> For the complete documentation index, see [llms.txt](https://academy.dnanexus.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://academy.dnanexus.com/mlaccelerator/dataprofiler/columnlevelscreen.md). # Column Level Screen A license is required to access the Data Profiler on the DNAnexus Platform. For more information, please contact DNAnexus Sales (via ). ### String Data Column-level screen shows a string column For columns containing string data, the data profiler will display several statistics and charts to help analyze the data. The statistics include: * The missing rate, expressed as a percentage of the missing values in the column. * The number of unique values present in the column. * The average length of the strings in the column. * The standard deviation, which measures the amount of variation in the string lengths. The charts provided include: * Character Length Distribution Chart: This chart shows how the lengths of the strings are distributed. By hovering over different parts of the chart, you can view the range of character lengths and how frequently each range occurs. * Boxplot: The boxplot provides a visual summary of the data in terms of its distribution, showing the maximum value, Q3 (upper quartile), median, Q1 (lower quartile), and the minimum value. * Top 10 Prevalent Values bar chart: This chart displays the top values that occur most frequently in the column. You can select how many top records to display using a dropdown list. By hovering over the bars, you can see the exact count of records for each value. ### Numeric Data Column-level screen shows a float column For columns containing float data, the data profiler provides several statistics and charts to help analyze the data. The statistics include: * The missing rate, displayed as a percentage of missing values. * The standard deviation, which measures the spread of the data values. * The interquantile range For columns containing numeric (Float or Integer) data, the Data Profiler provides a range of statistics and visualizations to help you understand data distribution and quality. The statistics include: * Missing Rate: The percentage of missing values in the column. * Standard Deviation: A measure of how widely the values are spread around the mean. * Interquartile Range (IQR): The range between the 25th and 75th percentiles, used to understand the spread of the middle portion of the data and identify potential outliers. The charts provided include: * Distribution Chart: This chart displays the distribution of values in the column. You can hover over the chart to view the range of values and their frequencies. * Boxplot: The boxplot visually represents the distribution of the data, showing the maximum value, Q3 (upper quartile), median, Q1 (lower quartile), and the minimum value. ### Datetime Column-level screen shows a datetime column For columns containing datetime data, the data profiler provides several statistics and charts for in-depth analysis. The statistics include: * The missing rate, displayed as a percentage of missing values. * The standard deviation, measuring the dispersion of the datetime values. * The percentage by date format, showing the distribution of various date formats in the column. The charts provided include: * **Distribution Chart:** This chart shows the distribution of datetime values in the column. You can hover over the chart to view the range of values and their frequencies. * **Boxplot:** The boxplot visually represents the distribution of the datetime data, displaying the maximum value, Q3 (upper quartile), median, Q1 (lower quartile), and the minimum value. * **Radar Chart:** This chart displays the frequency of values, grouped by year, month, or day. You can change the grouping option using the dropdown at the top. ## Resources [Full Documentation](https://documentation.dnanexus.com/) To create a support ticket if there are technical issues: 1. Go to the Help header (same section where Projects and Tools are) inside the platform 2. Select "Contact Support" 3. Fill in the Subject and Message to submit a support ticket.