In this article, we will look at some Time Series dataset sources which can be useful for machine learning beginners to create Time Series Analysis Projects. Before going through the data sets, let us first understand what is Time Series Analysis.
Understanding Time Series Analysis
Time series data is a type of data where the data collected has an association with a time component. This involvement of the component of time can be as small as seconds and sometimes as big as years or decades. This time-series data is generally monitored in industrial and corporate sectors.
Time series analysis is a method where time is the independent variable, using the time component we are trying to analyze other parameters and sometimes also predict them for the future. The advantage which time series analysis provides is it helps in detecting the internal relationship between the data. This relationship can be either an autocorrelation, a trend or sometimes seasonal variation.
Time series analysis is built with either of the two objectives. One is to decipher the reasoning behind the observed data. The other objective is to build a model and perform forecasting, monitoring or sometimes feedback as well. Time series analysis is highly feasible with its main application covering Economic Forecasting, Budgetary and Stock Market Analysis, Process and Quality Control, Workload Projections and Census Analysis.
Let us now have a look at the time series datasets.
Time Series Datasets
Time Series Data by World Bank
These datasets are hosted and uploaded by World Bank. The data type of all these datasets is time series, thus they are appropriate for time series analysis projects. There is a huge variety of datasets available over there with topics like transportation, finance, agriculture, trade and many more. So it is highly recommended to explore this source for your benefit.
- Time Series Analysis of data
- Data Visualization of time series data
- Time series prediction
World Bank Data for Countries
This dataset is again hosted by the World Bank. Here the data is available through two distinguishing parameters i.e. country or indicators. We can obtain data on the basis of various pointers like agriculture, aid effectiveness, climate change, education and many more subdivisions within these indicators. This dataset is different from the above one because there data type was time series but here the information is presented by combining information of country or indicators along with time.
- Data Visualization of various indicators for different countries
- Geographic Visualization of countries through indicators
- Predicting values of various indicators using available data for different countries
- Comparing different countries over different indicators
- Understanding which pointers are contributing the most to the growth of a country and which are the least useful.
NOTE: Data from World Bank can be downloaded in three formats i.e. CSV, EXCEL, and XML.
Google Trends Data
This is a very interactive source of the dataset. Here google has shown the visualization of various search results that take place all over the world in different span of time. The most striking feature of google trends is the feature of displaying the results in the form of time series analysis. Along with this, users can alter the available variables like Region of data, duration of data, to look at different results with the same data. Moreover, we can also download data from this website.
NOTE: For downloading data, you must look for a downward arrow on the top right corner of the time-series graph built for each search result.
- Time Series Analysis of various search results dataset
- Data Visualization of results
- Geographic Visualization of search results
- Making predictions with the help of search data
It’s time to conclude this article where we saw what actually time-series data is all about. We also learned how time-series data is used for performing time series analysis. With this, we identified some really handy open-source datasets which can be used for time series analysis projects and also for learning geographic visualization.