NOV Chart for .NET Features

SQL Server Reporting Services 2005, 2008, 2008R2, 2012, 2014, 2016, 2017 and 2019

Stock Chart

Stock charts are essential in data visualization for investors and traders to analyze historical market data and current trends, helping them to stay ahead of the curve, minimize risk, and maximize returns. These charts visualize stock prices over a period of time, such as days, weeks, months etc. The stock chart supports the two most common variations - candlestick and stick. Stock charts can easily be combined with build in technical analysis tools and indicators like moving averages, trend lines, and oscillators. By doing so, investors and traders can identify potential buy and sell signals, devise risk management strategies and determine entry and exit points for better investment decision-making.

Sample Table Format

Date	Open	High	Low	Close	Volume
2022-01-03	142.55	144.81	141.71	142.77	15574100
2022-01-04	141.23	141.79	138.64	139.53	17719200
2022-01-05	139.97	140.78	138.10	140.41	12134700

This is a simple example of a stock market data table with columns for Date, Open, High, Low, Close, and Volume. Each row represents a day's worth of data, with the date in the first column and the corresponding values for the other metrics in the subsequent columns. This format allows for easy sorting and analysis of the data and can be used to create charts and visualizations.

Best practices for using stock charts

Choose the right chart type: There are stock charts, such as line charts, candlestick charts, and bar charts. Choose the chart type best suits your data and the insights you want to convey.
Use a consistent time frame: When presenting historical stock data, use a consistent time frame throughout the chart. This allows viewers to easily compare trends and patterns over time.
Label your axes: Clearly label your chart's x and y axes so that viewers can understand the data. Use descriptive labels that include units of measurement and periods.
Avoid clutter: Avoid adding too much information to your stock chart, such as multiple indicators or excessive annotations. This can make the chart difficult to read and understand.
Use color strategically: Use color to highlight important data points or trends. However, be careful not to use too many colors or color schemes that are difficult to interpret.

Stick and candle styles are supported. Open High Low and Close High Low chart subtypes are also supported. XY Scatter mode (date-time stocks).

Polar


	Polar Area Chart

A Polar Area chart visually represents data in a 2-dimensional polar coordinate system. It shows a filled closed contour created by connecting data points defined by their distance from the center and angle of rotation. This chart is an effective way to display large sets of data with many categories or levels. Polar Area charts help identify trends or patterns in data, especially in circular distributions. They can also compare relative values across different categories or levels. Overall, Polar Area charts provide an intuitive and visually appealing way to communicate complex data in a concise and easily understandable format.

Supported Technologies

SQL Server Reporting Services 2005, 2008, 2008R2, 2012, 2014, 2016, 2017 and 2019

Polar Chart

A Polar Chart, also known as a Radial Chart, is a data visualization tool that displays data points in a polar coordinate system. In this coordinate system, each data point X value is interpreted as an angle and its Y value as a distance from the coordinate system center. This type of chart is beneficial for showing patterns and trends in data with directional or periodic characteristics, such as weather patterns, radar and sonar images, seasonal trends, and others.

Sample Table Format

Year	Category 1	Category 2	Category 3
2010	100	50	75
2011	120	60	80
2012	150	75	90
2013	180	90	100
2014	200	100	110
2014	220	110	120

The table displays data for three categories over five years in this example. Each row represents a different year, and each column represents a different category. The values in the table are used to create the Area Chart, where the area under each line represents the magnitude or value of each category. The chart can be used to visualize trends and patterns in the data over time and compare the relative values of each category.

Best practices for using a radar chart

Polar charts are a powerful tool for visualizing data that depends on angle and magnitude. To ensure that your polar charts effectively convey your data and insights, consider the following best practices:

Choose an appropriate data set: Polar charts are most effective for data sets that depend on angle and magnitude. Consider whether this chart type is the best choice for your data.
Label your axes: Label your angle and value axes to ensure users can easily interpret the data. Use clear and concise labeling that is easy to understand.
Use appropriate scaling: Choose a proper scaling for your chart to ensure all data points are visible and easily interpreted. Consider using logarithmic scaling for data sets with a wide range of magnitudes.
Optimize axis positioning: Ensure that your angle and value axes are positioned to maximize clarity and readability. Use evenly spaced intervals and appropriate ranges to optimize axis positioning.
Use color coding or shading: To enhance the user experience, consider using color coding or shading to provide a clear visual representation of data.

Polar line, point, area, range, and vector types.

Box and Whiskers


	Box and Whiskers Chart

A box and whiskers chart is a powerful type that provides a quick and easy summary of a dataset's overall data distribution. It presents the data in the form of a box and whiskers series, which enables the viewer to see the data's range, median, quartiles, and outliers at a glance. This makes it an excellent tool for identifying patterns and trends in the data and detecting any anomalies or outliers that may be present. With its ability to convey complex information clearly and concisely, a box and whiskers chart is a valuable resource for making informed decisions based on data.

Supported Technologies

SQL Server Reporting Services 2005, 2008, 2008R2, 2012, 2014, 2016, 2017 and 2019

Box and Whiskers Chart

A Box and Whisker chart, or a Box plot, is a powerful chart for visualizing statistical data. It displays the distribution of a dataset using quartiles and outliers, allowing users to quickly identify patterns and trends. The chart consists of a box representing the middle 50% of the data, with a line inside indicating the median value. The chart displays the minimum and maximum values as whiskers that extend from the box, and any outliers are represented as individual data points beyond the whiskers. Furthermore, it is highly customizable with options to adjust colors and labeling, making it an effective tool for data analysis.

