Hi and welcome back. In this video we're going to use Tableau to link multiple datasets. This lets analysts compare all datasets in the same visualization, visualize comparisons and combinations of data, and share more complex projects. You can put this video on one side of the screen and follow along in another window. You might notice your screen is slightly different from the video. That's okay. Tableau updates his interface from time to time, but the general steps will stay the same. And feel free to pause this video as you work in your own Tableau workspace before continuing to the next step. To begin, we're going to need to download the four datasets we'll use for this activity, click the link to create a copy of the data sets and download them. If you don't have a google account, download the data sets directly from the attachments. Now imagine this scenario you're working as a data analyst for a policy research institute for your current project. You need to create a visualization that shows the CO2 emissions per capita for each country from 2000-2011. You'll also provide information about each country's population GDP and energy use. All right, let's get started. First log into Tableau public. If you haven't created an account, refer to the earlier reading, logging into Tableau public. Go to the circle in the upper corner of the window, then choose my profile. From there, select Create a Viz. This will open the Tableau Public interface. The connect to data window will pop up. From here, you can go to the files tab and upload the CO2 dataset. Now go to the data source tab, then the connections column. From here, choose the plus icon to add another dataset. First add energy, then add GDP total and total population. Now, we'll have four datasets loaded into Tableau. You can proceed to linking them with joins. Tableau has already added energy into the multiple connections area. We can remove it by dragging it back to the connections column. Now let's create joins. As a reminder, Inner and outer joins are types of relationships that can be used to combine data based on common columns of information. To set up our first join will select CO2 under connections. Beneath that in the sheets section, click and drag CO2 data cleaned to the multiple connection section. Then double click the box created by the dataset. This opens the physical table and lets us create joins. To set the first join, select the energy dataset under connections and drag the energy sheet beneath it to the right side of the CO2 data clean box. A pop up window for a join will appear. It will automatically populate with year from CO2 data cleaned and year one from energy. If not, put year on the left side of the chart and year one on the right side. Then choose add from join clause under year. Select country name from the drop down on the left side and country on the right side. After that, use the X to close the drop down menu. We need to fix something in our dataset. Year and year one have a number sign above them. We can click those number signs and select date instead to change the data type for each column. Now join the other datasets choose GDP total under connections. Then under sheets drag the GDP total sheet into the white space underneath the energy box. The pop up window should already be populated with year one. Under data source and year GDP total under GDP total before adding any additional joins the data type for year GDP total needs to be changed. Will make its data type date just like we did with the other year columns. Now continue setting the join, choose the Venn diagram between energy and GDP total. Then add new join clause under year one. A drop down menu will appear. Under C02 to data cleaned, select country name. Then the empty field under GDP total across from country name. Set the right side of the joint to Country one. Then close the join pop up. We'll repeat this process for total population, The last data set we downloaded. When we drag the sheet to create the join, the window should already be populated with year under data source. And year total population, under total population change year total population to the date data type to match the other year columns. Then select the Venn diagram to edit the join and click add new join clause under year. Under C02 data cleaned, choose country name then on the right side of the row, country total population. Close the pop up. If you haven't yet be sure to update your data by clicking on the update now button. Nice. You've joined four different sources of data. Check out your new data set while your data set C02 went from 1960 to 2011, your other datasets went from 2000-2015. The intersection the years they have in common only includes 2000 to 2011. This is the time span that we need. However, there are some changes we still need to make. Some of the data types need to be converted. Similar to when you change your year columns to date types. You'll need to change the energy use and current GDP columns. Above the energy used column is an ABC icon. This means is a string type. Select it to open a drop down and change it to number decimal current GDP is also a string type but needs to be a whole number instead. Choose the ABC icon to change it to number whole. All right now we get to make our visualization. To begin choose the sheet one tab. You'll notice a column on the left side of the screen. Under CO2 data cleaned drag country name to the detail square, drag CO2 per capita to the color square, then choose the square and edit colors. Select the pallete drop down and change it from automatic to red, green diverging, check the boxes for stepped color. And reversed because green is generally viewed as a good thing when it comes to CO2 emissions. You want the colors to move toward red as emissions worsen, click the show advanced drop down, then the start and end boxes. Put zero into the start Column and 62 at the end column, then closed the window, drag year from under C02 data cleaned into the filters area. Choose years, next, all, and then okay. In the filters box, right click on year year. Select show filter. The filter will appear on the right side of the screen. On the far right side of the screen, choose the arrow to the right of year, select single value. Now the areas will be colored only for the values of each year. Select any year between 2000 and 2011 to view that year's CO2 emissions. Make sure to save your progress by clicking the save icon or hovering over the file tab and selecting Save. If you are asked to create an extract, return to the data source tab and click create extract, then click save again. Congratulations, you've linked your data and made a comprehensive data viz in tableau. The more visualizations you make, the more you'll be able to share complex analysis and insights.