How to Make a Line Graph in Excel?

There is a story behind every number – data visualization brings such stories to life. Data visualization has grown over the years, and more data points have been brought into the mix. In the past, analysts were content with measuring data sets with one or two variables. But what if there are multiple variables, and every one of these is important? Well, that’s where line graphs come into play. And making line graphs is not as difficult as advertised.

Years ago, data visualization was pretty much simple. Analysts get to check the relationship (or correlation) between variables using visuals. Nowadays, there are lots of twists in the marketplace, and you get to see multiple variables in a single data set. To cater to these new changes, more innovative ways of measuring data were introduced – and making line graphs were one of such way.

Line graphs don’t just show the relationship between variables, but it’s a reliable tool that showcases how one or more variables changes over time. It shows the progression of a variable over a period.

In this guide, you will discover what line graphs are, and how making line graphs could be the next step towards building a more robust data visualization strategy for your business. Finally, you will discover how to create line graphs using tools like ChartExpo.

Enough said! Here’s your first step in your journey to making line graphs.

Table of Contents:

1. What is a Line Graph?
2. What are the Elements or Components of a Line Graph?
3. What are the Different Types of Line Graphs?
4. Line Graph Examples
5. How to Create a Line Graph in Excel with Multiple Lines?
6. How to Make Line Graphs Online? Guide with Examples
7. How to Read a Line Graph?
8. When Using Line Graphs is Right?
9. Advantages and Disadvantages of Using Line Graphs
10. Line Graphs Best Practices
11. Why Do We Use Multiple Lines in Excel Graph?
12. Common Ways of Missing a Line Graph
    
13. Wrap Up

What is a Line Graph?

Definition: Also known as line charts, line graphs show how the value of a variable changes over time. It can also be used to measure how the value of several variables changes over time. Regardless of the number of variables involved, line graphs help you see how they change over time.

If you are working with a data set, and you see the phrase “over time”, that’s a clue to use a line graph. One of the primary benefits of a line graph is that they are efficient, simple, and easy to understand. Aside from using line graphs to measure changes over time, you can use the tool for other analyses like.

• Comparing several data sets at the same time
• Inserting important annotation and context
• Forecasting uncertainty in a data set
• Showing anomalies across (or within) data sets.

On the flip side, line graphs are not ideal.

• Highlighting sparse data sets
• Measuring categorical data
• Showing quantities in data units
• Performing part-to-whole comparisons.

Now you understand what line graphs are, and the benefits of making line graphs, you’ve got to take a look at the various components of a line graph.

What are the Elements or Components of a Line Graph?

A line graph transforms data into a visual masterpiece, offering clarity and insights to the readers. Let’s dissect the composition of a line graph and understand the significance of each element:

• X-axis: The X-axis, the backbone of our graph, stretches horizontally, representing the independent variable. This is where we place categories, time, or any other continuous scale.
• Y-axis: The Y-axis, standing tall vertically, represents the dependent variable. It’s the scale against which we measure and interpret the corresponding values.
• Data points: These are the stars on our stage. Each represents a specific value at the intersection of X and Y coordinates.
• Lines: The lines, like musical notes, connect the data points, creating a melodic flow. They visually articulate trends and patterns, turning isolated points into a cohesive narrative.
• Title: The title, akin to a musical score, guides the audience. It encapsulates the theme, allowing viewers to grasp the essence without delving into the minutiae.
• Labels: Like signposts along the journey, labels on the X and Y axes provide context. They ensure the audience understands what’s being measured and in what units.
• Legend: In our ensemble of elements, the legend is a program identifying each line or data set. It prevents confusion, ensuring the audience recognizes which melody corresponds to which instrument.
• Gridlines: The gridlines act as the stage floor, providing a visual reference for precise interpretation. They guide the eye, helping in understanding the scale and relationships between data points.

What are the Different Types of Line Graphs?

Just as artists have different techniques, there are distinct types of line graphs that convey information with precision. Each type has its personality, telling stories in unique ways.

