Map.fillcontinents(color=’coral’,lake_color=’aqua’) Map = Basemap(projection=’ortho’,lat_0=0, lon_0=0) It only takes a few lines of code to draw a world map: It is no exaggeration to say that basemap is the best third-party library for python map visualization.īasemap is developed based on matplotlib, so it has all the functions to create a data visualization, and must be used with matplotlib. If you are interested in it, you can pull out the sample code and run. The most important is it can realize dynamic interaction.īokeh‘s official website provides detailed map visualization solutions. First is bokehīokeh is good at making interactive graphics, and of course, it is not inferior to map data visualization.īokeh supports the geographic visual display of Google maps and JSON data. Next, I will introduce these three low-key python map visualization tools. The Python map visualization library has well-known pyecharts, plotly, folium, as well as slightly low-key bokeh, basemap, geopandas, they are also a weapon that cannot be ignored for map visualization. Python is one of the easier to get started in programming languages, and can very efficiently implement map data visualization of large amounts of data. I hope you can find a tool that meets your needs. In this article, I will introduce the advantages and disadvantages of the above three types of tools, and focus on the map data visualization in python. Tools to achieve map data visualizationĪt present, there are many tools that can implement map data visualization, which can be divided into three types: programming, platform, and software:įor most people, Excel has always been the first choice, but is Excel really the best tool for map visualization? Good map visualization integrates information into geographic context, contains a lot of information, and is extremely aesthetically pleasing and shocking. It can’t be denied that Maps are the most commonly used form of data visualization today. In layman’s terms, map visualization can present geographic data more clearly and directly. By visualizing the data with regional characteristics or the results of data analysis on the map, users can more easily understand the laws and trends of data. To be simple, map data visualization is to transform geographic data into a visual form. Tools to achieve map data visualizationīefore we start to make map data visualization, we need to know what is it?. list function will be used to convert it to an actual list in most of the examples. It’s an efficient memory address representation. This is because map function returns a map object (which may look weird). ** Most examples will make use of list function for data conversion. These Python examples can hopefully make these concepts more clear in a demonstrative way. One step at a time, you will be an amazing Python programmer.īelow you will find some Python map function examples we have created for you. But there are many concepts so don’t overwhelm yourself either. So, it’s important to have good command of the syntax and functions especially in the beginning of a journey of programming language learning and practice a lot. Usually in programming, there are multiple ways to achieve a result, and particularly so with Python. * It’s good to know different Python objects when working with iterables and functions (list comprehension, dict comprehension, map, filter, zip etc.) as these work in harmony.
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