URL sharing is essential for online platforms and applications. It allows users to access specific resources on the internet, such as web pages, images, videos, files, and more. #APIs make sharing URLs even more seamless, like those offered by OpenDOSM
With URL sharing APIs, developers can provide users with a more streamlined experience, allowing them to share URLs and other data without leaving the application. This can drive more traffic to the platform and increase user engagement. #OpenData#API
A URL sharing API can improve the overall user experience, making it easier for users to quickly and easily share URLs and other data. This is especially useful for social media platforms and applications that rely heavily on user-generated content. #OpenDataAPI
URL sharing APIs can enhance collaboration between different users and applications. By sharing URLs and data between different services, developers can create a more integrated and collaborative ecosystem that allows users to work together more effectively. #OpenDataAPI
In addition, URL sharing APIs provide insights into how users interact with the platform. In #OpenDOSM, a number of URLs were shared and developers were able to see what data behaviour they display.
Want to access OpenDosm dataset in STATA? @azizulabllah shows you how! OpenDosm provides open data for everyone to analyze and make use. #opendata#STATA
Use this command:
“import delimited [openDOSM API URL dataset]”
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Making real-time public transportation information public, free, and usable is necessary to address the inconvenience, uncertainty, and other costs associated with public transportation, and it could lead to better solutions for commuters.
Real-time public transportation data could be provided through transport agencies @MOTMalaysia, private data firms or transport corporations, or public or community initiatives funded by donations.
If affordable, reliable public transport is a public good funded by taxpayers, then public transport data should be made public and free.
Preparedness equips us with the skills and resources to tackle data science challenges, while practice hones our abilities and helps us stay at the forefront of the constantly evolving field.
Preparedness refers to being ready or equipped for a certainsituation, task or event. In the context of data science, preparedness means having the necessary skills, knowledge, and resources to tackle a data science project or problem effectively.
This includes having a good understanding of relevant programming languages, data analysis techniques, and machine learning algorithms, as well as access to powerful computing resources.
Annual data alone may not be sufficient to make decisions on time-critical issues. Annual data provides a snapshot of a particular variable at a specific point in time, but it may not capture the dynamics and trends of that variable over time.
For time-critical issues, it's important to have access to more frequent data, such as monthly or even daily data. This type of data can provide a more detailed understanding of the issue and can help identify patterns and trends that may not be apparent from annual data alone.
Additionally, historical data can be useful for planning for future. By analyzing past trends and patterns, you can identify potential future scenarios and develop strategies to address them.
What is driving chicken price volatility today? Volatility refers to the rate at which the price of a financial asset, such as a stock or a commodity, changes over time. It is often used to assess the potential for price fluctuations.
High volatility means that the price of the asset can change significantly within a short period of time, while low volatility means that the price changes more slowly and steadily.
Volatility can be calculated using statistical methods, such as the standard deviation of daily price changes or the annualized rate of return over a certain period of time.