• Basic Line Graph

The basic line graph is the fundamental storyteller in the world of data. It consists of a single line connecting data points, typically representing how one variable changes over time. This simplicity makes it perfect for illustrating trends and variations with clarity.

• Multiple Line Graph

When the story involves more than one character, we turn to the multiple-line graph. It accommodates two or more lines on the same graph, allowing for direct comparisons between different datasets. The multiple-line graph excels in showcasing relationships and divergences between variables.

• Stacked Line Graph

Line Graph Examples function like stacking layers of information, akin to building blocks. The stacked line graph accomplishes this precisely. Each line signifies a distinct category, and they layer atop one another to depict the cumulative sum. This visual layering accentuates not just individual values but also the comprehensive structure of the data.

• Step Line Graph

Stepping away from smooth transitions, the step-line graph introduces a unique rhythm. Instead of connecting points with continuous lines, it uses horizontal and vertical steps. This method accentuates individual data points, making it useful for displaying data that changes abruptly.

• Spline Line Graph

For a touch of elegance, we introduce the spline line graph. Instead of straight lines, this type uses smooth curves to connect data points. The result is a graph with a more polished and visually appealing look. This graph type is particularly suitable for capturing gradual changes in data.

• Area Line Graph

Line Graph Examples go beyond mere lines, as seen in the area line graph that emphasizes space. By shading the area below the line, it underscores the magnitude of values. This type is particularly effective at depicting volume or the cumulative impact of data, enriching the narrative with depth.

• Comparative Line Graph

Imagine a stage with different acts. Comparative line graphs compare multiple lines, each with its scale. This type accommodates the complexity of multiple variables, allowing for nuanced analysis and interpretation.

Line Graph Examples

1. Marketing Strategy

Now you’re done with the basics, it’s time to get into the nitty-gritty of how to create line graphs using ChartExpo.

How to Create a Line Graph in Excel with Multiple Lines?

Are you tired of Excel’s data visualizations looking as exciting as a tax form instruction manual?

We get it; those uninspiring charts can be a buzzkill. But fear not; we have the antidote to Excel’s limitations in data visualization—ChartExpo.

Say goodbye to boring, outdated graphs and hello to cool Excel charts and graphs that bring your data to life. With ChartExpo, you can create vibrant, multi-line masterpieces effortlessly.

Benefits of Using ChartExpo

• ChartExpo flaunts a smorgasbord of visualizations, allowing you to handpick the perfect one for your data. Say farewell to data doldrums; this makes your data analysis and presentation as sharp as a well-tailored suit.
• Navigating ChartExpo is smoother than a jazz riff on a saxophone. Its user-friendly interface lets you craft dazzling visuals without needing a crash course in coding. It’s like having a visual wizard in your back pocket.
• Unleash your inner artist with ChartExpo’s customizability. Tweak colors, fonts, and styles to make your charts as unique as a thumbprint. It’s your data’s chance to dress to impress!
• And here’s the kicker: ChartExpo delivers more bang for your buck than a budget-friendly fireworks show. Get a taste with a free 7-day trial. And when you’re hooked (you will be), it’s just $10 a month to keep the visual magic flowing.

How to Install ChartExpo in Excel?

1. Open your Excel application.
2. Open the worksheet and click the “Insert” menu.
3. You’ll see the “My Apps” option.
4. In the office Add-ins window, click “Store” and search for ChartExpo on my Apps Store.
5. Click the “Add” button to install ChartExpo in your Excel.

ChartExpo charts are available both in Google Sheets and Microsoft Excel. Please use the following CTA’s to install the tool of your choice and create beautiful visualizations in a few clicks in your favorite tool.

Example

Suppose you want to analyze the monthly website visitors, advertising spending, & bounce rate data below.

Months	Visitors	Advertising Spending (in $)	Bounce Rate (%)
Jan	84551	1484	36
Feb	103091	2096	43
Mar	102740	1724	33
Apr	80207	1287	49
May	97442	1255	47
Jun	88406	1568	46
Jul	60540	1286	31
Aug	101165	1539	31
Sep	74958	1125	31
Oct	78681	1811	36
Nov	66559	1400	48
Dec	89007	1146	39

Follow the steps below to learn about Excel line graphs with multiple lines with Chart Expo for analysis.

