{ "source_file": "0930", "source_platform": "Medium", "author": "Cai Parry-Jones", "title_listed": "Advanced Techniques in Lying using Data Visualizations", "keywords": "", "domain": "数据处理", "content_type": "深度技术解析", "is_paid_flag": "否", "url": "https://towardsdatascience.com/advanced-techniques-in-lying-using-data-visualizations-794278c09844/", "publish_date": "2024-10-04", "corpus_stage": "", "notes": "", "id": "c33131c1e7f1", "collected_at": "2026-10-02T05:23:51", "title": "Advanced Techniques in Lying using Data Visualizations | Towards Data Science", "body_markdown": "![Revisit consent button](../images/body-df29beacd7496220cc94.svg)\nWe value your privacy\nWe use cookies to enhance your browsing experience, serve personalised ads or content, and analyse our traffic. By clicking \"Accept All\", you consent to our use of cookies.\nCustomise Reject All Accept All\nCustomise Consent Preferences ![](../images/body-2159bb67f3de8ad870eb.svg)\nWe use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.\nThe cookies that are categorised as \"Necessary\" are stored on your browser as they are essential for enabling the basic functionalities of the site. ... Show more\nNecessaryAlways Active\nNecessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.\n * Cookie\nBCTempID\n * Duration\n10 minutes\n * Description\nNo description available.\n\n\n * Cookie\n__cf_bm\n * Duration\n1 hour\n * Description\nThis cookie, set by Cloudflare, is used to support Cloudflare Bot Management. \n\n\n * Cookie\nAWSALBCORS\n * Duration\n7 days\n * Description\nAmazon Web Services set this cookie for load balancing.\n\n\n * Cookie\n_cfuvid\n * Duration\nsession\n * Description\nCloudflare sets this cookie to track users across sessions to optimize user experience by maintaining session consistency and providing personalized services\n\n\n * Cookie\nli_gc\n * Duration\n6 months\n * Description\nLinkedin set this cookie for storing visitor's consent regarding using cookies for non-essential purposes.\n\n\n * Cookie\n__hssrc\n * Duration\nsession\n * Description\nThis cookie is set by Hubspot whenever it changes the session cookie. The __hssrc cookie set to 1 indicates that the user has restarted the browser, and if the cookie does not exist, it is assumed to be a new session.\n\n\n * Cookie\n__hssc\n * Duration\n1 hour\n * Description\nHubSpot sets this cookie to keep track of sessions and to determine if HubSpot should increment the session number and timestamps in the __hstc cookie.\n\n\n * Cookie\nwpEmojiSettingsSupports\n * Duration\nsession\n * Description\nWordPress sets this cookie when a user interacts with emojis on a WordPress site. It helps determine if the user's browser can display emojis properly.\n\n\n * Cookie\nBCSessionID\n * Duration\n1 year 1 month 4 days\n * Description\nBlueconic sets this cookie as a unique identifier for the BlueConic profile.\n\n\n * Cookie\n_octo\n * Duration\n1 year\n * Description\nNo description available.\n\n\n * Cookie\nlogged_in\n * Duration\n1 year\n * Description\nNo description available.\n\n\n * Cookie\n__Secure-YEC\n * Duration\npast\n * Description\nYouTube sets this cookie to stores the user's video player preferences using embedded YouTube video\n\n\n * Cookie\n__eoi\n * Duration\n6 months\n * Description\nDescription is currently not available.\n\n\n * Cookie\nAWSALBTGCORS\n * Duration\n7 days\n * Description\nNo description available.\n\n\n * Cookie\nlogin-status-p\n * Duration\npast\n * Description\nDescription is currently not available.\n\n\n * Cookie\nAWSALBTG\n * Duration\n7 days\n * Description\nNo description available.\n\n\n * Cookie\ncsrf_token\n * Duration\nsession\n * Description\nNo description available.\n\n\n * Cookie\ntoken_v2\n * Duration\n1 day\n * Description\nDescription is currently not available.\n\n\n * Cookie\nD\n * Duration\n1 year\n * Description\nDescription is currently not available.\n\n\n * Cookie\nPHPSESSID\n * Duration\nsession\n * Description\nThis cookie is native to PHP applications. The cookie stores and identifies a user's unique session ID to manage user sessions on the website. The cookie is a session cookie and will be deleted when all the browser windows are closed.\n\n\n * Cookie\nVISITOR_PRIVACY_METADATA\n * Duration\n6 months\n * Description\nYouTube sets this cookie to store the user's cookie consent state for the current domain. \n\n\n * Cookie\ncookietest\n * Duration\nsession\n * Description\nThe cookietest cookie is typically used to determine whether the user's browser accepts cookies, essential for website functionality and user experience.\n\n\n * Cookie\n__Host-airtable-session\n * Duration\n1 year\n * Description\nThis cookie is used to enable us to integrate the services of Airtable.\n\n\n * Cookie\n__Host-airtable-session.sig\n * Duration\n1 year\n * Description\nThis cookie is used to enable us to integrate the services of Airtable.\n\n\n * Cookie\nm\n * Duration\n1 year 1 month 4 days\n * Description\nStripe sets this cookie for fraud prevention purposes. It identifies the device used to access the website, allowing the website to be formatted accordingly.\n\n\n * Cookie\nBIGipServer*\n * Duration\nsession\n * Description\nMarketo sets this cookie to collect information about the user's online activity and build a profile about their interests to provide advertisements relevant to the user. \n\n\n * Cookie\n__cfruid\n * Duration\nsession\n * Description\nCloudflare sets this cookie to identify trusted web traffic.\n\n\n * Cookie\n_GRECAPTCHA\n * Duration\n6 months\n * Description\nGoogle Recaptcha service sets this cookie to identify bots to protect the website against malicious spam attacks.\n\n\n * Cookie\n__Secure-YNID\n * Duration\n6 months\n * Description\nGoogle cookie used to protect user security and prevent fraud, especially during the login process.\n\n\n * Cookie\ncookieyes-consent\n * Duration\n1 year\n * Description\nCookieYes sets this cookie to remember users' consent preferences so that their preferences are respected on subsequent visits to this site. It does not collect or store any personal information about the site visitors.\n\n\nFunctional\nFunctional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.\n * Cookie\nlidc\n * Duration\n1 day\n * Description\nLinkedIn sets the lidc cookie to facilitate data center selection.\n\n\n * Cookie\nbrw\n * Duration\n1 year\n * Description\nNo description available.\n\n\n * Cookie\nbrwConsent\n * Duration\n5 minutes\n * Description\nDescription is currently not available.\n\n\n * Cookie\nWMF-Uniq\n * Duration\n1 year\n * Description\nDescription is currently not available.\n\n\n * Cookie\nloom_anon_comment\n * Duration\n1 year\n * Description\nNo description available.\n\n\n * Cookie\nloom_referral_video\n * Duration\nsession\n * Description\nDescription is currently not available.\n\n\n * Cookie\nVISITOR_INFO1_LIVE\n * Duration\n6 months\n * Description\nA cookie set by YouTube to measure bandwidth that determines whether the user gets the new or old player interface.\n\n\n * Cookie\nyt-remote-connected-devices\n * Duration\nNever Expires\n * Description\nYouTube sets this cookie to store the user's video preferences using embedded YouTube videos.\n\n\n * Cookie\nytidb::LAST_RESULT_ENTRY_KEY\n * Duration\nNever Expires\n * Description\nThe cookie ytidb::LAST_RESULT_ENTRY_KEY is used by YouTube to store the last search result entry that was clicked by the user. This information is used to improve the user experience by providing more relevant search results in the future.\n\n\n * Cookie\nyt-remote-device-id\n * Duration\nNever Expires\n * Description\nYouTube sets this cookie to store the user's video preferences using embedded YouTube videos.\n\n\n * Cookie\nyt-remote-session-name\n * Duration\nsession\n * Description\nThe yt-remote-session-name cookie is used by YouTube to store the user's video player preferences using embedded YouTube video.\n\n\n * Cookie\nyt-remote-fast-check-period\n * Duration\nsession\n * Description\nThe yt-remote-fast-check-period cookie is used by YouTube to store the user's video player preferences for embedded YouTube videos.\n\n\n * Cookie\nyt-remote-session-app\n * Duration\nsession\n * Description\nThe yt-remote-session-app cookie is used by YouTube to store user preferences and information about the interface of the embedded YouTube video player.\n\n\n * Cookie\nyt-remote-cast-available\n * Duration\nsession\n * Description\nThe yt-remote-cast-available cookie is used to store the user's preferences regarding whether casting is available on their YouTube video player.\n\n\n * Cookie\nyt-remote-cast-installed\n * Duration\nsession\n * Description\nThe yt-remote-cast-installed cookie is used to store the user's video player preferences using embedded YouTube video.\n\n\n * Cookie\ncp_session\n * Duration\n3 months\n * Description\nCodepen sets this cookie for Help systems found in the website.\n\n\n * Cookie\nloid\n * Duration\n1 year 1 month 4 days\n * Description\nThis cookie is set by the Reddit. The cookie enables the sharing of content from the website onto the social media platform.\n\n\nAnalytics\nAnalytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.\n * Cookie\n__hstc\n * Duration\n6 months\n * Description\nHubspot set this main cookie for tracking visitors. It contains the domain, initial timestamp (first visit), last timestamp (last visit), current timestamp (this visit), and session number (increments for each subsequent session).\n\n\n * Cookie\nhubspotutk\n * Duration\n6 months\n * Description\nHubSpot sets this cookie to keep track of the visitors to the website. This cookie is passed to HubSpot on form submission and used when deduplicating contacts.\n\n\n * Cookie\n_ga\n * Duration\n1 year 1 month 4 days\n * Description\nGoogle Analytics sets this cookie to calculate visitor, session and campaign data and track site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognise unique visitors.\n\n\n * Cookie\n_ga_*\n * Duration\n1 year 1 month 4 days\n * Description\nGoogle Analytics sets this cookie to store and count page views.\n\n\n * Cookie\n__Host-psifi.analyticsTrace\n * Duration\n6 hours\n * Description\nDescription is currently not available.\n\n\n * Cookie\n__Host-psifi.analyticsTraceV2\n * Duration\n6 hours\n * Description\nDescription is currently not available.\n\n\n * Cookie\n_gh_sess\n * Duration\nsession\n * Description\nGitHub sets this cookie for temporary application and framework state between pages like what step the user is on in a multiple step form.