Sample Table Format

Sample Name	Minimum	Lower Quartile	Median	Upper Quartile	Maximum
Sample A	5	8	10	15	20
Sample B	10	12	15	18	25
Sample C	8	10	12	16	22

This table represents three different samples of numerical data, each with five statistical measures. The minimum and maximum values indicate the range of values in each sample, while the lower and upper quartiles represent the 25th and 75th percentiles, respectively. The median is the value that divides the data into two halves. Comparing the values across the samples, we can observe differences in their distributions, ranges, and central tendencies. The box and whisker chart is a valuable tool to visually compare these characteristics and identify any outliers or unusual patterns in the data.

Best practices for using box and whiskers charts

Use Box and Whiskers charts to compare data: Box and Whiskers charts are excellent for comparing data between different groups. Use them to compare data points across multiple categories or periods.
Label your chart clearly: It's important to label it with a clear and descriptive title and label the axes with meaningful units of measure.
Ensure your data is accurate: Check it carefully before creating your chart to ensure it is accurate and up-to-date.
Use colors carefully: Sparingly and purposefully highlight important information in your chart. Avoid using too many bright colors that may distract from the data
Include relevant statistical information: Include relevant statistical data in your chart, such as the median, quartiles, and outliers.
Choose an appropriate scale: Choose a scale appropriate for the displayed data. A smaller scale may be more suitable if the data is tightly clustered.
Avoid clutter: Avoid cluttering your chart with too much information. Use a clear and simple design to make it easy to interpret the data.

Box and whiskers plots are very helpful in interpreting the distribution of data. Each box and whiskers item represents a set of values and displays statistical information for it like minimum, maximum and median values, upper and lower quartiles, outliers, and optionally a mean value.

Vector

NOV vector charts display arrows in 2D space. A vector data item is defined by two points (begin - end) and is represented by a single arrow. An arrowhead is placed at the endpoint to indicate the vector direction.

Range

Supports the display of 2D shapes defined by the begin/end values of their bounding boxes. It can be used for the display of histograms, bars with custom sizes, etc.

Combo

Combo Charts are used to combine certain series types within the same chart area. Series types are specified per values data groupings. There are many per series type options.

Tree Map


	Tree Map Chart Series

Tree maps display hierarchical (tree-structured) data as a set of nested rectangles. Each branch of the tree is given a rectangle, which is then tiled with smaller rectangles representing sub-branches. A leaf node's rectangle has an area proportional to a specified value versus the total aggregated value of all leaf nodes.

Supported Technologies

SQL Server Reporting Services 2005, 2008, 2008R2, 2012, 2014, 2016, 2017 and 2019

Tree Map Chart

The Tree Map Chart Series is a type of chart series that enables you to create visually appealing and interactive treemap charts. Treemap charts are a type of visualization that displays hierarchical data using nested rectangles or boxes, where the size and color of each rectangle represent different variables.
The TreeMap Chart Series is widely used in data analysis, finance, and business intelligence, enabling users to represent complex data in an easy-to-understand format. The TreeMap Chart Series allows users to create charts that display data in a hierarchical structure, allowing them to drill down into the data and analyze it at different levels of granularity.
One of the key advantages of the TreeMap Chart Series is that it allows users to visualize large amounts of data in a small space. The TreeMap Chart Series automatically adjusts the size of each rectangle based on the data, ensuring that the chart is visually appealing and informative. Additionally, the TreeMap Chart Series allows users to customize the color and style of each rectangle, making it easy to highlight specific trends or data points.
TreeMap Chart Series is a valuable tool for anyone who needs to visualize hierarchical data. It provides an intuitive and easy-to-understand format for displaying complex data sets, making it an ideal tool for data analysts, finance professionals, and business intelligence experts.

Sample Table Format

Group	Subgroup	Value
A	A1	10
A	A2	20
B	B1	15
...	...	...

The data is organized into groups and subgroups in this table, with a corresponding value for each subgroup. This table format can be easily visualized using a TreeMap Chart Series, with each group represented as a large rectangle and each subgroup represented as a smaller rectangle within the group rectangle. The size and color of each rectangle can be customized to reflect the value of the subgroup, making it easy to identify trends and patterns within the data.

Best practices for using tree map charts

Keep it simple: The TreeMap Chart Series is a powerful tool, but avoiding cluttering the chart with too much information is important. Stick to a few key variables and try to make the chart as easy to understand as possible.
Use color wisely: Color can be a powerful tool for highlighting trends or patterns within the data, but it can also be overwhelming if misused. Use color sparingly and ensure that each color has a clear meaning
Group similar data: Grouping similar data together can make identifying patterns within the data easier. Consider grouping data by category, region, or period, depending on your data set.
Provide context: Always provide context for your chart by including a title, axis labels, and a legend. This will help users understand what they are looking at and interpret the data correctly.

Tree maps display hierarchical (tree-structured) data as a set of nested rectangles. Tree maps allow you to easily see patterns that would be difficult to spot in other ways, such as if a certain node value changes by a large amount or the relative node value vs. the other node values. The second advantage of tree maps is that, by construction, they make efficient use of space. As a result, they can legibly display a large number of items simultaneously on the screen.

Heat Map


	Heat Map Chart Series

A Heat Map is a 2D representation of data where the individual values are contained in a matrix and are represented as colors, which are taken from an associated palette.

Supported Technologies