• To get started with ChartExpo, install ChartExpo in Excel.
• Now Click on My Apps from the INSERT menu.

• Choose ChartExpo from My Apps, then click Insert.

• Once it loads, scroll through the charts list to locate and choose the “Multi-Axis Line Chart”.

• Click the “Create Chart From Selection” button after selecting the data from the sheet, as shown.

• ChartExpo will generate the visualization below for you.

• If you want to have the chart’s title, click Edit Chart, as shown in the above image.
• Click the pencil icon next to the Chart Header to change the title.
• It will open the properties dialog. Under the Text section, you can add a heading in Line 1 and enable Show.
• Give the appropriate title of your chart and click the Apply button.

• Let’s add the Prefix (e.g., $ sign) with the Advertising Spending scale in the chart.
• Click the highlighted pencil icon. Expand the “Label” properties to add the Prefix value (e.g., $ sign).

• Let’s add the Postfix (e.g., % Sign) with the Bounce Rate scale in the chart.
• Click the highlighted pencil icon. Expand the “Label” properties to add the Postfix value (e.g., % sign).
• To persist the changes made to the chart, you can click on the “Save Changes” button.

• Your final chart will look like the one below.

Insights

• Bounce Rate Trends

The bounce rate fluctuates across different months of the year. In March and July, the bounce rate was relatively low at 33% and 31%, respectively, indicating higher user engagement during these periods. On the other hand, in April and November, the bounce rate peaked at 49% and 48%, respectively. This suggests potential concerns with the website’s content or user experience during these months.

• Seasonal Visitor Trends

The number of visitors fluctuates throughout the year, showing a seasonal pattern. February and August experienced the highest visitor volume, with 103,091 and 101,165 visitors, respectively. These peaks could be attributed to targeted marketing campaigns or seasonal factors. Conversely, July sees the lowest number of visitors, with 60,540, which could be influenced by vacation periods.

• Advertising Spending Impact

There is a correlation between advertising expenditure and the number of visitors. The higher spending observed in February and October partially corresponds to the peaks in visitor counts during those months. However, the spending in September and December remains comparatively low.

How to Make Line Graphs Online? Guide with Examples

Data visualization comes with lots of possibilities – and there are countless types of charts you can create with line graphs. Before getting started, you’ve got to do your homework. Yes, identify the right chart that is suitable for your data.

Regardless of how complex or intuitive your data is, there is a data visualization tool to help you create a visually appealing line graph. Making line graphs is tough – but you can skip the tedious process that goes into maneuvering lots of connections by merely using ChartExpo for Google Sheets add-on.

Using ChartExpo to plot line graphs is pretty straightforward – after all, there are various types of built-in line charts, and with simple clicks, you get to create compelling charts within minutes.

One of the importance of a line chart is that you get to see the overall trend with little or no room for error. Let’s say you want to check the performance of a company in the previous decade. First, you’ve got to gather data like the one shown below.

Year	TV	Mobiles	Sound System
2015	700	1500	1000
2016	600	1400	900
2017	700	2000	1300
2018	1200	1800	800
2019	980	1900	1100
2020	700	2500	1200

• First, you’ve got to open the ChartExpo add-on by clicking on the add-on. If it is not installed yet you can get ChartExpo add-on from here.

• After clicking on the ChartExpo add-on, you’d get to see lots of options displayed on the right corner of your screen. Choose the Multi Series Line Chart from General Analysis Charts.

• Next, choose the dimension and metrics and click on the create chart option.

• Finally, a chart similar to the one below will be displayed on your screen.

Sometimes, the trends in a chart are not always defined, which leads to confusion. But that’s not the case with a line graph. With a multi-series line chart, everything is defined – and you get to closely monitor the trends over a specified time.

Example # 1: Line Chart

Let’s say you’ve got the data below and you want to analyze your online store sales in year 2020, here is what you need to do.