\n\n\n * Cookie\nYSC\n * Duration\nsession\n * Description\nYSC cookie is set by Youtube and is used to track the views of embedded videos on Youtube pages.\n\n\n * Cookie\najs_anonymous_id\n * Duration\n1 year\n * Description\nThis cookie is set by Segment to count the number of people who visit a certain site by tracking if they have visited before.\n\n\n * Cookie\nvuid\n * Duration\n1 year 1 month 4 days\n * Description\nVimeo installs this cookie to collect tracking information by setting a unique ID to embed videos on the website. \n\n\nPerformance\nPerformance cookies are used to understand and analyse the key performance indexes of the website which helps in delivering a better user experience for the visitors.\n * Cookie\nAWSALB\n * Duration\n7 days\n * Description\nAWSALB is an application load balancer cookie set by Amazon Web Services to map the session to the target.\n\n\n * Cookie\nacq\n * Duration\npast\n * Description\nDescription is currently not available.\n\n\n * Cookie\nacq.sig\n * Duration\npast\n * Description\nDescription is currently not available.\n\n\n * Cookie\nptc\n * Duration\n2 years\n * Description\nNo description available.\n\n\nAdvertisement\nAdvertisement cookies are used to provide visitors with customised advertisements based on the pages you visited previously and to analyse the effectiveness of the ad campaigns.\n * Cookie\nmuc_ads\n * Duration\n1 year 1 month 4 days\n * Description\nTwitter sets this cookie to collect user behaviour and interaction data to optimize the website.\n\n\n * Cookie\nguest_id_marketing\n * Duration\n1 year 1 month 4 days\n * Description\nTwitter sets this cookie to identify and track the website visitor.\n\n\n * Cookie\nguest_id_ads\n * Duration\n1 year 1 month 4 days\n * Description\nTwitter sets this cookie to identify and track the website visitor.\n\n\n * Cookie\npersonalization_id\n * Duration\n1 year 1 month 4 days\n * Description\nTwitter sets this cookie to integrate and share features for social media and also store information about how the user uses the website, for tracking and targeting.\n\n\n * Cookie\nguest_id\n * Duration\n1 year 1 month 4 days\n * Description\nTwitter sets this cookie to identify and track the website visitor. It registers if a user is signed in to the Twitter platform and collects information about ad preferences.\n\n\n * Cookie\nbcookie\n * Duration\n1 year\n * Description\nLinkedIn sets this cookie from LinkedIn share buttons and ad tags to recognize browser IDs.\n\n\n * Cookie\n__Secure-ROLLOUT_TOKEN\n * Duration\n6 months\n * Description\nYouTube sets this cookie to manage feature rollout and experimentation. It helps Google control which new features or interface changes are shown to users as part of testing and staged rollouts, ensuring consistent experience for a given user during an experiment.\n\n\n * Cookie\nyt.innertube::nextId\n * Duration\nNever Expires\n * Description\nYouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen.\n\n\n * Cookie\nyt.innertube::requests\n * Duration\nNever Expires\n * Description\nYouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen.\n\n\n * Cookie\nsession_tracker\n * Duration\nsession\n * Description\nThis cookie is set by the Reddit. This cookie is used to identify trusted web traffic. It also helps in adverstising on the website.\n\n\n * Cookie\nedgebucket\n * Duration\nsession\n * Description\nReddit sets this cookie to save the information about a log-on Reddit user, for the purpose of advertisement recommendations and updating the content.\n\n\n * Cookie\ndid\n * Duration\n1 year\n * Description\nArbor sets this cookie to show targeted ads to site visitors.This cookie expires after 2 months or 1 year.\n\n\nUncategorised\nOther uncategorised cookies are those that are being analysed and have not been classified into a category as yet.\nNo cookies to display.\nReject All Save My Preferences Accept All\nToggle Search[](https://towardsdatascience.com/)Toggle Mobile Navigation\n[](https://towardsdatascience.com/)\nPublish AI, ML & data-science insights to a global community of data professionals.\nSign in[Submit an Article](https://write.insightmediagroup.io)\n[Latest](https://towardsdatascience.com/latest/)[Editor's Picks](https://towardsdatascience.com/tag/editors-pick/)[Newsletter](https://towardsdatascience.com/tag/the-variable/)[ShipAI](https://towardsdatascience.com/shipai/)\n* * *\n[Write For TDS](https://towardsdatascience.com/submissions/)\n[LinkedIn](https://www.linkedin.com/company/towards-data-science/)[X](https://x.com/TDataScience)Toggle Search\n[Misinformation](https://towardsdatascience.com/category/misinformation/)\n# Advanced Techniques in Lying using Data Visualizations\nDiscover the power of chart design to manipulate an audience, whatever the narrative\n[Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\nOctober 4, 20249 min read\n# Advanced Techniques in Lying Using Data Visualizations\n### Discover the power of chart design to manipulate an audience towards any narrative\n![source: unsplash.com](../images/000.jpg)\nsource: [unsplash.com](https://unsplash.com/)\n _This article is satire. Using bogus visualizations to spread misinformation is not cool. The purpose of this article is to teach you how to spot misinformation._\nDo you have a narrative you need to sell? Perhaps you've predicted something at work, which you now need to prove. Maybe someone on X said your political opinion was wrong, so you need ammunition for a counter-attack.\nData visualizations are often the final layer in data analysis, used for presenting insights quickly and easily. The audience can vary, from board members to TV viewers to government officials to social media followers. However, despite their differences, they often have a few things in common. They're usually not a data technical professional, and they usually don't have time to delve into the details. This makes data visualizations the perfect tool for manipulating your audience, whatever the data, whatever your narrative.\nLearn this step by step with the interactive [Data Analyst](https://roadmap.sh/data-analyst) roadmap.\nUsing real-world examples, this article delves into four advanced techniques that data-savvy manipulators use to get their own message across, regardless of what the raw data actually says. These are:\n 1. Omit unwanted data points\n 2. Exploit pattern psychology\n 3. Selectively categorize data\n 4. Strategically adjust readability\n\n\nBy the end of this article your tool bag will be fully equipped to spread misinformation in its most potent form, statistics.\n## TL;DR\n * Selectively removing or shuffling data around is often powerful enough to support contradictory narratives.\n * For audiences that don't have time to critically analyze the data, using simple psychological patterns, such as red = bad, green = good, can be enough to sway them.\n * The only way to stop manipulative data techniques is to call it out when you see it.\n\n\n## Omitting unwanted data points\nIf you're into healthy living, you will likely be aware of the best selling book \"[Why We Sleep](https://www.amazon.co.uk/Why-We-Sleep-Science-Dreams/dp/0141983760)\" by Matthew Walker. Health books didn't just casually fall into no.1 place on the Sunday Times Bestseller list. So, how did \"Why We Sleep\" achieve such a remarkable feat? If you've read the book, like I did, you will know exactly why. It is a powerful, bordering on frightening, piece of non-fiction with the central message: **if you don't take your sleep seriously, you will suffer a world of health issues**.\nIt's not just the message that's powerful. The book contains an abundance of academic research and data analysis, all of which unequivocally supports the narrative. By the end of the book, there is no doubt about it - the message is true, and we, the enlightened few, then go out to tell everyone else they should read it too. The end result for the publisher is 10s of millions of dollars in revenue. I'm sure Penguin gave Matthew Walker a big pat on the back, and a few million for himself, naturally.\nWhat Matthew Walker did brilliantly to ensure a faultless narrative was, of course, omit unwanted data. There is no mention of research that goes against the idea that less sleep doesn't make a difference, or could even be good for you. But, what is truly impressive is that there are no unwanted data points for analyses that are actually used in the book!\nFor example, on discussing the likelihood of injury in sports vs average sleep duration, a chart is shown, on page 129 of the book, presenting the results of a [research](https://journals.lww.com/pedorthopaedics/fulltext/2014/03000/chronic_lack_of_sleep_is_associated_with_increased.1.aspx) paper. In it we have 4 four data points, 6hr = 72%, 7hr = 60%, 8hr = 34%, 9hr = 18%. The underlying data that built this chart comes from research published in the Journal of Paediatric Orthopaedics, titled \"Chronic lack of sleep is associated with increased sports injuries in adolescent athletes\". The paper's data is exactly the same, except for the fact that there is an additional data point. It has data for athletes with five hours average sleep, which had an injury risk of 54%.\nWhy might this data point have been omitted from Matthew Walker's chart? It's in a peer reviewed journal, so it's not as if the five hours data point isn't usable data. Of course, the answer is that it goes against the narrative. It's much better to have a chart that goes from lowest sleep = worst to most sleep = best. Next time, when you have a pesky data point or two, remember, you can just remove it. If it's acceptable enough for a Penguin published book by an author who is a UC Berkeley professor, then it's acceptable enough for us.\n![Created by the author using Google Sheets.](../images/001.png)\nCreated by the author using Google Sheets.\n## Exploit pattern psychology\nThis may seem a little less obvious than the first technique, but it's actually quite simple. It is about being aware of how people instinctively feel about seeing things on charts, and taking advantage of that for your benefit. Common perceptive patterns are:\n * Green = good\n * Red = bad\n * Sharp rise = significant\n * Big = significant\n * Correlation = causation\n\n\nFox News are great at this [sort of stuff](https://www.researchgate.net/figure/The-original-Fox-News-bar-chart-cropping-y-axis-and-omitting-labels-Source_fig2_329075050). However, depending on your audience's ability to critically assess your work, you may need to adjust how much you take advantage of this technique.