Category: Big Data & Analytics

Tableau – Basic Filters ”; Previous Next Filtering is the process of removing certain values or range of values from a result set. Tableau filtering feature allows both simple scenarios using field values as well as advanced calculation or context-based filters. In this chapter, you will learn about the basic filters available in Tableau. There are three types of basic filters available in Tableau. They are as follows − Filter Dimensions are the filters applied on the dimension fields. Filter Measures are the filters applied on the measure fields. Filter Dates are the filters applied on the date fields. Filter Dimensions These filters are applied on the dimension fields. Typical examples include filtering based on categories of text or numeric values with logical expressions greater than or less than conditions. Example We use the Sample – Superstore data source to apply dimension filters on the sub-category of products. We create a view for showing profit for each sub-category of products according to their shipping mode. For it, drag the dimension field “Sub-Category” to the Rows shelf and the measure field “profit” to the Columns shelf. Next, drag the Sub-Category dimension to the Filters shelf to open the Filter dialog box. Click the None button at the bottom of the list to deselect all segments. Then, select the Exclude option in the lower right corner of the dialog box. Finally, select Labels and Storage and then click OK. The following screenshot shows the result with the above two categories excluded. Filter Measures These filters are applied on the measure fields. Filtering is based on the calculations applied to the measure fields. Hence, while in dimension filters you use only values to filter, in measures filter you use calculations based on fields. Example You can use the Sample – Superstore data source to apply dimension filters on the average value of the profits. First, create a view with ship mode and subcategory as dimensions and Average of profit as shown in the following screenshot. Next, drag the AVG (profit) value to the filter pane. Choose Average as the filter mode. Next, choose “At least” and give a value to filter the rows, which meet these criteria. After completion of the above steps, we get the final view below showing only the subcategories whose average profit is greater than 20. Filter Dates Tableau treats the date field in three different ways while applying the date field. It can apply filter by taking a relative date as compared to today, an absolute date, or range of dates. Each of this option is presented when a date field is dragged out of the filter pane. Example We choose the sample – Superstore data source and create a view with order date in the column shelf and profit in the rows shelf as shown in the following screenshot. Next, drag the “order date” field to the filter shelf and choose Range of dates in the filter dialog box. Choose the dates as shown in the following screenshot. On clicking OK, the final view appears showing the result for the chosen range of dates as seen in the following screenshot. Print Page Previous Next Advertisements ”;

Tableau – Filter Operations ”; Previous Next Any data analysis and visualization work involves the use of extensive filtering of data. Tableau has a very wide variety of filtering options to address these needs. There are many inbuilt functions for applying filters on the records using both dimensions and measures. The filter option for measures offers numeric calculations and comparison. The filter option for dimension offers choosing string values from a list or using a custom list of values. In this chapter, you will learn about the various options as well as the steps to edit and clear the filters. Creating Filters Filters are created by dragging the required field to the Filters shelf located above the Marks card. Create a horizontal bar chart by dragging the measure sales to the Columns shelf and the dimension Sub-Category to the Rows shelf. Again drag the measure sales into the Filters shelf. Once this filter is created, right-click and choose the edit filter option from the pop-up menu. Creating Filters for Measures Measures are numeric fields. So, the filter options for such fields involve choosing values. Tableau offers the following types of filters for measures. Range of Values − Specifies the minimum and maximum values of the range to include in the view. At Least − Includes all values that are greater than or equal to a specified minimum value. At Most − Includes all values that are less than or equal to a specified maximum value. Special − Helps you filter on Null values. Include only Null values, Non-null values, or All Values. Following worksheet shows these options. Creating Filters for Dimensions Dimensions are descriptive fields having values which are strings. Tableau offers the following types of filters for dimensions. General Filter − allows to select specific values from a list. Wildcard Filter − allows to mention wildcards like cha* to filter all string values starting with cha. Condition Filter − applies conditions such as sum of sales. Top Filter − chooses the records representing a range of top values. Following worksheet shows these options. Clearing Filters Filters can be easily removed by choosing the clear filter option as shown in the following screenshot. Print Page Previous Next Advertisements ”;

