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    to represent the share of a particular category, bar chart is the most appropriate graphical representation.

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    get to represent the share of a particular category, bar chart is the most appropriate graphical representation. from screen.

    A Complete Guide to Bar Charts

    Bar charts are a fundamental visualization for comparing values between groups of data. Use this guide to learn how to get the most of this chart type!

    DATA TUTORIALSCHARTS

    A Complete Guide to Bar Charts

    Posted by Mike Yi

    One of the most fundamental chart types is the bar chart, and one of your most useful tools when it comes to exploring and understanding your data.

    What is a bar chart?

    A bar chart (aka bar graph, column chart) plots numeric values for levels of a categorical feature as bars. Levels are plotted on one chart axis, and values are plotted on the other axis. Each categorical value claims one bar, and the length of each bar corresponds to the bar’s value. Bars are plotted on a common baseline to allow for easy comparison of values.

    This example bar chart depicts the number of purchases made on a site by different types of users. The categorical feature, user type, is plotted on the horizontal axis, and each bar’s height corresponds to the number of purchases made under each user type. We can see from this chart that while there are about three times as many purchases from new users who create user accounts than those that do not create user accounts (guests), both are dwarfed by the number of purchases made by repeating users.

    When you should use a bar chart

    A bar chart is used when you want to show a distribution of data points or perform a comparison of metric values across different subgroups of your data. From a bar chart, we can see which groups are highest or most common, and how other groups compare against the others. Since this is a fairly common task, bar charts are a fairly ubiquitous chart type.

    The primary variable of a bar chart is its categorical variable. A categorical variable takes discrete values, which can be thought of as labels. Examples include state or country, industry type, website access method (desktop, mobile), and visitor type (free, basic, premium). Some categorical variables have ordered values, like dividing objects by size (small, medium, large). In addition, some non-categorical variables can be converted into groups, like aggregating temporal data based on date (eg. dividing by quarter into 20XX-Q1, 20XX-Q2, 20XX-Q3, 20XX-Q4, etc.) The important point for this primary variable is that the groups are distinct.

    In contrast, the secondary variable will be numeric in nature. The secondary variable’s values determine the length of each bar. These values can come from a great variety of sources. In its simplest form, the values may be a simple frequency count or proportion for how much of the data is divided into each category – not an actual data feature at all. For example, the following plot counts pageviews over a period of six months. You can see from this visualization that there was a small peak in June and July before returning to the previous baseline.

    Other times, the values may be an average, total, or some other summary measure computed separately for each group. In the following example, the height of each bar depicts the average transaction size by method of payment. Note that while the average payments are highest with checks, it would take a different plot to show how often customers actually use them.

    Example of data structure

    PAYMENT TYPE AVERAGE TRANSACTION

    Check 46.861 Credit Card 36.681 Debit Card 28.860

    Digital Wallet 18.900

    Cash 4.802

    Data rendered as a bar chart might come in a compact form like the above table, with one column for the categories and the second column for their values. Other times, data may come in its unaggregated form like the below table snippet, with the visualization tool automatically performing the aggregation at the time of visualization creation.

    For a count-based bar chart, just the first column is needed. For a summary-based bar chart, group by the first column, then compute the summary measure on the second.

    Best practices for using bar charts

    Use a common zero-valued baseline

    First and foremost, make sure that all of your bars are being plotted against a zero-value baseline. Not only does that baseline make it easier for readers to compare bar lengths, it also maintains the truthfulness of your data visualization. A bar chart with a non-zero baseline or some other gap in the axis scale can easily misrepresent the comparison between groups since the ratio in bar lengths will not match the ratio in actual bar values.

    By cutting 90 points out of the vertical axis, a small 4-point difference can be exaggerated to look like a 1:3 ratio.

    स्रोत : chartio.com

    [Solved] In which of the following way we can represent data regardin

    Data are information collected in a systematic manner with the aim of deriving certain related conclusion. The data may be collected from different sources dire

    Home Mathematics Statistics Classification of Data

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    In which of the following way we can represent data regarding the population of five different countries in a particular year?

    I. Table II. Bar graph III. Histogram IV. Pie chart

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    I and III II, III and IV I and II I, II, III and IV

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    Option 4 : I, II, III and IV

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    Data are information collected in a systematic manner with the aim of deriving certain related conclusion. The data may be collected from different sources directly and indirectly. The collected data are to be recorded in a systematic manner that would be convenient for further use. For example, table, bar graph, histogram, and pi- chart can be used to represent data regarding the population of five different countries in a particular year.

    Bar Graph: It is used to show a comparison among categories. It may consist of two or more parallel vertical (or horizontal) bars (rectangles). It is used to compare variables. The lengths of the bars are equivalent to the measure of data, are known as bar graphs or bar charts. Rectangles are drawn on X-axis known as Horizontal Bar Graph. Rectangles drawn along the y-axis are known as Vertical Bar Graphs

    Histogram: A histogram is similar to a bar graph in the way that it is also formed using rectangles but the difference is there no gap between these rectangles. Also, it is used to show the distribution of variables.

    Pie graph: Another type of graph is called a pie graph or circle graph. In the circle or pie graph, the concept of “greater than”, “taller than”, “smaller-bigger”, “highest-lowest” etc., are depicted.

    Table: It consists of cells in which entries are filled. Those entries can be number, list of word, or symbols.