\n![Created by the author using Google Sheets.](../images/002.png)\nCreated by the author using Google Sheets.\nAbove uses the popular trick of starting the Y-axis at greater than zero. The effect is a much sharper difference between data points, which translates to a feeling of significance. Of course, if the direction between data points goes against your narrative, you will want to set the Y-axis as low as possible, as to convey a feeling of insignificance in difference.\nAnother way of presenting the data to suit your agenda is using colors. For most people, the color red is associated with something bad. Presenting a chart with a wall of red can be very effective in providing a sense of fear, crisis, alarm etc. to the audience. Climate change is a particularly great topic to use red as it's also used to symbolize heat and fire.\nA chart by The Guardian in the article \"[What's happening with the climate crisis and heat-trapping emissions in Australia](https://www.theguardian.com/environment/datablog/ng-interactive/2022/oct/03/tracking-australias-progress-on-the-climate-crisis-and-the-consequences-of-global-heating)\" perfectly executes the use of red.\n!['World on fire' version of chart. Created by the author using Tableau. Data source: Global Carbon Budget, 2022](../images/003.png)\n'World on fire' version of chart. Created by the author using Tableau. Data source: Global Carbon Budget, 2022\nNotice how every country on the map is red, even countries that produce zero fossil fuel emissions would be highlighted in a pinky red. Using the exact same data, without a full red color scale, produces a chart with a much less fearful punch to it, such as the one below:\n!['Only parts of the world on fire' version of chart. Created by the author using Tableau. Data source: Global Carbon Budget, 2022](../images/004.png)\n'Only parts of the world on fire' version of chart. Created by the author using Tableau. Data source: Global Carbon Budget, 2022\n## Be selective in categorizing\nThis technique is somewhat similar to omitting data. However, it isn't quite the same. Omitting data is simply removing the unwanted data from view, selective categorization is about shuffling data around until we find an adequate story. It is also less susceptible to criticism, and as such is most commonly used in areas where there is an attempt at critically assessing the analysis, such as published papers in peer-reviewed journals.\nI'll start with a simple toy example to explain what I mean by shuffling data around. Say I am studying the number of people who live in each household of a village. I have collected the following raw data:\n![](../images/body-c8fce57142d8b02eeda2.png)\nIf I want to convey the message that the village has many overcrowded households, then I can present the data like so:\n![Created by the author using Google Sheets.](../images/005.png)\nCreated by the author using Google Sheets.\nAll I have done is bundle 5,6,7, and 8 together to create one single data point, 5+. The final result is a chart with the biggest people per household category appearing the largest. Perfect for my narrative.\nBut, what if I don't want that. In fact, what if I want to convey the exact opposite message. I can shuffle the data around a bit, and end up presenting the data like so:\n![Created by the author using Google Sheets.](../images/006.png)\nCreated by the author using Google Sheets.\nHere, what I have done is bundle 0, 1, and 2 together, 3, 4, and 5 together, and 6, 7, and 8 together. As you can see, without even omitting a single point of raw data, I have completely changed the story.\nThis technique was brilliantly implemented in an academic research [paper](https://www.jstor.org/stable/10.1086/467988?seq=34) focusing on whether more guns reduce or increase crime. A highly cited paper by John Lott and David Mustard titled, \"Crime, Deterrence, and Right‐to‐Carry Concealed Handguns\" provides a remarkable chart of the consequences of implementing handgun concealment laws designed to increase the number of guns on the street.\n![source: "Crime, Deterrence, and Right‐to‐Carry Concealed Handguns" by John Lott and David Mustard](../images/007.png)\nsource: [\"Crime, Deterrence, and Right‐to‐Carry Concealed Handguns\"](https://www.jstor.org/stable/10.1086/467988?seq=34) by John Lott and David Mustard\nTake another second to really look at what this chart is saying, because it is quite remarkable. It would suggest that violent crimes are almost universally due to the lack of concealed handguns, as evident by the lack of variance i.e. the crime rate smoothly declines post introduction of handgun laws. So, how did the authors achieve such a remarkable chart?\nFirstly, it takes advantage of technique number two, exploit pattern psychology, by starting the Y-axis at greater than zero. Secondly, and most influentially, it has selectively chosen what is and isn't considered as a 'violent crime', 'concealed handgun law', and the 'population' of the study. For example, in the violent crime category, they choose to allow robbery and aggravated assaults with a gun, but not without a gun e.g. a knife. Why? Because, robberies and aggravated assaults on average increased post adoption of handgun laws, which goes against the narrative. But taking a small slice of this violent crime i.e. robberies and aggravated assaults with a gun, the average conveniently decreased post adoption of handgun laws.\nSimilarly, some regions and years were excluded from the population sample. These regions and years had huge spikes in violent crimes post concealed handgun law adoption. The reason the authors gave for removing these populations was due to 'higher drug prices' (I'm not making this up, page 24 \"[Crime, Deterrence, and Right‐to‐Carry Concealed Handguns](https://www.jstor.org/stable/10.1086/467988?seq=34)\").\nRepeat this sort of selective categorization a few more times, and voila - the perfect chart!\n## Strategically adjust readability\nIf, sadly, you can't avoid publishing some unsightly data in your charts, there is one final technique you can use to maintain your narrative. Make the charts unbearable to look at. A classic is to present the data as a cold hard table. For example:\n![Created by the author using Microsoft Word](../images/008.jpeg)\nCreated by the author using Microsoft Word\nDid you read it all? If so you're a stronger person than I am. I'll be honest with you, I have no idea if this data is trying to manipulate me or not, all I know is I don't want to read that ugly table, and you can't make me!\nIf you do have some good data sprinkled around the nasty narrative-killing data, then do your best to make the good stuff as readable as possible. Nice simple line or bar charts will do. And, of course, make sure all the bad data gets the table treatment.\n## Conclusion\n**A message to data scientists, business analysts, academic researchers, and everyone else involved in presenting data** : Manipulating your audience can be easy, but it's not cool. It is important to make a deliberate effort to consider whether your work uses any of these four techniques. It may not have been intentional, but confirmation bias, as well as pressure from others, does cause manipulative data tricks to slip into one's work.\n**A message to data consumers (** basically, everyone**)** : I hope this article has empowered you to critically evaluate the data and statistics you encounter. Furthermore, I encourage readers to be vocal about any poor data ethical discoveries you may find. Whether it is via verbal discussion, a social media post, blog, video essay, note in the comment section... the list goes on, please don't be shy from criticising it when you see it.\nIf you'd like more of my insights on uncovering data issues, I encourage you to read my previous article, [Stop being data driven](https://medium.com/towards-data-science/stop-being-data-driven-583b5e7abe7b), as well as following me on [Medium](https://medium.com/@caiparryjones96) for future articles. If you'd like to spread the reach of this article, please give it a clap (or 50 😏 ) and share on social media. Thanks for reading. Until next time, peace out data champs! ✌️\n## Register Now to Continue Reading\n### Unlock Towards Data Science with a Free Account\nAll articles on Towards Data Science are available to registered users. Create a free account today to access this article and thousands more.\nRegister for freeSign in to your account\n* * *\n![](../images/body-be9b2abe4d1a1929d9b6.jpeg)\nWritten By\n## [Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\n[See all from Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\n[Charts](https://towardsdatascience.com/tag/charts/)[Data Analysis](https://towardsdatascience.com/tag/data-analysis/)[Data Visualization](https://towardsdatascience.com/tag/data-visualization/)[Misinformation](https://towardsdatascience.com/tag/misinformation/)[Tips And Tricks](https://towardsdatascience.com/tag/tips-and-tricks/)\nShare This Article\n * [](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Ftowardsdatascience.com%2Fadvanced-techniques-in-lying-using-data-visualizations-794278c09844%2F&title=Advanced%20Techniques%20in%20Lying%20using%20Data%20Visualizations)\n * [](https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Ftowardsdatascience.com%2Fadvanced-techniques-in-lying-using-data-visualizations-794278c09844%2F&title=Advanced%20Techniques%20in%20Lying%20using%20Data%20Visualizations)\n * [](https://x.com/share?url=https%3A%2F%2Ftowardsdatascience.com%2Fadvanced-techniques-in-lying-using-data-visualizations-794278c09844%2F&text=Advanced%20Techniques%20in%20Lying%20using%20Data%20Visualizations)\n\n\nTowards Data Science is a community publication. Submit your insights to reach our global audience and earn through the TDS Author Payment Program.\n[Write for TDS](https://towardsdatascience.com/submissions/)\n## Related Articles\n * [![](../images/body-63beb50f664a055ed739.jpg)](https://towardsdatascience.com/build-your-own-synthetic-data-15d91389a37b/)\n## [Build Your Own Synthetic Data](https://towardsdatascience.com/build-your-own-synthetic-data-15d91389a37b/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nGo from Nothing to a Complete Dataframe with Python\n[Kurt Klingensmith](https://towardsdatascience.com/author/kurt.klingensmith/)\nFebruary 7, 20248 min read\n * [![](../images/010.gif)](https://towardsdatascience.com/minimum-viable-streaming-dashboard-in-power-bi-part-1-56e00a82c22f/)\n## [Minimum Viable Streaming Dashboard in Power BI: Part 1](https://towardsdatascience.com/minimum-viable-streaming-dashboard-in-power-bi-part-1-56e00a82c22f/)\n[Data Visualization](https://towardsdatascience.com/category/data-science/data-visualization/)\nA two-part series on developing real-time streaming dashboards and their use cases.