Tableau – Top Filters ”; Previous Next The Top option in Tableau filter is used to limit the result set from a filter. For example, from a large set of records on sales you want only the top 10 values. You can apply this filter using the inbuilt options for limiting the records in many ways or by creating a formula. In this chapter, you will explore the inbuilt options. Creating a Top Filter Using the Sample-superstore, find the sub-category of products which represents the top 5 sales amount. To achieve this objective, following are the steps. Step 1 − Drag the dimension Sub-Category to the Rows shelf and the Measure Sales to the Columns shelf. Choose the horizontal bar as the chart type. Tableau shows the following chart. Step 2 − Right-click on the field Sub-Category and go to the tab named Top. Here, choose the second radio option by field. From the drop-down, choose the option Top 5 by Sum of Sales. On completion of the above step, you will get the following chart, which shows the top 5 Sub-Category of products by sales. Print Page Previous Next Advertisements ”;

Tableau – Extracting Data ”; Previous Next Data extraction in Tableau creates a subset of data from the data source. This is useful in increasing the performance by applying filters. It also helps in applying some features of Tableau to data which may not be available in the data source like finding the distinct values in the data. However, the data extract feature is most frequently used for creating an extract to be stored in the local drive for offline access by Tableau. Creating an Extract Extraction of data is done by following the menu – Data → Extract Data. It creates many options such as applying limits to how many rows to be extracted and whether to aggregate data for dimensions. The following screen shows the Extract Data option. Applying Extract Filters To extract a subset of data from the data source, you can create filters which will return only the relevant rows. Let’s consider the Sample Superstore data set and create an extract. In the filter option, choose Select from list and tick mark the checkbox value for which you need to pull the data from the source. Adding New Data to Extract To add more data for an already created extract, you can choose the option Data → Extract → Append Data from File. In this case, browse the file containing the data and click OK to finish. Of course, the number and datatype of columns in the file should be in sync with the existing data. Extract History You can verify the history of data extracts to be sure about how many times the extract has happened and at what times. For this, you can use the menu – Data → Extract History. Print Page Previous Next Advertisements ”;

Tableau – Date Calculations ”; Previous Next Dates are one of the key fields which is extensively used in most of the data analysis scenarios. Hence, Tableau provides a large number of inbuilt functions involving dates. You can carry out simple date manipulations such as adding or subtracting days from a date. You can also create complex expressions involving dates. Following are the steps to create a calculation field and use date functions in it. Create Calculated Field While connected to Sample superstore, go to the Analysis menu and click ‘Create Calculated Field’, as shown in the following screenshot. Calculation Editor The above step opens a calculation editor, which lists all the functions available in Tableau. You can change the dropdown value and see only the functions related to Date. Create a Formula Now, find out the sales volume along with the difference in the date of sales in months from 21st March 2009. For this, create the formula as shown in the following screenshot. Using the Calculated Field Now to see the created field in action, you can drag it to the Rows shelf and drag the Sales field to the Columns shelf. Also drag the ship Date with months. The following screenshot shows the Sales values. Print Page Previous Next Advertisements ”;

Tableau – Data Blending ”; Previous Next Data Blending is a very powerful feature in Tableau. It is used when there is related data in multiple data sources, which you want to analyze together in a single view. As an example, consider the Sales data is present in a relational database and Sales Target data in an Excel spreadsheet. Now, to compare actual sales to target sales, you can blend the data based on common dimensions to get access to the Sales Target measure. The two sources involved in data blending are referred as primary and secondary data sources. A left join is created between the primary data source and the secondary data source with all the data rows from primary and matching data rows from secondary data source. Preparing Data for Blending Tableau has two inbuilt data sources named Sample-superstore and Sample coffee chain.mdb which will be used to illustrate data blending. First load the sample coffee chain to Tableau and look at its metadata. Go to the menu – Data → New Data Source and browse for the sample coffee chain file, which is a MS Access database file. The following screenshot shows the different tables and joins available in the file. Adding Secondary Data Source Next, add the secondary data source named Sample-superstore by again following the steps – Data → New Data Source and choosing this data source. Both the data sources now appear on the Data window as shown in the following screenshot. Blending the Data Now you can integrate the data from both the above sources based on a common dimension. Note that a small chain image appears next to the dimension named State. This indicates the common dimension between the two data sources. Drag the State field from the primary data source to the rows shelf and the field Profit Ratio from the secondary data source to the Columns shelf. Then, select the bullet chart option from Show Me to get the bullet chart shown in the following screenshot. The chart shows how the profit ratio varies for each state in both the superstore and coffee chain shops. Print Page Previous Next Advertisements ”;