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    More Classification of Data Questions

    Q1. The frequency distribution according to individual variate values is called:Q2. The following frequency distribution is classified: x: 5 15 38 47 68 y: 2   4   9   3   1Q3. Consider the frequency of five observations: x - 2, x - 4, y, -2x, x If the cumulative frequency of fifth observations is 8 then the value of y will beQ4. Study the following graph. Total exports for the given year is:Q5. The ogive curve represents the daily income of 50 workers of a factory. If there are 8 workers with daily wages b/w 140 - 160 How many workers have a daily income of fewer than 160 Rs?Q6. Bar chart shows production of cement by four factories A, B, C & D over the years The production of cement by factory B in 2009 and production of cement by factory D in 2010 together is what percentage of percent of production by factory A in 2008 ?Q7. The graph represents the average score of a Test player with respect to the number of Test matches he played.  Determined the percentage change in average score b/w 10 - 40 match.Q8. If the frequency of 2nd and 5th observations are the same then (x - y) will be Class 10-20 20-30 30-40 40-50 50-60 60-70 Cumulative frequency 10 x 24 27 y 38Q9. A cumulative frequency distribution is given below: Class 40 - 42 43 - 45 46 - 48 49 - 51 52 - 54  55 - 57 Cumulative frequency 6 14 24 35 49 61 Which one of the following classes has maximum frequency?Q10. Consider the following distribution: Salary (in Rs.) Number of employees More than or equal to zero 51 More than or equal to 10,000 48 More than or equal to 20,000 37 More than or equal to 30,000 25 More than or equal to 40,000 19 More than or equal to 50,000 9   The frequency of class interval 30,000 - 40,000 is:

    More Statistics Questions

    Q1. What is the mode of the following numbers: 10, 21, 10, 12, 21, 10, 21, 21, 21, 12, 13, 21, 12?Q2. If the frequency of each class is doubled, then what would be the mean?Q3. What is the value of q ?Q4. What is the value of p ?Q5. What is the sum of the deviations measured from the median?Q6. What is the median of the marks?Q7. What is the mean of the marks ?Q8. If the algebraic sum of the deviations of the same set of values measured from y is 180, then what is the value of y ?Q9. What is the algebraic sum of the deviations of the same set of values measured from 99?Q10. What is the mean of the values?

    स्रोत : testbook.com

    What types of data are appropriately represented with a stacked bar graph?

    Answer (1 of 3): Bar graphs are an excellent way to display a value by a category - like sales per month. Stacked bar graph adds a subcategory - like sales per product per month. This lets you see the big picture alongside some amount of detail. Did we sell more this month because of more custome...

    What types of data are appropriately represented with a stacked bar graph?

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    Sort Theo Rosenfeld

    Founding partner of Engage Data, a data visualization and interface design firm6y

    Bar graphs are an excellent way to display a value by a category - like sales per month. Stacked bar graph adds a subcategory - like sales per product per month. This lets you see the big picture alongside some amount of detail. Did we sell more this month because of more customer traffic overall or because of a spike in demand for a particular product?

    This works best when the sub-categories are common across the main categories. A bar graph is great to show sales per department. A stacked bar graph would be great for sales per department per month (as every department uses the same calendar)

    Related questions

    What types of data are appropriately represented with a grouped bar graph?

    What type of data does a bar graph represent?

    What is a bar graph and what are the types of bar graphs?

    How are stacked line graphs constructed?

    What does a stacked bar graph mainly show?

    Oleg Seriaga

    Product owner, vizydrop.comUpdated 3y

    Pretty good explanation can be found here Stacked Graph | Better Evaluation

    Stacked graphs display cumulative values. Thus, consider whether it makes sense to add up your values; for example, it is again better to use a line graph

    rather than adding the price of one company to the price of another, or adding the prices of products over time.

    For example can be used for displaying sum of all commits by authors weekly

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    Voorhees

    Analytics Team Lead at Syvylyze Analytics LLP (2018–present)Author has 54 answers and 59.2K answer views5y

    Related

    What types of data are appropriately represented with a grouped bar graph?

    Grouped bar chart can be used to compare 2 or more products, lets say of different brands, for different demographics or Month-on-Month comparison.If you want to compare different products of same company then you can use stacked bar.The height of entire bar will present total sales of the company with contributions of individual products.

    Also, total sales,profit and loss can be shown side by side for different demographics or M-o-M comparisons.

    Karen Mruk

    PhD Biochemistry, Biophysics, and Chemical BiologyAuthor has 78 answers and 283.6K answer views6y

    I find them particularly useful for phenotypic data.

    I. Hyper/Hypo-morphic Mutations:

    REFERENCE: Optochemical dissection of T-box gene-dependent medial floor plate development.

    II Chemical Manipulation:

    These bars are easier to read than a large bar graph (in this example 16x3 subgroups). They also take up less space allowing for clear images of each phenotype.

    It doesn't require color to see/understand which is advantageous for the cash-strapped junior PI!

    Lukas Tencer ML Lead at Twitch7y Related

    What's the best way to visualize high-dimensional data?

    Unfortunately our imagination sucks if you go beyond 3 dimensions.

    Therefore for "high-dimensional data visualization" you can adjust one of two things, either the visualization or the data.

    Adjusting the visualization:

    You can use some of the techniques for high dimensional data visualization. You can use color, shape, size and other properties of 3D and 2D objects. This allows you to go further in high-dimensional visualization but still if you have more than 6 dimensions, the visualization might be hard to understand.

    Then there are other visualization techniques for high dimensional data. Some

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    , Econ PhD from Stanford, 2 years of PhD stats and

    Alex Blocker

    , Staff Statistician at GRAIL, Xoogler, statistics PhDAuthor has 930 answers and 28.7M answer viewsUpdated 7y

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    What should everyone know about making good charts and graphs to represent data?

    Rule 1: Avoid 3D Versions of 2D Graphs

    Sure, they look prettier and any presentation software will give you a whole range of them, but depth distorts any graph where area and position matter. If done unknowingly, this is misleading. If done purposefully, this is a deceitful and shameful practice. See this slide from one of Steve Job's 2008 Macworld Expo keynotes:

    स्रोत : www.quora.com

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