\n[Nathan Cheng](https://towardsdatascience.com/author/natworkeffects/)\nJanuary 31, 20218 min read\n * [![](../images/011.jpeg)](https://towardsdatascience.com/8-must-know-data-visualizations-for-better-data-analysis-9752953dd703/)\n## [8 Must-Know Data Visualizations for Better Data Analysis](https://towardsdatascience.com/8-must-know-data-visualizations-for-better-data-analysis-9752953dd703/)\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\nExplained with examples using Seaborn\n[Soner Yıldırım](https://towardsdatascience.com/author/sonery/)\nNovember 21, 20206 min read\n * [![](../images/012.png)](https://towardsdatascience.com/how-to-make-cyberpunk-dark-mode-data-visualizations-in-python-b28f82386e75/)\n## [How to Make Cyberpunk \"Dark Mode\" Data Visualizations in Python](https://towardsdatascience.com/how-to-make-cyberpunk-dark-mode-data-visualizations-in-python-b28f82386e75/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nNeon Lines and Dark Designs, An Introduction\n[Mia Dwyer](https://towardsdatascience.com/author/mia_dwyer/)\nApril 8, 20243 min read\n * [![](../images/013.jpg)](https://towardsdatascience.com/from-pixels-to-plots/)\n## [From Pixels to Plots](https://towardsdatascience.com/from-pixels-to-plots/)\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\nHow I built an AI-powered prototype to turn images into insights\n[Jens Winkelmann](https://towardsdatascience.com/author/jens.winkelmann/)\nJune 30, 202514 min read\n * [![](../images/014.png)](https://towardsdatascience.com/9-examples-to-master-seaborn-grids-1935bb38014c/)\n## [9 Examples to Master Seaborn Grids](https://towardsdatascience.com/9-examples-to-master-seaborn-grids-1935bb38014c/)\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\nPractical guide for FacetGrid and PairGrid\n[Soner Yıldırım](https://towardsdatascience.com/author/sonery/)\nJanuary 2, 20215 min read\n * [![](../images/015.jpeg)](https://towardsdatascience.com/do-all-russians-love-their-jobs-how-work-enjoyment-changes-how-much-you-value-your-time-4daca4e7ba19/)\n## [Do All Russians Love Their Jobs? 🧐 How Work Enjoyment Changes How Much You Value Your Time.](https://towardsdatascience.com/do-all-russians-love-their-jobs-how-work-enjoyment-changes-how-much-you-value-your-time-4daca4e7ba19/)\n[Data Visualization](https://towardsdatascience.com/category/data-science/data-visualization/)\nData Analysis, Stats & Visualisation of 13k+ responses to the Value of Time Calculator\n[Marta](https://towardsdatascience.com/author/krzem-m/)\nJanuary 10, 20215 min read\n * [![](../images/016.png)](https://towardsdatascience.com/visualizing-satellite-data-using-matplotlib-and-cartopy-8274acb07b84/)\n## [Visualizing Satellite Data Using Matplotlib and Cartopy](https://towardsdatascience.com/visualizing-satellite-data-using-matplotlib-and-cartopy-8274acb07b84/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nExplore our changing climate using Python and passive microwave data\n[Will Norris](https://towardsdatascience.com/author/willmnorris/)\nJune 25, 202110 min read\n * [![](../images/017.jpeg)](https://towardsdatascience.com/can-i-form-a-dream-team-in-fifa-19-using-sql-160fd9a3f172/)\n## [Can I Form A Dream Team in FIFA 19 using SQL?](https://towardsdatascience.com/can-i-form-a-dream-team-in-fifa-19-using-sql-160fd9a3f172/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nSQL Is Powerful but Is It Powerful Enough for This Important Job?\n[Efe Buyuk](https://towardsdatascience.com/author/efebuyuk/)\nDecember 8, 20204 min read\n\n\n * [YouTube](https://www.youtube.com/c/TowardsDataScience)\n * [X](https://x.com/TDataScience)\n * [LinkedIn](https://www.linkedin.com/company/towards-data-science/)\n * [Threads](https://www.threads.net/@towardsdatascience)\n * [Bluesky](https://bsky.app/profile/towardsdatascience.com)\n\n\n[](https://towardsdatascience.com/)\nYour home for data science and AI. The world's leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.\nSubscribe to Our Newsletter[Write For TDS](https://towardsdatascience.com/submissions/)•[About](https://towardsdatascience.com/about-towards-data-science-d691af11cc2f/)•[Advertise](https://contact.towardsdatascience.com/advertise-with-towards-data-science)•[Privacy Policy](https://towardsdatascience.com/privacy-policy/)•[Terms of Use](https://towardsdatascience.com/website-terms-of-use/)\n© Insight Media Group, LLC 2026•[The New Stack](https://thenewstack.io)•[roadmap.sh](https://roadmap.sh)•[Creator Network](https://insightmediagroup.io/creator-network)\n#### Recommended Articles \nClose\n * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607686/image?etag=1782161464448&width=500&height=500) How Relevance Models Foreshadowed Transformers for NLP ](https://towardsdatascience.com/how-relevance-models-foreshadowed-transformers-for-nlp/ \"How Relevance Models Foreshadowed Transformers for NLP\")\n * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607639/image?etag=1781250125848&width=500&height=500) Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 1 ](https://towardsdatascience.com/javascript-fatigue-you-dont-need-js-to-build-chatgpt/ \"Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 1\")\n * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607930/image?etag=1782124566054&width=500&height=500) The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs ](https://towardsdatascience.com/subset-sum-problem-solved-in-linear-time-for-dense-enough-inputs/ \"The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs\")\n * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/3660/image?etag=1780176246070&width=500&height=500) Does Your Company Have a Data Strategy? ](https://towardsdatascience.com/does-your-company-have-a-data-strategy-e8944dbec4ae/ \"Does Your Company Have a Data Strategy?\")\n\n\n", "metadata": { "title": "Advanced Techniques in Lying using Data Visualizations | Towards Data Science", "description": "Discover the power of chart design to manipulate an audience, whatever the narrative", "keywords": null, "author": "Cai Parry-Jones", "og:locale": "en_US", "og:type": "article", "og:title": "Advanced Techniques in Lying using Data Visualizations", "og:description": "Discover the power of chart design to manipulate an audience, whatever the narrative", "og:url": "https://towardsdatascience.com/advanced-techniques-in-lying-using-data-visualizations-794278c09844/", "og:site_name": "Towards Data Science", "og:image": "https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/0xQN0XidSOO4w73N1-scaled.jpg", "og:image:width": "2560", "og:image:height": "1703", "og:image:type": "image/jpeg", "twitter:card": "summary_large_image", "twitter:site": "@TDataScience", "twitter:creator": "@TDataScience", "twitter:label1": "Written by", "twitter:data1": "Cai Parry-Jones", "twitter:label2": "Est. reading time", "twitter:data2": "9 min read", "article:published_time": "2024-10-04T16:50:51.000Z", "article:modified_time": "2024-10-04T16:50:51.000Z", "article:author": "https://towardsdatascience.com/author/caiparryjones96/" }, "paywall": { "listed_paid": false, "detected": false, "marker": "", "public_only": false, "policy": "付费/会员内容只保留页面公开可见部分，不绕过付费墙" }, "crawl": { "success": true, "status_code": 200, "error": "" }, "code_blocks": [], "images": [ { "status": "http_404", "url": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607686/image?etag=1782161464448&width=500&height=500", "src": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607686/image?etag=1782161464448&width=500&height=500", "alt": "", "downloaded": false, "discovery": "saved_markdown", "retried_at": "2026-10-20T18:07:57Z" }, { "status": "http_404", "url": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607639/image?etag=1781250125848&width=500&height=500", "src": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607639/image?etag=1781250125848&width=500&height=500", "alt": "", "downloaded": false, "discovery": "saved_markdown", "retried_at": "2026-10-20T18:07:57Z" }, { "status": "http_404", "url": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607930/image?etag=1782124566054&width=500&height=500", "src": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607930/image?etag=1782124566054&width=500&height=500", "alt": "", "downloaded": false, "discovery": "saved_markdown", "retried_at": "2026-10-20T18:07:57Z" }, { "status": "http_404", "url": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/3660/image?etag=1780176246070&width=500&height=500", "src": "https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/3660/image?etag=1780176246070&width=500&height=500", "alt": "", "downloaded": false, "discovery": "saved_markdown", "retried_at": "2026-10-20T18:07:57Z" } ], "audio": [], "videos": [ { "url": "https://www.youtube.com/c/TowardsDataScience", "kind": "channel_reference", "status": "reference_only" } ], "links": [ { "type": "internal", "href": "https://towardsdatascience.com/" }, { "type": "internal", "href": "https://towardsdatascience.com/latest/" }, { "type": "internal", "href": "https://towardsdatascience.com/tag/editors-pick/" }, { "type": "internal", "href": "https://towardsdatascience.com/tag/the-variable/" }, { "type": "internal", "href": "https://towardsdatascience.com/shipai/" }, { "type": "internal", "href": "https://towardsdatascience.com/submissions/" }, { "type": "internal", "href": "https://towardsdatascience.com/category/misinformation/" }, { "type": "internal", "href": "https://towardsdatascience.com/author/caiparryjones96/" }, { "type": "internal", "href": "https://towardsdatascience.com/tag/charts/" }, { "type": "internal", "href": "https://towardsdatascience.com/tag/data-analysis/" }, { "type": "internal", "href": "https://towardsdatascience.com/tag/data-visualization/" }, { "type": "internal", "href": "https://towardsdatascience.com/tag/misinformation/" }, { "type": "internal", "href": "https://towardsdatascience.com/tag/tips-and-tricks/" }, { "type": "internal", "href": "https://towardsdatascience.com/build-your-own-synthetic-data-15d91389a37b/" }, { "type": "internal", "href": "https://towardsdatascience.com/category/data-science/" }, { "type": "internal", "href": "https://towardsdatascience.com/author/kurt.klingensmith/" }, { "type": "internal", "href": "https://towardsdatascience.com/minimum-viable-streaming-dashboard-in-power-bi-part-1-56e00a82c22f/" }, { "type": "internal", "href": "https://towardsdatascience.com/category/data-science/data-visualization/" }, { "type": "internal", "href": "https://towardsdatascience.com/author/natworkeffects/" }, { "type": "internal", "href": "https://towardsdatascience.com/8-must-know-data-visualizations-for-better-data-analysis-9752953dd703/" }, { "type": "external", "href": "https://write.insightmediagroup.io" }, { "type": "external", "href": "https://www.linkedin.com/company/towards-data-science/" }, { "type": "external", "href": "https://x.com/TDataScience" }, { "type": "external", "href": "https://unsplash.com/" }, { "type": "external", "href": "https://roadmap.sh/data-analyst" }, { "type": "external", "href": "https://www.amazon.co.uk/Why-We-Sleep-Science-Dreams/dp/0141983760" }, { "type": "external", "href": "https://journals.lww.com/pedorthopaedics/fulltext/2014/03000/chronic_lack_of_sleep_is_associated_with_increased.1.aspx" }, { "type": "external", "href": "https://www.researchgate.net/figure/The-original-Fox-News-bar-chart-cropping-y-axis-and-omitting-labels-Source_fig2_329075050" }, { "type": "external", "href": "https://www.theguardian.com/environment/datablog/ng-interactive/2022/oct/03/tracking-australias-progress-on-the-climate-crisis-and-the-consequences-of-global-heating" }, { "type": "external", "href": "https://www.jstor.org/stable/10.1086/467988?seq=34" }, { "type": "external", "href": "https://medium.com/towards-data-science/stop-being-data-driven-583b5e7abe7b" }, { "type": "external", "href": "https://medium.com/@caiparryjones96" }, { "type": "external", "href": "https://www.facebook.com/sharer/sharer.php?title=Advanced+Techniques+in+Lying+using+Data+Visualizations&u=https%3A%2F%2Ftowardsdatascience.com%2Fadvanced-techniques-in-lying-using-data-visualizations-794278c09844%2F" }, { "type": "external", "href": "https://www.linkedin.com/shareArticle?mini=true&title=Advanced+Techniques+in+Lying+using+Data+Visualizations&url=https%3A%2F%2Ftowardsdatascience.com%2Fadvanced-techniques-in-lying-using-data-visualizations-794278c09844%2F" }, { "type": "external", "href": "https://x.com/share?text=Advanced+Techniques+in+Lying+using+Data+Visualizations&url=https%3A%2F%2Ftowardsdatascience.com%2Fadvanced-techniques-in-lying-using-data-visualizations-794278c09844%2F" }, { "type": "external", "href": "https://www.youtube.com/c/TowardsDataScience" }, { "type": "external", "href": "https://www.threads.net/@towardsdatascience" }, { "type": "external", "href": "https://bsky.app/profile/towardsdatascience.com" }, { "type": "external", "href": "https://thenewstack.io" }, { "type": "external", "href": "https://roadmap.sh" } ], "repair_version": 2, "repaired_at": "2026-10-20T17:33:17Z", "source_url": "https://towardsdatascience.com/advanced-techniques-in-lying-using-data-visualizations-794278c09844/", "delivery_status": "unverified", "discovery_status": "http_403", "missing_reason": "源页面未重新核验:http_403；已按保留正文补采图片", "repair_error": "", "actual_video_files": [], "expected_saved_body_images": 4, "image_discovery": "saved_markdown", "source_body_markdown": "![Revisit consent button](https://cdn-cookieyes.com/assets/images/revisit.svg)\nWe value your privacy\nWe use cookies to enhance your browsing experience, serve personalised ads or content, and analyse our traffic. By clicking \"Accept All\", you consent to our use of cookies.\nCustomise Reject All Accept All\nCustomise Consent Preferences ![](https://cdn-cookieyes.com/assets/images/close.svg)\nWe use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.\nThe cookies that are categorised as \"Necessary\" are stored on your browser as they are essential for enabling the basic functionalities of the site. ... Show more\nNecessaryAlways Active\nNecessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.\n * Cookie\nBCTempID\n * Duration\n10 minutes\n * Description\nNo description available.\n\n\n * Cookie\n__cf_bm\n * Duration\n1 hour\n * Description\nThis cookie, set by Cloudflare, is used to support Cloudflare Bot Management. \n\n\n * Cookie\nAWSALBCORS\n * Duration\n7 days\n * Description\nAmazon Web Services set this cookie for load balancing.\n\n\n * Cookie\n_cfuvid\n * Duration\nsession\n * Description\nCloudflare sets this cookie to track users across sessions to optimize user experience by maintaining session consistency and providing personalized services\n\n\n * Cookie\nli_gc\n * Duration\n6 months\n * Description\nLinkedin set this cookie for storing visitor's consent regarding using cookies for non-essential purposes.\n\n\n * Cookie\n__hssrc\n * Duration\nsession\n * Description\nThis cookie is set by Hubspot whenever it changes the session cookie. The __hssrc cookie set to 1 indicates that the user has restarted the browser, and if the cookie does not exist, it is assumed to be a new session.\n\n\n * Cookie\n__hssc\n * Duration\n1 hour\n * Description\nHubSpot sets this cookie to keep track of sessions and to determine if HubSpot should increment the session number and timestamps in the __hstc cookie.\n\n\n * Cookie\nwpEmojiSettingsSupports\n * Duration\nsession\n * Description\nWordPress sets this cookie when a user interacts with emojis on a WordPress site. It helps determine if the user's browser can display emojis properly.\n\n\n * Cookie\nBCSessionID\n * Duration\n1 year 1 month 4 days\n * Description\nBlueconic sets this cookie as a unique identifier for the BlueConic profile.\n\n\n * Cookie\n_octo\n * Duration\n1 year\n * Description\nNo description available.\n\n\n * Cookie\nlogged_in\n * Duration\n1 year\n * Description\nNo description available.\n\n\n * Cookie\n__Secure-YEC\n * Duration\npast\n * Description\nYouTube sets this cookie to stores the user's video player preferences using embedded YouTube video\n\n\n * Cookie\n__eoi\n * Duration\n6 months\n * Description\nDescription is currently not available.\n\n\n * Cookie\nAWSALBTGCORS\n * Duration\n7 days\n * Description\nNo description available.\n\n\n * Cookie\nlogin-status-p\n * Duration\npast\n * Description\nDescription is currently not available.\n\n\n * Cookie\nAWSALBTG\n * Duration\n7 days\n * Description\nNo description available.\n\n\n * Cookie\ncsrf_token\n * Duration\nsession\n * Description\nNo description available.\n\n\n * Cookie\ntoken_v2\n * Duration\n1 day\n * Description\nDescription is currently not available.\n\n\n * Cookie\nD\n * Duration\n1 year\n * Description\nDescription is currently not available.\n\n\n * Cookie\nPHPSESSID\n * Duration\nsession\n * Description\nThis cookie is native to PHP applications. The cookie stores and identifies a user's unique session ID to manage user sessions on the website. The cookie is a session cookie and will be deleted when all the browser windows are closed.\n\n\n * Cookie\nVISITOR_PRIVACY_METADATA\n * Duration\n6 months\n * Description\nYouTube sets this cookie to store the user's cookie consent state for the current domain. \n\n\n * Cookie\ncookietest\n * Duration\nsession\n * Description\nThe cookietest cookie is typically used to determine whether the user's browser accepts cookies, essential for website functionality and user experience.\n\n\n * Cookie\n__Host-airtable-session\n * Duration\n1 year\n * Description\nThis cookie is used to enable us to integrate the services of Airtable.\n\n\n * Cookie\n__Host-airtable-session.sig\n * Duration\n1 year\n * Description\nThis cookie is used to enable us to integrate the services of Airtable.\n\n\n * Cookie\nm\n * Duration\n1 year 1 month 4 days\n * Description\nStripe sets this cookie for fraud prevention purposes. It identifies the device used to access the website, allowing the website to be formatted accordingly.\n\n\n * Cookie\nBIGipServer*\n * Duration\nsession\n * Description\nMarketo sets this cookie to collect information about the user's online activity and build a profile about their interests to provide advertisements relevant to the user. \n\n\n * Cookie\n__cfruid\n * Duration\nsession\n * Description\nCloudflare sets this cookie to identify trusted web traffic.\n\n\n * Cookie\n_GRECAPTCHA\n * Duration\n6 months\n * Description\nGoogle Recaptcha service sets this cookie to identify bots to protect the website against malicious spam attacks.\n\n\n * Cookie\n__Secure-YNID\n * Duration\n6 months\n * Description\nGoogle cookie used to protect user security and prevent fraud, especially during the login process.\n\n\n * Cookie\ncookieyes-consent\n * Duration\n1 year\n * Description\nCookieYes sets this cookie to remember users' consent preferences so that their preferences are respected on subsequent visits to this site. It does not collect or store any personal information about the site visitors.\n\n\nFunctional\nFunctional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.\n * Cookie\nlidc\n * Duration\n1 day\n * Description\nLinkedIn sets the lidc cookie to facilitate data center selection.\n\n\n * Cookie\nbrw\n * Duration\n1 year\n * Description\nNo description available.\n\n\n * Cookie\nbrwConsent\n * Duration\n5 minutes\n * Description\nDescription is currently not available.\n\n\n * Cookie\nWMF-Uniq\n * Duration\n1 year\n * Description\nDescription is currently not available.\n\n\n * Cookie\nloom_anon_comment\n * Duration\n1 year\n * Description\nNo description available.\n\n\n * Cookie\nloom_referral_video\n * Duration\nsession\n * Description\nDescription is currently not available.\n\n\n * Cookie\nVISITOR_INFO1_LIVE\n * Duration\n6 months\n * Description\nA cookie set by YouTube to measure bandwidth that determines whether the user gets the new or old player interface.\n\n\n * Cookie\nyt-remote-connected-devices\n * Duration\nNever Expires\n * Description\nYouTube sets this cookie to store the user's video preferences using embedded YouTube videos.\n\n\n * Cookie\nytidb::LAST_RESULT_ENTRY_KEY\n * Duration\nNever Expires\n * Description\nThe cookie ytidb::LAST_RESULT_ENTRY_KEY is used by YouTube to store the last search result entry that was clicked by the user. This information is used to improve the user experience by providing more relevant search results in the future.\n\n\n * Cookie\nyt-remote-device-id\n * Duration\nNever Expires\n * Description\nYouTube sets this cookie to store the user's video preferences using embedded YouTube videos.