First, compile the data in a table as shown below.

Year	Sales
Jan	500
Feb	550
Mar	800
Apr	600
May	850
Jun	1100
July	900
Aug	950
Sep	1150
Oct	1085
Nov	1175
Dec	1300

• Next, insert the data in Google Sheets, and from the options shown in your ChartExpo, choose a line chart from General Analysis Charts. Moving on, you’ve got to select your dimensions and metrics and click the create chart button.

• A screen similar to the one below will be displayed.

Example # 2: Sentiment Sparkline Chart

Let’s say you are one of the workers in a healthcare facility, and you’ve got survey data below for analyzing the positive and negative cases of some health issues, here is how to handle it. First, you’ve got your survey data as shown below.

Years	NEGATIVE	POSITIVE
Jan 2020	50	50
Feb 2020	60	40
Mar 2020	10	90
Apr 2020	70	30
May 2020	45	55
Jun 2020	95	5
July 2020	25	75
Aug 2020	20	80
Sep 2020	38	62
Oct 2020	29	75
Nov 2020	30	90
Dec 2020	55	35

• Insert the data in your Google Sheets, and after choosing the Sentiment Sparkline Chart from ChartExpo, fill in the dimensions and metrics and click on the create chart icon.

• A chart similar to the one below will be displayed.

Checking the covid-19 test results is quite easy from the chart. The red part shows the negative test reports, while the green part shows the positive test reports. This way, you can easily study your data with ease. But remember, having negative test is a good sign and having positive COVID-19 is a bad sign so you can flip the colors to show the same chart with more meanings.

Example # 3:Vertical Axis Line Chart

Let’s say you’ve been running a PPC marketing campaign for some time, and you need to analyze some metrics like conversions, impressions, and clicks. All you need to do is create compelling visuals using a data visualization tool.

But first, you need to gather data like the one below.

Date	Impressions	Clicks	Conversions
05/01/2020	4141	411	0
05/02/2020	6380	601	2
05/03/2020	11541	1046	7
05/04/2020	12312	1256	8
05/05/2020	16406	1504	6
05/06/2020	17765	1807	5
05/07/2020	24532	2224	10
05/08/2020	29016	2345	11
05/09/2020	29122	2297	8
05/10/2020	27125	2164	9
05/11/2020	26783	2280	6
05/12/2020	25942	2086	16
05/13/2020	27127	2320	6
05/14/2020	24548	2111	9
05/15/2020	23448	2115	38
05/16/2020	23408	2065	92
05/17/2020	21473	2075	90
05/18/2020	20959	1939	82
05/19/2020	15710	1437	64
05/20/2020	21221	1964	104
05/21/2020	20317	1740	80
05/22/2020	16431	1548	76
05/23/2020	16785	1376	78
05/24/2020	17247	1526	82
05/25/2020	17851	1620	83
05/26/2020	6752	629	32
05/27/2020	16015	1569	70
05/28/2020	13689	1369	100
05/29/2020	12416	1123	100
05/30/2020	16874	1399	115
05/31/2020	18146	1324	97

• Insert the data in Google Sheets, and from the options available in ChartExpo, choose a vertical axis line chart and provide the figures for the dimensions and metrics. Finally, click the create chart button.

• You will get a chart similar to the one below.

If you take a close look, you will gain lots of insights from this chart. From this data visualization, you get to analyze lots of metrics and trends by merely looking at the chart. It eliminates the stress that comes with flipping through multiple charts just to gain insight and draw a conclusion from the data trends. Everything you need is showcased on a single screen.

Example # 4: Area Line Chart

Let’s say you manage a clothing brand, and you want to analyze your total purchase from your visitors. All you’ve got to do is gather some data like the one shown below.

Day	Total Visitors	Converted Visitors
05/01/2020	280	2
05/02/2020	220	4
05/03/2020	210	1
05/04/2020	180	5
05/05/2020	190	1
05/06/2020	230	3
05/07/2020	270	5
05/08/2020	230	10
05/09/2020	210	2
05/10/2020	225	4

• Insert the data in Google Sheets, and from the list of tools shown in ChartExpo, choose the area line chart, provide the dimensions and metrics and click on the create chart icon.

