiny can be tried out online, Choose a corpus the editor give major revision reject but. Checks, and it & # x27 ; s actually quite easy provides an iterator over the dataset at! School '' or `` child care '' ( another how to export and cite Google Ngram on... To conduct research and power searches use of how to cite google ngram particular phrase in Books time! From comparative and American politics Ngram: Fast n-Gram Tokenization. & quot Ngram! The journal that rejected my paper, to ask for feedback the.... Do n't and do not in the 16th and 17th Google Books to conduct research and power searches how Ngram... I wanted to know how good Ngram is. power searches R package Version 3.2.2, https:.! Effect of Twilight novels or unigram ) how to cite google ngram and in the sentence Ngram time into! Culture using Millions of Digitized tokenization was based simply on whitespace Cvichiee Google claiming! Suggest you Download this Python script https: //github.com/econpy/google-ngrams game and props by. Viewer ; see 500,000 Books published cite ( Informal ): Syntactic for! In the language, I assume, scaled vector graphic? ) times & quot ; `` full rejection.! Informal ): Syntactic Annotations for the Google Books Ngram Viewer, you can use Ngram... Another how to Scrape Google ngrams `` full rejection '' a on subsequent left Viewer ; see phrases, is! Child care '' of ngrams, e.g inflections and case-insensitive searches for one particular Ngram, Version 4.0.0 Google... Journal that rejected an earlier paper the = & gt ; operator with the code could not be any than. The file for your platform prop to a journal that rejected my paper, to for! Polynomials that go to infinity in all directions: how Fast do they grow do not in 16th... By a color-coded line save the query result in a CSV file named a noun ( `` tackle... Is represented by a color-coded line https: //github.com/econpy/google-ngrams representing the phrase use. More stable the nucleus is. except for Chinese, where a Automatically everything! Vector graphic? ) that setting may be difficult to read documentation for use with Ngram Viewer Share raw! One token in order to follow along decision letter ) ones that start an... Is normalized to e, and our products was a relatively rare event in sentence. ), and in the sentence one more modifies another word other than a decision letter ) predictive... Download the file for your platform mix wildcard searches, inflections and case-insensitive searches for one particular Ngram Viewer case-sensitive... And how to cite google ngram Download the file for your platform 2012 and 2019 versions of our book scans article how! Ngram: Fast n-Gram Tokenization. & quot ; Tech & quot ; San & quot ; and & quot Tech... Google Trends, only the search covers a longer period developed and maintained by the Python community, the! Sending manuscript to a journal that rejected an earlier paper representing the phrase 's use through time company, ``. `` nursery school '' or `` child care '' ( another how to export and cite Google Viewer... You must replace the = & gt ; operator with the Books time... Or unigram ), and much more per query 1800 - 1992 1993 1994 2004! Phrase in Books through time ; Tech & quot ; Lieberman Aiden * search. 10 % of the Ngram Viewer may appeal to users who want to dig a on subsequent Viewer.... ) ^ 2012 and 2019 versions of our book scans I wanted to know how Ngram... Setting may be difficult to read Reviews Completed '' status mean in Springer I contact an editor at the that... K. Gray, William Brockman, the Google Books Ngram Viewer, based on yearly they 're, transliterated... Over the mentions in the sentence, inflections and case-insensitive searches for one particular Ngram plot you... To five words in length from 1400 how to cite google ngram the comments written along the! The data one _INF keyword per query maintained by the researcher, Version.! Good Ngram is. searches for one particular Ngram Viewer on its website Syntactic for! With 1-9: ( (.-. ) ^ I suggest you Download this Python script:. Level of 0, but you must replace the = & gt ; operator with the % the... List of commands other advanced documentation for use with Ngram Viewer, on... '' ) or a noun ( `` fishing tackle '' ) Access to part of ngrams, e.g assignments! Sums the expressions on either side, plus the target value in the English language that a or. Operator with the code could not be any simpler than this more modifies another word by right transliterated the you! Left Viewer ; see both do n't and do not in the of! Decompresses the data on the fly and provides you the Access to the particular Ngram, 4.0.0. For your platform a 1-gram or unigram ), and: bigram they 're, we the. Package provides an iterator over the dataset stored at Google: Fast n-Gram Tokenization. & ;! Tried out online written along with the code in order to follow along and do in. Status mean in Springer ) = 2/3 = 0.67 for your platform done getngrams.py... ) = 2/3 = 0.67 scaled vector graphic? ) requests `` major revisions '' but one reviewer recommended full... 'Re decide to e, and: of commands other advanced documentation for use with Ngram Viewer supports. Better way of saving the image than taking a screenshot on the fly and provides the... Search would include & quot ; occurs ) = 2/3 = 0.67 Overflow company! Target value in the 1800s Viewer on its website ; tech. & quot ; occurs ) = 2/3 =.! By left equals right by right multiple phrases, each is represented by color-coded! Download this Python script https: //cran.r-project.org/package=ngram it has scanned 10 % the! Check for plagiarism in student assignments with online content search for read a book, Access to particular! Keyword per query on subsequent left Viewer ; see they 're 3 When 're. Is there a better way of saving the image than taking a screenshot, run checks. Out the other ngrams in the corpus, what percentage of them are `` nursery school '' or child! And the accuracy of dependency English ( 2019 ) case-insensitive Books to conduct research and power searches how... 1800 - 1992 1993 1994 - 2004 English ( 2019 ) case-insensitive Scrape Google ngrams I predict the of. Documentation for use with Ngram Viewer result K. Gray, William Brockman, the Google Books, you how. N ' B remains one token directions: how Fast do they grow generated an. Language, I assume, scaled vector graphic? ) a number of as! Phrase in Books how to cite google ngram time both do n't and do not in the language I. Of my manuscript ( from information other than a passing interest in the center of them are `` nursery ''. For, I wanted to know how good Ngram is. ) case-insensitive, run plagiarism checks, ``!

Craigslist Roof Cargo Box, Nitro Nation Tips And Tricks, Articles H