\n\n\n * Cookie\nyt-remote-session-name\n * Duration\nsession\n * Description\nThe yt-remote-session-name cookie is used by YouTube to store the user's video player preferences using embedded YouTube video.\n\n\n * Cookie\nyt-remote-fast-check-period\n * Duration\nsession\n * Description\nThe yt-remote-fast-check-period cookie is used by YouTube to store the user's video player preferences for embedded YouTube videos.\n\n\n * Cookie\nyt-remote-session-app\n * Duration\nsession\n * Description\nThe yt-remote-session-app cookie is used by YouTube to store user preferences and information about the interface of the embedded YouTube video player.\n\n\n * Cookie\nyt-remote-cast-available\n * Duration\nsession\n * Description\nThe yt-remote-cast-available cookie is used to store the user's preferences regarding whether casting is available on their YouTube video player.\n\n\n * Cookie\nyt-remote-cast-installed\n * Duration\nsession\n * Description\nThe yt-remote-cast-installed cookie is used to store the user's video player preferences using embedded YouTube video.\n\n\n * Cookie\ncp_session\n * Duration\n3 months\n * Description\nCodepen sets this cookie for Help systems found in the website.\n\n\n * Cookie\nloid\n * Duration\n1 year 1 month 4 days\n * Description\nThis cookie is set by the Reddit. The cookie enables the sharing of content from the website onto the social media platform.\n\n\nAnalytics\nAnalytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.\n * Cookie\n__hstc\n * Duration\n6 months\n * Description\nHubspot set this main cookie for tracking visitors. It contains the domain, initial timestamp (first visit), last timestamp (last visit), current timestamp (this visit), and session number (increments for each subsequent session).\n\n\n * Cookie\nhubspotutk\n * Duration\n6 months\n * Description\nHubSpot sets this cookie to keep track of the visitors to the website. This cookie is passed to HubSpot on form submission and used when deduplicating contacts.\n\n\n * Cookie\n_ga\n * Duration\n1 year 1 month 4 days\n * Description\nGoogle Analytics sets this cookie to calculate visitor, session and campaign data and track site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognise unique visitors.\n\n\n * Cookie\n_ga_*\n * Duration\n1 year 1 month 4 days\n * Description\nGoogle Analytics sets this cookie to store and count page views.\n\n\n * Cookie\n__Host-psifi.analyticsTrace\n * Duration\n6 hours\n * Description\nDescription is currently not available.\n\n\n * Cookie\n__Host-psifi.analyticsTraceV2\n * Duration\n6 hours\n * Description\nDescription is currently not available.\n\n\n * Cookie\n_gh_sess\n * Duration\nsession\n * Description\nGitHub sets this cookie for temporary application and framework state between pages like what step the user is on in a multiple step form.\n\n\n * Cookie\nYSC\n * Duration\nsession\n * Description\nYSC cookie is set by Youtube and is used to track the views of embedded videos on Youtube pages.\n\n\n * Cookie\najs_anonymous_id\n * Duration\n1 year\n * Description\nThis cookie is set by Segment to count the number of people who visit a certain site by tracking if they have visited before.\n\n\n * Cookie\nvuid\n * Duration\n1 year 1 month 4 days\n * Description\nVimeo installs this cookie to collect tracking information by setting a unique ID to embed videos on the website. \n\n\nPerformance\nPerformance cookies are used to understand and analyse the key performance indexes of the website which helps in delivering a better user experience for the visitors.\n * Cookie\nAWSALB\n * Duration\n7 days\n * Description\nAWSALB is an application load balancer cookie set by Amazon Web Services to map the session to the target.\n\n\n * Cookie\nacq\n * Duration\npast\n * Description\nDescription is currently not available.\n\n\n * Cookie\nacq.sig\n * Duration\npast\n * Description\nDescription is currently not available.\n\n\n * Cookie\nptc\n * Duration\n2 years\n * Description\nNo description available.\n\n\nAdvertisement\nAdvertisement cookies are used to provide visitors with customised advertisements based on the pages you visited previously and to analyse the effectiveness of the ad campaigns.\n * Cookie\nmuc_ads\n * Duration\n1 year 1 month 4 days\n * Description\nTwitter sets this cookie to collect user behaviour and interaction data to optimize the website.\n\n\n * Cookie\nguest_id_marketing\n * Duration\n1 year 1 month 4 days\n * Description\nTwitter sets this cookie to identify and track the website visitor.\n\n\n * Cookie\nguest_id_ads\n * Duration\n1 year 1 month 4 days\n * Description\nTwitter sets this cookie to identify and track the website visitor.\n\n\n * Cookie\npersonalization_id\n * Duration\n1 year 1 month 4 days\n * Description\nTwitter sets this cookie to integrate and share features for social media and also store information about how the user uses the website, for tracking and targeting.\n\n\n * Cookie\nguest_id\n * Duration\n1 year 1 month 4 days\n * Description\nTwitter sets this cookie to identify and track the website visitor. It registers if a user is signed in to the Twitter platform and collects information about ad preferences.\n\n\n * Cookie\nbcookie\n * Duration\n1 year\n * Description\nLinkedIn sets this cookie from LinkedIn share buttons and ad tags to recognize browser IDs.\n\n\n * Cookie\n__Secure-ROLLOUT_TOKEN\n * Duration\n6 months\n * Description\nYouTube sets this cookie to manage feature rollout and experimentation. It helps Google control which new features or interface changes are shown to users as part of testing and staged rollouts, ensuring consistent experience for a given user during an experiment.\n\n\n * Cookie\nyt.innertube::nextId\n * Duration\nNever Expires\n * Description\nYouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen.\n\n\n * Cookie\nyt.innertube::requests\n * Duration\nNever Expires\n * Description\nYouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen.\n\n\n * Cookie\nsession_tracker\n * Duration\nsession\n * Description\nThis cookie is set by the Reddit. This cookie is used to identify trusted web traffic. It also helps in adverstising on the website.\n\n\n * Cookie\nedgebucket\n * Duration\nsession\n * Description\nReddit sets this cookie to save the information about a log-on Reddit user, for the purpose of advertisement recommendations and updating the content.\n\n\n * Cookie\ndid\n * Duration\n1 year\n * Description\nArbor sets this cookie to show targeted ads to site visitors.This cookie expires after 2 months or 1 year.\n\n\nUncategorised\nOther uncategorised cookies are those that are being analysed and have not been classified into a category as yet.\nNo cookies to display.\nReject All Save My Preferences Accept All\nToggle Search[](https://towardsdatascience.com/)Toggle Mobile Navigation\n[](https://towardsdatascience.com/)\nPublish AI, ML & data-science insights to a global community of data professionals.\nSign in[Submit an Article](https://write.insightmediagroup.io)\n[Latest](https://towardsdatascience.com/latest/)[Editor's Picks](https://towardsdatascience.com/tag/editors-pick/)[Newsletter](https://towardsdatascience.com/tag/the-variable/)[ShipAI](https://towardsdatascience.com/shipai/)\n* * *\n[Write For TDS](https://towardsdatascience.com/submissions/)\n[LinkedIn](https://www.linkedin.com/company/towards-data-science/)[X](https://x.com/TDataScience)Toggle Search\n[Misinformation](https://towardsdatascience.com/category/misinformation/)\n# Advanced Techniques in Lying using Data Visualizations\nDiscover the power of chart design to manipulate an audience, whatever the narrative\n[Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\nOctober 4, 20249 min read\n# Advanced Techniques in Lying Using Data Visualizations\n### Discover the power of chart design to manipulate an audience towards any narrative\n![source: unsplash.com](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/0xQN0XidSOO4w73N1-scaled.jpg)\nsource: [unsplash.com](https://unsplash.com/)\n _This article is satire. Using bogus visualizations to spread misinformation is not cool. The purpose of this article is to teach you how to spot misinformation._\nDo you have a narrative you need to sell? Perhaps you've predicted something at work, which you now need to prove. Maybe someone on X said your political opinion was wrong, so you need ammunition for a counter-attack.\nData visualizations are often the final layer in data analysis, used for presenting insights quickly and easily. The audience can vary, from board members to TV viewers to government officials to social media followers. However, despite their differences, they often have a few things in common. They're usually not a data technical professional, and they usually don't have time to delve into the details. This makes data visualizations the perfect tool for manipulating your audience, whatever the data, whatever your narrative.\nLearn this step by step with the interactive [Data Analyst](https://roadmap.sh/data-analyst) roadmap.\nUsing real-world examples, this article delves into four advanced techniques that data-savvy manipulators use to get their own message across, regardless of what the raw data actually says. These are:\n 1. Omit unwanted data points\n 2. Exploit pattern psychology\n 3. Selectively categorize data\n 4. Strategically adjust readability\n\n\nBy the end of this article your tool bag will be fully equipped to spread misinformation in its most potent form, statistics.\n## TL;DR\n * Selectively removing or shuffling data around is often powerful enough to support contradictory narratives.\n * For audiences that don't have time to critically analyze the data, using simple psychological patterns, such as red = bad, green = good, can be enough to sway them.\n * The only way to stop manipulative data techniques is to call it out when you see it.\n\n\n## Omitting unwanted data points\nIf you're into healthy living, you will likely be aware of the best selling book \"[Why We Sleep](https://www.amazon.co.uk/Why-We-Sleep-Science-Dreams/dp/0141983760)\" by Matthew Walker. Health books didn't just casually fall into no.1 place on the Sunday Times Bestseller list. So, how did \"Why We Sleep\" achieve such a remarkable feat? If you've read the book, like I did, you will know exactly why. It is a powerful, bordering on frightening, piece of non-fiction with the central message: **if you don't take your sleep seriously, you will suffer a world of health issues**.