• A chart similar to the one below will be displayed.

From the chart above, you get to easily compare the number of visitors with the total purchase made. This way, analyzing the shop performance will be quite easy.

Example # 5: Sparkline Chart

Let’s say you opened a new institute in the United States, and you want to monitor the number of students gaining admission, all you’ve got to do is gather some data like the one below.

Months	Admission Count
Jan	45
Feb	66
Mar	57
Apr	84
May	64

• Insert the data in Google Sheets, and from the list of data visualization tools shown in your ChartExpo, choose Sparkline Chart and provide information to fill up the dimension and metrics. Next, click on the create chart icon.

• A chart like the one below will be displayed.

The same chart can be used in combinations and is best suited for small spaces to show some Sparkline trends. E.g if you have detail of admission of each month you can show the data like below:

From the chart above, you’ve got to check the trends for the admission of new students in different months. It’s a great way of analyzing the performance of the institute.

Example # 6: Dual Axis Line Chart

If you manage a restaurant and you want to track the sales of two products (maybe coffee and ice cream) to determine the product that generates the most revenue. All you’ve got to do is use a dual-axis line chart to track the product for the 24-hour period you’re open.

But first, you’ve got to gather data similar to the one displayed below.

Hour of Day	Ice Cream Sale	Coffee Sale
0	22.23	9.1
1	19.87	22
2	18.22	7.6
3	27.67	7.3
4	22.7	8.5
5	15.76	8.4
6	16.85	19
7	17.54	9.2
8	16.14	8.6
9	16.33	8.7
10	16.43	8.9
11	16.34	8.5
12	16.21	8.7
13	16.52	8.9
14	16.42	8.9
15	16.17	16
16	15.57	8.6
17	16.48	9
18	16.34	8.8
19	14.99	8.9
20	17.26	9.8
21	13.67	15
22	12.32	9.3
23	11.28	8.6

• Insert the data into your Google Sheets, and from your ChartExpo, choose a dual-axis line chart. Provide information for the dimension and metrics and click on the create chart icon.

• A chart similar to the one below will be displayed.

From the chart above, you can take a look at the revenue trends for ice cream and coffee sales. It also helps you to pinpoint the time of the day you are most likely to generate sales in each category.

You can use dual axis line and bar chart, you can also called it a combo chart to show your different data in a single chart

To analyze your data using a dual axis line and bar chart, you’ve got to select your data and provide the information for the dimensions and metrics.

• Next, click on the create chart icon to generate a chart similar to the one below.

• The chart above will offer more insight into your ice cream and coffee sales revenue. The bars showcase your sales revenue for each hour of the day.

How to Read a Line Graph?

Line Graph Examples can sometimes be as challenging to interpret as deciphering a doctor’s handwriting. But worry not; here’s a guide to mastering the art of reading a line graph with finesse.

1. Understand the axes: First, acquaint yourself with the stage. The X-axis stretches horizontally, representing the independent variable (like time or categories). The Y-axis stands tall vertically, portraying the dependent variable (the data you’re measuring). Know where you are on this grid, and you’ve got your bearings.
2. Interpret data points: Each dot on the graph is a data point – a storyteller in its own right. Understand what these points represent. Is it sales over time? Temperature across seasons? Each dot holds a nugget of information waiting to be unveiled.
3. Follow the lines: Connect the dots, quite literally. The lines between data points reveal the trajectory of change. A rising line signifies an increase, while a descending line indicates a decrease. The slope of the line is the story’s pace – is it a gradual ascent or a sudden plunge? You tell me.
4. Check the scale: The scale is the ruler of our narrative. Examine the intervals on the axes – are they days, months, or something else? Understanding the scale ensures you interpret the graph accurately, avoiding missteps in your data journey.
5. Identify key points: Zoom in on critical junctures. Peaks and valleys, where the lines change direction, are pivotal. These are turning points in the story, signaling highs, lows, or shifts in the data landscape. Paying attention to these key points enriches your understanding.
6. Consider the context: No story exists in a vacuum. Consider the broader context – external factors that may influence the data. Is there a spike in sales due to a marketing campaign? Is the temperature drop related to a seasonal change? Context adds depth to your interpretation.

