Analyzing and Visualizing Data with Chachi PT Plus and Notable

Chachi PT Plus is a powerful tool for data analysis and visualization, and with the use of the Notable plugin, it can perform some pretty sophisticated analysis even with little prompting. One interesting feature of these tools is their ability to find data through API calls from certain types of websites, even if a data set isn't available or uploaded. In this article, we will explore an example of how Chachi PT Plus can perform this function.

Finding Data with Chachi PT Plus and Notable

To begin, Chachi PT Plus is requested to find data on the changes in GDP per capita around the world over the past few decades. The World Bank's open data is suggested as a good source, and Notable creates a workbook. The World Bank provides an API that allows the data to be fetched directly. A Python script is written to download the data.

One issue that arises is that sometimes Chachi PT Plus and Notable make mistakes, but they are excellent at correcting such mistakes and getting the desired analysis. In this case, the data wasn't in the expected format because it was in a compressed zip file. The code needed modification to handle the zip file, and an error occurred in reading the CSV file. However, by skipping the initial rows and reading the CSV file again, the GDP per capita data from the World Bank was successfully loaded.

Analyzing and Visualizing Data

Once the data is available, analysis and visualization can be performed. Chachi PT Plus is asked to perform analysis and charts on the data. The first task is to analyze the global trend of GDP per capita over the years by calculating the average GDP per capita for all countries and plotting it. The resulting chart shows a general increase in global average GDP per capita over time with fluctuations in periods of slower growth.

Chachi PT Plus then suggests that GDP per capita for specific countries be examined. It is noted that a simple average of all countries in the data set could be misleading in understanding overall GDP per capita since it weights all countries equally regardless of their size. Instead, population data is required to weight countries appropriately. Alternatively, the median GDP could be analyzed, or the focus could be on specific countries.

Small Multiples and Insights

Chachi PT Plus displays a small multiple of GDP per capita for all the G7 countries with each country shown on a separate chart. This allows the trend for each country to be examined individually. However, the chart is not aesthetically pleasing, and this issue is raised with Chachi PT Plus.

Further insight is then sought into why GDP per capita growth has varied between different G7 countries over time. Chachi PT Plus draws on its wider knowledge and suggests factors such as political stability, natural resources, and more.

Notable Dashboard

Notable provides a dashboard that displays the entire analysis, including code and outputs. This permanent record is helpful for reviewing and recalling work later.

Conclusion

Chachi PT Plus and Notable are powerful tools for data analysis and visualization. They can find data through API calls, even if a data set isn't uploaded or available. While mistakes can happen, they are corrected well. An aesthetic issue with a chart can be raised, and detailed explanations of the insights are given. The Notable dashboard provides a permanent record of analysis. Overall, these tools are highly effective and efficient for data tasks.