Manual zoom level fix .geojson without tippecanoe

Mapbox Studio environment automatically chooses max and min zoom levels for uploaded tilesets. In the .geojson file format case we can modify it manually.

Комментарии

Отправить комментарий

Популярные сообщения из этого блога

Common Data Analyst interview questions

Изображение
It's a one of great videos I used when have been preparing for my first MEAL officer position interview. The video not focused on some app or tecnologie qusetions, but it can give you an advice, what kind of topics you may meet at the interview. If you aren't focused on the senior DA position, you should repeat what you have already known, but there are too many different information and this video can give a hint about priority knowledge areas.  
Далее...

Day 1. SQL Introduction

Изображение
It's not enought informative video, but it can be useful for beginners, who don't know what start with. The video contains short description of SQL language basics and gives instruction how to install SQL engine + SQL Server Management Studio from Microsoft.
Далее...

Power BI simple custom line chart with Python visual and matplotlib

Изображение
Step-by-step instruction: To convert an existing line chart into a Python visual, you will utilize the matplotlib library. Select your visual and change its type to Python by selecting correspond button on the right panel. Begin by importing the necessary module with the following code: import matplotlib.pyplot as plt . Define the x-axis and y-axis variables for your chart. For the x-axis, you will use the "month name" column from your dataset. For the y-axis, you need to define three variables: y1 for the current year's profit, y2 for the previous year's profit, and y3 for the profit growth or decline. Make sure to accurately identify and assign the corresponding columns from your dataset to these variables. Proceed to define the plots for each y-axis variable using the plt.plot() function. You will create three separate plots, one for each variable. Begin with y1 by using plt.plot(x, y1) where x represents the x-axis values and y1 represents the y-axis ...
Далее...