When Using Line Graphs is Right?

Ideally, a making line graph should have one variable plotted on the vertical axis, while a second variable plotted on the horizontal axis – and variable on the horizontal axis has to consist of continuous values. Here is the thing, line graphs are used to measure changes within such plots.

Typically, the measurement on the horizontal axis has to be on regular intervals, and the variables should consist of continuous values. Most times, these variables are temporal, and they generate observations in specific time intervals like every hour, day, week, or month. These interval choices are not inherent in the data set. The analyst, most times, is the person to choose the right time interval for the data set.

The variables on the vertical axis are also defined by the intervals of the horizontal axis, and the analyst has to report the numeric values of the second variable that falls in each interval. These values could be the average value in each interval.

If you want to compare trends between series, then you’ve got to plot multiple lines in the line chart. These comparisons could be used to observe a breakdown of data across various subgroups.

For emphasis, not every kind of data can be represented using making line graphs. Here are the kinds of data that can be represented on a line graph.

Kinds of data that can be represented on a line graph

By now, you probably know that a line graph could have continuous data both on the horizontal (x-axis) and on the vertical (y-axis) dimensions. You get to see the value of the measured variable on the y-axis, while the x-axis shows when the variable is being measured – it could be represented chronologically or tied to some independent metrics.

To get the most out of a line graph, there has to be a solid correlation (or relationship) between successive points on the graph. If you manage a store, you could use a line graph to show your product sales data for each month. However, it would be somewhat impossible to use a line graph to show differences in various product sales. To demonstrate the sales of various products, you are better off with a bar chart.

Making line graphs is not all juicy. Yes, there are some benefits as well as disadvantages of using a line graph. Here are some advantages and disadvantages of using line graphs.

Advantages and Disadvantages of Using Line Graphs

Here are some benefits of making line graphs.

• With a line graph, you get to easily see and monitor changes in your data over time.
• You can easily pinpoint the relationship (or correlation) between two or more variables
• It shows changes and trends in an impressive format
• It indicates both positive and negative values
• Line graphs can easily measure small changes, no matter how negligible – and these changes are somewhat challenging to measure in other charts.

Enough of the benefits, here are some disadvantages (or limitations) of a line graph.

• It cannot accommodate several lines in a single graph – it leads to cluttering, and it becomes somewhat difficult for your audience to read
• It’s somewhat impossible to plot a wide range of data in a single line graph
• It’s only fit for presenting data that consists of figures like the value for the amount of rainfall in a year.

Having a good grasp of the benefits and limitations of making line graphs is not enough. If you want to use the chart, you’ve got to understand the best practices for using the chart.

Line Graphs Best Practices

Here are some things you must have in mind while making line graphs.

• Use appropriate intervals for your measurement

The interval (or bin size) is arguably the most important piece to consider while making line graphs. If your data is temporal, measurements that are too broad will make it somewhat difficult to trace your data trends. It could also hide useful signals in the chart. However, measurement intervals that are too short could cancel the signals, leading to noise. You see, you should maintain a balance when it comes to choosing measurement intervals.

• Avoid plotting too many lines

Technically, it’s possible to plot too many lines on a line graph – but that doesn’t mean you should do it. There is nothing wrong with maintaining a balance when it comes to the number of lines you plot on a line graph.

As a general rule of thumb, you should limit yourself to at most five lines when it comes to using a line graph. Anything more than that could make your line graph somewhat confusing to read.

That’s not to say you can’t plot multiple lines in a line graph.

Yes, multiple lines can be plotted in a line graph if your lines are properly separated. This way, tracking your values will be easy.

Why Do We Use Multiple Lines in Excel Graph?