\nIt's not just the message that's powerful. The book contains an abundance of academic research and data analysis, all of which unequivocally supports the narrative. By the end of the book, there is no doubt about it - the message is true, and we, the enlightened few, then go out to tell everyone else they should read it too. The end result for the publisher is 10s of millions of dollars in revenue. I'm sure Penguin gave Matthew Walker a big pat on the back, and a few million for himself, naturally.\nWhat Matthew Walker did brilliantly to ensure a faultless narrative was, of course, omit unwanted data. There is no mention of research that goes against the idea that less sleep doesn't make a difference, or could even be good for you. But, what is truly impressive is that there are no unwanted data points for analyses that are actually used in the book!\nFor example, on discussing the likelihood of injury in sports vs average sleep duration, a chart is shown, on page 129 of the book, presenting the results of a [research](https://journals.lww.com/pedorthopaedics/fulltext/2014/03000/chronic_lack_of_sleep_is_associated_with_increased.1.aspx) paper. In it we have 4 four data points, 6hr = 72%, 7hr = 60%, 8hr = 34%, 9hr = 18%. The underlying data that built this chart comes from research published in the Journal of Paediatric Orthopaedics, titled \"Chronic lack of sleep is associated with increased sports injuries in adolescent athletes\". The paper's data is exactly the same, except for the fact that there is an additional data point. It has data for athletes with five hours average sleep, which had an injury risk of 54%.\nWhy might this data point have been omitted from Matthew Walker's chart? It's in a peer reviewed journal, so it's not as if the five hours data point isn't usable data. Of course, the answer is that it goes against the narrative. It's much better to have a chart that goes from lowest sleep = worst to most sleep = best. Next time, when you have a pesky data point or two, remember, you can just remove it. If it's acceptable enough for a Penguin published book by an author who is a UC Berkeley professor, then it's acceptable enough for us.\n![Created by the author using Google Sheets.](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/1kasmm8fzjgGxzS-kUdxujQ.png)\nCreated by the author using Google Sheets.\n## Exploit pattern psychology\nThis may seem a little less obvious than the first technique, but it's actually quite simple. It is about being aware of how people instinctively feel about seeing things on charts, and taking advantage of that for your benefit. Common perceptive patterns are:\n * Green = good\n * Red = bad\n * Sharp rise = significant\n * Big = significant\n * Correlation = causation\n\n\nFox News are great at this [sort of stuff](https://www.researchgate.net/figure/The-original-Fox-News-bar-chart-cropping-y-axis-and-omitting-labels-Source_fig2_329075050). However, depending on your audience's ability to critically assess your work, you may need to adjust how much you take advantage of this technique.\n![Created by the author using Google Sheets.](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/1iyXQ8myaKMDRp67dy0m1SA.png)\nCreated by the author using Google Sheets.\nAbove uses the popular trick of starting the Y-axis at greater than zero. The effect is a much sharper difference between data points, which translates to a feeling of significance. Of course, if the direction between data points goes against your narrative, you will want to set the Y-axis as low as possible, as to convey a feeling of insignificance in difference.\nAnother way of presenting the data to suit your agenda is using colors. For most people, the color red is associated with something bad. Presenting a chart with a wall of red can be very effective in providing a sense of fear, crisis, alarm etc. to the audience. Climate change is a particularly great topic to use red as it's also used to symbolize heat and fire.\nA chart by The Guardian in the article \"[What's happening with the climate crisis and heat-trapping emissions in Australia](https://www.theguardian.com/environment/datablog/ng-interactive/2022/oct/03/tracking-australias-progress-on-the-climate-crisis-and-the-consequences-of-global-heating)\" perfectly executes the use of red.\n!['World on fire' version of chart. Created by the author using Tableau. Data source: Global Carbon Budget, 2022](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/1U5G5mV9-pi-nQZSCGblopg.png)\n'World on fire' version of chart. Created by the author using Tableau. Data source: Global Carbon Budget, 2022\nNotice how every country on the map is red, even countries that produce zero fossil fuel emissions would be highlighted in a pinky red. Using the exact same data, without a full red color scale, produces a chart with a much less fearful punch to it, such as the one below:\n!['Only parts of the world on fire' version of chart. Created by the author using Tableau. Data source: Global Carbon Budget, 2022](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/1UC87CcrkOY2Nes1PVZWKNg.png)\n'Only parts of the world on fire' version of chart. Created by the author using Tableau. Data source: Global Carbon Budget, 2022\n## Be selective in categorizing\nThis technique is somewhat similar to omitting data. However, it isn't quite the same. Omitting data is simply removing the unwanted data from view, selective categorization is about shuffling data around until we find an adequate story. It is also less susceptible to criticism, and as such is most commonly used in areas where there is an attempt at critically assessing the analysis, such as published papers in peer-reviewed journals.\nI'll start with a simple toy example to explain what I mean by shuffling data around. Say I am studying the number of people who live in each household of a village. I have collected the following raw data:\n![](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/15qU6-w1jwzop_0bBIQKJyw.png)\nIf I want to convey the message that the village has many overcrowded households, then I can present the data like so:\n![Created by the author using Google Sheets.](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/1w92YiuweQiP9ifDAmqiTkQ.png)\nCreated by the author using Google Sheets.\nAll I have done is bundle 5,6,7, and 8 together to create one single data point, 5+. The final result is a chart with the biggest people per household category appearing the largest. Perfect for my narrative.\nBut, what if I don't want that. In fact, what if I want to convey the exact opposite message. I can shuffle the data around a bit, and end up presenting the data like so:\n![Created by the author using Google Sheets.](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/198K7YsAJT_sO_Demx6M6_w.png)\nCreated by the author using Google Sheets.\nHere, what I have done is bundle 0, 1, and 2 together, 3, 4, and 5 together, and 6, 7, and 8 together. As you can see, without even omitting a single point of raw data, I have completely changed the story.\nThis technique was brilliantly implemented in an academic research [paper](https://www.jstor.org/stable/10.1086/467988?seq=34) focusing on whether more guns reduce or increase crime. A highly cited paper by John Lott and David Mustard titled, \"Crime, Deterrence, and Right‐to‐Carry Concealed Handguns\" provides a remarkable chart of the consequences of implementing handgun concealment laws designed to increase the number of guns on the street.\n![source: "Crime, Deterrence, and Right‐to‐Carry Concealed Handguns" by John Lott and David Mustard](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/1Mo4m1oHlzZiQih8V02M1Tg.png)\nsource: [\"Crime, Deterrence, and Right‐to‐Carry Concealed Handguns\"](https://www.jstor.org/stable/10.1086/467988?seq=34) by John Lott and David Mustard\nTake another second to really look at what this chart is saying, because it is quite remarkable. It would suggest that violent crimes are almost universally due to the lack of concealed handguns, as evident by the lack of variance i.e. the crime rate smoothly declines post introduction of handgun laws. So, how did the authors achieve such a remarkable chart?\nFirstly, it takes advantage of technique number two, exploit pattern psychology, by starting the Y-axis at greater than zero. Secondly, and most influentially, it has selectively chosen what is and isn't considered as a 'violent crime', 'concealed handgun law', and the 'population' of the study. For example, in the violent crime category, they choose to allow robbery and aggravated assaults with a gun, but not without a gun e.g. a knife. Why? Because, robberies and aggravated assaults on average increased post adoption of handgun laws, which goes against the narrative. But taking a small slice of this violent crime i.e. robberies and aggravated assaults with a gun, the average conveniently decreased post adoption of handgun laws.\nSimilarly, some regions and years were excluded from the population sample. These regions and years had huge spikes in violent crimes post concealed handgun law adoption. The reason the authors gave for removing these populations was due to 'higher drug prices' (I'm not making this up, page 24 \"[Crime, Deterrence, and Right‐to‐Carry Concealed Handguns](https://www.jstor.org/stable/10.1086/467988?seq=34)\").\nRepeat this sort of selective categorization a few more times, and voila - the perfect chart!\n## Strategically adjust readability\nIf, sadly, you can't avoid publishing some unsightly data in your charts, there is one final technique you can use to maintain your narrative. Make the charts unbearable to look at. A classic is to present the data as a cold hard table. For example:\n![Created by the author using Microsoft Word](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/10/1Z6XHjmeZj6Yh_Cp2mygD9w.jpeg)\nCreated by the author using Microsoft Word\nDid you read it all? If so you're a stronger person than I am. I'll be honest with you, I have no idea if this data is trying to manipulate me or not, all I know is I don't want to read that ugly table, and you can't make me!\nIf you do have some good data sprinkled around the nasty narrative-killing data, then do your best to make the good stuff as readable as possible. Nice simple line or bar charts will do. And, of course, make sure all the bad data gets the table treatment.\n## Conclusion\n**A message to data scientists, business analysts, academic researchers, and everyone else involved in presenting data** : Manipulating your audience can be easy, but it's not cool. It is important to make a deliberate effort to consider whether your work uses any of these four techniques. It may not have been intentional, but confirmation bias, as well as pressure from others, does cause manipulative data tricks to slip into one's work.