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Note: The online trial of JupyterLab is a good place to start if you want to experiment with programming in Python, but for continued use in the future, it is recommended to install the Conda package and environment management system and JupyterLab locally on your system. If your session has expired, start a new one from, and use the interface to upload your saved notebook to continue where you left off. TREEMAP CHART IN MATPLOTLIB DOWNLOADMake sure to download and save your notebooks locally before leaving the computer. Take note that this JupyterLab session is hosted on, and it will timeout after ~15 minutes if inactive. ![]() Try refreshing the window if loading stalls. A cloud-hosted ready-to-use online JupyterLab environment will be activated after a short wait. To try a notebook online, just open, and click Try JupyterLab. We will be using JupyterLab, a modern web-based notebook interface for Python, that requires no installation on the user’s part. TREEMAP CHART IN MATPLOTLIB CODESharing small code projects (such as visualizations!) generally becomes much simpler with the notebook approach since you can save the entire notebook and send it to others. ![]() This makes working with code and experimenting with changing parameters much more flexible and is particularly suitable for interactive data exploration, where the Python programming language shines. In a notebook, on the other hand, the code is broken down into cells, which can be run one at a time, displaying results right in the editor. The traditional way of programming would be to write some code in a text file, then building and running it to generate an output. CP12: Financial services n.e.c., personal care, insurance, personal effects n.e.c., and other services n.e.c.CP11: Catering services and accommodation services.CP10: Pre-primary and primary education, tertiary education, and education not definable by level.CP09: Recreational and cultural services, package holidays, audio-visual, photographic and information processing equipment, newspapers, books and stationery, other recreational items and equipment, gardens and pets, and other major durables for recreation and outside.CP08: Telephone and telefax services and postal services.CP07: Operation of personal transport equipment, purchase of vehicle and transport services.CP06: Out-patient services and medical products, appliances and equipment.CP05: Goods and services for routine household maintenance, furniture and furnishings, carpets and other floor coverings, household appliances, glassware, tableware, and household utensils, and household textiles.CP04: Imputed rentals for housing, actual rentals for housing, electricity, gas and other fuels, water supply and miscellaneous services related to the dwelling, and maintenance and repair of the dwelling.CP02: Alcoholic beverages, tobacco, and narcotics.CP01: Food and non-alcoholic beverages.The treemap shows the categories of different expenditures. Interpretation of a treemap can be considerably more difficult, however, and its use is best reserved for cases where there are more individual subgroups or pieces that can be feasibly presented in the other two chart types, and when the overall goal is to only provide a general overview of a hierarchy. Usually, the same type of data that can be depicted in 100% stacked bar charts or pie charts can be utilized in a treemap-that is to say, quantitative data about a whole and its inherent subparts. Treemaps are useful, namely, in presenting the distribution of parts as a whole. ![]() The treemap is very similar to the Marimekko plot, also called a mosaic plot. Treemaps are composed of various sizes of rectangles that fit together to form a whole, often rendered with the help of an algorithm that ensures the shapes are as similar as possible throughout for easier visual comparison. Treemaps can have many levels of nested hierarchies laid one atop another, though with more complexity, of course, the chart’s interpretation becomes more difficult for the reader. The treemap is a visualization with a tree-like content structure used to show the hierarchical distribution of the parts of a whole, much like 100% stacked bar charts. ![]()
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