An Excel line graph with multiple lines is a dynamic lens through which you can scrutinize and interpret your data. Let’s take a closer look at the reasons why it is useful:

1. Comparison: Picture this – you have multiple datasets and want to see how they stack against each other. Multiple lines allow you to place these datasets on a single canvas. As a result, this facilitates effortless comparisons and reveals trends, discrepancies, or convergences.
2. Visualization: Data can be complex, but multiple lines make it visually digestible. They transform numbers into a narrative, giving you and your audience a bird’s-eye view of the data landscape.
3. Highlighting differences: Uncovering outliers or deviations is a breeze with multiple lines. They emphasize disparities, helping you spot what’s unusual and business as usual.
4. Data analysis: The beauty of multiple lines lies in their analytical prowess. They’re not just pretty pictures but tools for dissecting data, unraveling correlations, and uncovering patterns.
5. Historical trends: If you’re exploring data over time, multiple lines breathe life into historical trends. Whether it’s tracking stock prices, temperature fluctuations, or sales figures, they provide context and a historical narrative.
6. Presentation: When it’s time to share your findings, multiple lines are your storytelling companions. They enhance your ability to convey complex information effectively. Be it in a boardroom presentation, a research paper, or an academic presentation, the possibilities are endless.

Moving on, here are common ways of misusing a line graph.

Common Ways of Missing a Line Graph

• Inability to Pinpoint Uneven Gaps Between Points

Sometimes, the line graph misses information of some bins, and if adequate care is not taken, these gaps would be read as phantom values, especially if the lines are not composed of distinct dots. If the number of points to the plot is scanty, then showing just lines won’t cut it – you’ve got to show all the points as well.

On the flip side, showing all the points could make it somewhat difficult to interpret the plot. To avoid such a situation, you’ve got to include a gap in the line. The gap shows where the values are missing.

• Using a zero-value baseline

If you’ve used online charting tools like histogram and bar charts, you probably know that the vertical axis starts with a zero baseline. With the line graphs, the case is somewhat different – there is no need for a zero-value baseline!

Here’s the thing, a line graph is more focused on identifying changes in value over time. It does not focus on measuring the magnitude of such values. You see, using a zero-value baseline may not be ideal at all times while using a line graph. Therefore, if adjusting the vertical axis range could make it easy to identify changes in your data values, go for it.

• Interpolating curve(s) between points

Typically, a straight line segment is used to connect one point from the other in a line graph. If you are not disciplined enough, you may fall into the aesthetic temptation of trying to link all points in the line graph using a smooth curve. Yes, using a smooth curve could be aesthetically appealing, but it’s not ideal when it comes to linking points in a line graph.

FAQs:

What do you mean by line chart?

A line chart displays how information changes over time. Creating it is simple – all you’ve got to do is plot a series of points and connect them with a line. Line charts are arguably the best tools for tracking changes in a data set over time.

What is a line chart used for?

Line charts are used for tracking changes over a period of time – it could be a long or short period. If you want to track small changes over time, then line graphs are probably your best shot. Yes, bar charts are not ideal for tracking small changes in any data set. Furthermore, you can use line graphs to compare changes in various data sets over the same time frame.

How to create Line Graphs?

Creating and analyzing line graphs can be done using ChartExpo. With ChartExpo, you can easily create line graphs within minutes by merely clicking on your computer screen. Yes, no coding skills are required.

Wrap Up:

Making line graphs is one of the most reliable ways of monitoring the correlation (or relationship) between multiple variables. With simple clicks, you can easily make line graphs in minutes using ChartExpo.

Regardless of how complex or simple your data is, data virtualization is a reliable way of representing it. This way, you get to pass the right message that resonates with your target audience.

Years ago, you had to use lots of spreadsheets to represent multiple data. Well, those days are over – and you get to do that by merely using visualization tools like the line graph.

One more thing…

To get started, you’ve got to generate lots of data by conducting solid surveys. Next, translate the raw data into digestible information using line graphs.

Now you understand what line graphs are, and the importance of making line graphs, what kind of data will you be representing using the tool?