\n**A message to data consumers (** basically, everyone**)** : I hope this article has empowered you to critically evaluate the data and statistics you encounter. Furthermore, I encourage readers to be vocal about any poor data ethical discoveries you may find. Whether it is via verbal discussion, a social media post, blog, video essay, note in the comment section... the list goes on, please don't be shy from criticising it when you see it.\nIf you'd like more of my insights on uncovering data issues, I encourage you to read my previous article, [Stop being data driven](https://medium.com/towards-data-science/stop-being-data-driven-583b5e7abe7b), as well as following me on [Medium](https://medium.com/@caiparryjones96) for future articles. If you'd like to spread the reach of this article, please give it a clap (or 50 😏 ) and share on social media. Thanks for reading. Until next time, peace out data champs! ✌️\n## Register Now to Continue Reading\n### Unlock Towards Data Science with a Free Account\nAll articles on Towards Data Science are available to registered users. Create a free account today to access this article and thousands more.\nRegister for freeSign in to your account\n* * *\n![](https://assets.insightmediagroup.io/media/1787657617193_bio6ww.jpeg)\nWritten By\n## [Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\n[See all from Cai Parry-Jones](https://towardsdatascience.com/author/caiparryjones96/)\n[Charts](https://towardsdatascience.com/tag/charts/)[Data Analysis](https://towardsdatascience.com/tag/data-analysis/)[Data Visualization](https://towardsdatascience.com/tag/data-visualization/)[Misinformation](https://towardsdatascience.com/tag/misinformation/)[Tips And Tricks](https://towardsdatascience.com/tag/tips-and-tricks/)\nShare This Article\n * [](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Ftowardsdatascience.com%2Fadvanced-techniques-in-lying-using-data-visualizations-794278c09844%2F&title=Advanced%20Techniques%20in%20Lying%20using%20Data%20Visualizations)\n * [](https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Ftowardsdatascience.com%2Fadvanced-techniques-in-lying-using-data-visualizations-794278c09844%2F&title=Advanced%20Techniques%20in%20Lying%20using%20Data%20Visualizations)\n * [](https://x.com/share?url=https%3A%2F%2Ftowardsdatascience.com%2Fadvanced-techniques-in-lying-using-data-visualizations-794278c09844%2F&text=Advanced%20Techniques%20in%20Lying%20using%20Data%20Visualizations)\n\n\nTowards Data Science is a community publication. Submit your insights to reach our global audience and earn through the TDS Author Payment Program.\n[Write for TDS](https://towardsdatascience.com/submissions/)\n## Related Articles\n * [![](https://towardsdatascience.com/images/fallback-image.jpg)](https://towardsdatascience.com/build-your-own-synthetic-data-15d91389a37b/)\n## [Build Your Own Synthetic Data](https://towardsdatascience.com/build-your-own-synthetic-data-15d91389a37b/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nGo from Nothing to a Complete Dataframe with Python\n[Kurt Klingensmith](https://towardsdatascience.com/author/kurt.klingensmith/)\nFebruary 7, 20248 min read\n * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2021/01/1BGRcud4X7KLvWWBkpCsXsQ.gif)](https://towardsdatascience.com/minimum-viable-streaming-dashboard-in-power-bi-part-1-56e00a82c22f/)\n## [Minimum Viable Streaming Dashboard in Power BI: Part 1](https://towardsdatascience.com/minimum-viable-streaming-dashboard-in-power-bi-part-1-56e00a82c22f/)\n[Data Visualization](https://towardsdatascience.com/category/data-science/data-visualization/)\nA two-part series on developing real-time streaming dashboards and their use cases.\n[Nathan Cheng](https://towardsdatascience.com/author/natworkeffects/)\nJanuary 31, 20218 min read\n * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2020/11/1PwSPD0vizMYiNa4JGI0c8w-scaled.jpeg)](https://towardsdatascience.com/8-must-know-data-visualizations-for-better-data-analysis-9752953dd703/)\n## [8 Must-Know Data Visualizations for Better Data Analysis](https://towardsdatascience.com/8-must-know-data-visualizations-for-better-data-analysis-9752953dd703/)\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\nExplained with examples using Seaborn\n[Soner Yıldırım](https://towardsdatascience.com/author/sonery/)\nNovember 21, 20206 min read\n * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2024/04/1tpxLntNxZykssOsfvvbxTw.png)](https://towardsdatascience.com/how-to-make-cyberpunk-dark-mode-data-visualizations-in-python-b28f82386e75/)\n## [How to Make Cyberpunk \"Dark Mode\" Data Visualizations in Python](https://towardsdatascience.com/how-to-make-cyberpunk-dark-mode-data-visualizations-in-python-b28f82386e75/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nNeon Lines and Dark Designs, An Introduction\n[Mia Dwyer](https://towardsdatascience.com/author/mia_dwyer/)\nApril 8, 20243 min read\n * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2025/06/olga-davydova-8QUKrx-qcDc-unsplash-scaled-1.jpg)](https://towardsdatascience.com/from-pixels-to-plots/)\n## [From Pixels to Plots](https://towardsdatascience.com/from-pixels-to-plots/)\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\nHow I built an AI-powered prototype to turn images into insights\n[Jens Winkelmann](https://towardsdatascience.com/author/jens.winkelmann/)\nJune 30, 202514 min read\n * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2021/01/02GWJUJOWXxqf6QIG.png)](https://towardsdatascience.com/9-examples-to-master-seaborn-grids-1935bb38014c/)\n## [9 Examples to Master Seaborn Grids](https://towardsdatascience.com/9-examples-to-master-seaborn-grids-1935bb38014c/)\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\nPractical guide for FacetGrid and PairGrid\n[Soner Yıldırım](https://towardsdatascience.com/author/sonery/)\nJanuary 2, 20215 min read\n * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2021/01/1JU8SLStT_WFtPsdasinMbw-scaled.jpeg)](https://towardsdatascience.com/do-all-russians-love-their-jobs-how-work-enjoyment-changes-how-much-you-value-your-time-4daca4e7ba19/)\n## [Do All Russians Love Their Jobs? 🧐 How Work Enjoyment Changes How Much You Value Your Time.](https://towardsdatascience.com/do-all-russians-love-their-jobs-how-work-enjoyment-changes-how-much-you-value-your-time-4daca4e7ba19/)\n[Data Visualization](https://towardsdatascience.com/category/data-science/data-visualization/)\nData Analysis, Stats & Visualisation of 13k+ responses to the Value of Time Calculator\n[Marta](https://towardsdatascience.com/author/krzem-m/)\nJanuary 10, 20215 min read\n * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2021/06/1BzpMkVsJaN_j9sfiP_B5Fw.png)](https://towardsdatascience.com/visualizing-satellite-data-using-matplotlib-and-cartopy-8274acb07b84/)\n## [Visualizing Satellite Data Using Matplotlib and Cartopy](https://towardsdatascience.com/visualizing-satellite-data-using-matplotlib-and-cartopy-8274acb07b84/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nExplore our changing climate using Python and passive microwave data\n[Will Norris](https://towardsdatascience.com/author/willmnorris/)\nJune 25, 202110 min read\n * [![](https://assets.insightmediagroup.io/media/wp-content/uploads/2020/12/1Bwfbq67us1pmwBGY9YuytA.jpeg)](https://towardsdatascience.com/can-i-form-a-dream-team-in-fifa-19-using-sql-160fd9a3f172/)\n## [Can I Form A Dream Team in FIFA 19 using SQL?](https://towardsdatascience.com/can-i-form-a-dream-team-in-fifa-19-using-sql-160fd9a3f172/)\n[Data Science](https://towardsdatascience.com/category/data-science/)\nSQL Is Powerful but Is It Powerful Enough for This Important Job?\n[Efe Buyuk](https://towardsdatascience.com/author/efebuyuk/)\nDecember 8, 20204 min read\n\n\n * [YouTube](https://www.youtube.com/c/TowardsDataScience)\n * [X](https://x.com/TDataScience)\n * [LinkedIn](https://www.linkedin.com/company/towards-data-science/)\n * [Threads](https://www.threads.net/@towardsdatascience)\n * [Bluesky](https://bsky.app/profile/towardsdatascience.com)\n\n\n[](https://towardsdatascience.com/)\nYour home for data science and AI. The world's leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.\nSubscribe to Our Newsletter[Write For TDS](https://towardsdatascience.com/submissions/)•[About](https://towardsdatascience.com/about-towards-data-science-d691af11cc2f/)•[Advertise](https://contact.towardsdatascience.com/advertise-with-towards-data-science)•[Privacy Policy](https://towardsdatascience.com/privacy-policy/)•[Terms of Use](https://towardsdatascience.com/website-terms-of-use/)\n© Insight Media Group, LLC 2026•[The New Stack](https://thenewstack.io)•[roadmap.sh](https://roadmap.sh)•[Creator Network](https://insightmediagroup.io/creator-network)\n#### Recommended Articles \nClose\n * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607686/image?etag=1782161464448&width=500&height=500) How Relevance Models Foreshadowed Transformers for NLP ](https://towardsdatascience.com/how-relevance-models-foreshadowed-transformers-for-nlp/ \"How Relevance Models Foreshadowed Transformers for NLP\")\n * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607639/image?etag=1781250125848&width=500&height=500) Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 1 ](https://towardsdatascience.com/javascript-fatigue-you-dont-need-js-to-build-chatgpt/ \"Javascript Fatigue: HTMX Is All You Need to Build ChatGPT — Part 1\")\n * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/607930/image?etag=1782124566054&width=500&height=500) The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs ](https://towardsdatascience.com/subset-sum-problem-solved-in-linear-time-for-dense-enough-inputs/ \"The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs\")\n * [ ![](https://h030.towardsdatascience.com/rest/v2/contentStores/d7d3a4ab-7caf-4383-bbd2-fbf7fb4f1787/items/3660/image?etag=1780176246070&width=500&height=500) Does Your Company Have a Data Strategy? ](https://towardsdatascience.com/does-your-company-have-a-data-strategy-e8944dbec4ae/ \"Does Your Company Have a Data Strategy?\")\n\n\n", "body_base_path": "attachments/c33131c1e7f1/pages/", "body_markdown_path": "attachments/c33131c1e7f1/pages/archived-body.md", "local_html": "attachments/c33131c1e7f1/pages/archived-body.html", "body_source": "prior_capture" }