data:image/png;base64,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:image/png;base64,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2.0 Explore the blocks already written for you and understand how they work.These data sets are also given. Look inside.You will write these blocks below. Right click and edit.3.0 Develop code for the draw axes block. It should draw the horizontal and vertical axes based on the given stage coordinates of the origin x0, y0 and the given length, height information.4.0 Explore the basic label block included in the starter project. Try changing the location and direction of the drawing sprite.5.0 Use the basic label block to develop code for the more elaborate label block that will place a label with the inputted specifications (text, size and direction.)6.0 Develop code for the draw bar block. It should draw a vertical bar (a line with the given width and height) straight up from the current location with a label placed underneath the bar.7.0 Develop code for the draw bars block, which should draw a series of labelled bars of the desired width and an appropriate height that start on the left and continue to the right. In order to properly level the bars and the labels you may need to refer to the global variables x-origin, y-origin.8.0 Develop code for the label vertical axis block so that it labels the vertical axis based on the specified inputs. For simplicity, you can assume that the labels will always split the vertical axis into 10 equal parts (using 11 tick marks) like this:9.0 Now you are ready to put everything together and develop code for the Bar Graph drawing block for a given data list input. Fill in the blanks.10.0 When everything is done, the following code, with a few extra labels for the graph title, should produce a bar graph as shown below: 11.0 Your coding should be general enough to accommodate a new set of data (also included in your starter file):12.0 In collaboration with your partner, compare the two bar graphs. What insights does each graph provide about CO2 emissions? Is one better than the other?Fill in the blanksLABEL will stamp text on the stage at the given font size. The direction of the text is the direction the sprite is facing, and color will match the pen color.Hello!121datamapmany1data lists11110i121cont3catchtagcontcatchtagSpriteSpriteA direction is missing in this code.Not all parts are present and not in correct order.Not all pieces of the puzzle are given.Not all items are present.-200-90