Beginner's guide to Alphacast

Alphacast is an integrated platform for economic and financial analysis. Think GitHub, but for economy and finance.

There are many things you and your team can do with Alphacast. Download and create data, integrate with R or Python or Power-bi, create interactive charts, maps, insights, or full auto-updated presentations.

In this guide, we will guide you through the basics of Alphacast, follow the links for more in-depth information

Downloading your first dataset

Let's start by finding some data you need, say, for example. Argentina's Consumer Price Index.

  1. Go to Search at the top right of your screen
  2. Type "Inflation Argentina", search and select "Inflation - Argentina - INDEC - Consumer Price Index - Groups - Monthly"
  3. Click Filter on the top right and then "Nivel General" followed by the transformation "Year over Year". You should be logged in to do this.
  4. Click Download on the top right and select either CSV o XLSX, and whether you want a transposed version of the data. You can also download the Ids of the variables by clicking on that option.
  5. That's it. The Browser will start downloading your dataset.


You can also integrate the dataset to your excel through some of our download options.

Creating your first pipeline

With pipelines you can process the data within the platform. A pipeline is a sequence of steps, transformations and others to be applied to a particular dataset that has the characteristic of updating automatically every time a data is updated. There are two different ways to do this:

  • From scratch: click Create new on the upper right corner and then Pipeline.
  • From any dataset: you can create a pipeline from any dataset. When entering to the dataset view, on the right you will find the button Create Pipe

Both options will lead you to the Pipeline Engine. Here you will need to choose the repository where the pipeline will be stored and select a name for it. After that is where the fun begins! First, you will have to choose the dataset you want to work with. Once you save it, you will be able to choose different steps to modify and transform your data as you wish.

As an example we chose the following dataset: Inflation - Argentina - INDEC - Consumer Price Index - Groups - Monthly and we applied the following steps:

  • Rename columns: to change the name of one of the variables
  • Change Frequency: to rescale the frequency from monthly to quarterly
  • Select columns: to leave only the variable we were interested in and leave behind the other ones.

Remember to click the Save button each time you finish working on your step.

Once you finish working on your pipeline, you will need to click the default step called Publish to dataset to assign a name and repository to your new dataset. It will be automatically updated every time the original dataset is updated either by Alphacast or by yourself or when the pipeline is run. After that, you can save it and preview it or you can just go to the new dataset to start charting!


Creating your first chart

Now let's create your first chart. There are two ways to create a chart:

  • From scratch: click Create new on the upper right corner and then Chart. You will be redirected to the chart editor

  • From any dataset: you can create a chart from any dataset. If you are still on the dataset Inflation - Argentina - INDEC - Consumer Price Index - Groups - Monthly filter again the variable "Nivel General" and its transformation "Year over Year". When doing so, in the upper right you will see the Chart Preview. Then click on Create chart. It will redirect you to the chart editor, follow the next steps to finish your chart.

chart 1.png


Clicking on Add variables will display a list with the repositories that you own, the ones that you are part of and those you follow. If you select one of these, it will lead you to a list of variables grouped by datasets. Following our example, choose some variables corresponding to the inflation dataset and once selected click "set variables".


Once the graph is finished, you can choose the repository to publish it in Select repository for chart. Finally click on Publish. That's it! You have just created your first chart. You can access it with its link (click on the title of the chart) Step 2.6.gif

Writing your first insight

Let's use your recently created chart to write your first insight!

  • If you are still seeing your chart copy the full "URL" at the top of your browser or you can click on Charts in the list on the left. We will use that to embed your chart on the insights.
  • Go back to your repo in Alphacast home and click again on "My Public Repo"
  • Click "New Insight" on the top right of the screen. The insights editor will show up with a basic template. Delete everything for a fresh start.
  • Start writing. Use # for headers. Write "# This is my first insight"
  • To embed your chart you have to use the @ command "chart" followed by the URL of your chart. Write the following command without space between @ and chart


VOILA! Your chart is now embedded. To publish your insights click Publish on the top right, pick "My Public Repo" and publish again. That's it!

Luciano Cohan

Written by

Luciano Cohan

Co-Fundador de Alphacast. Ex Subsecretario de Programación Macroeconómica. Data Science. Creando una plataforma para el trabajo colaborativo en economías

Related insights

  •

    Creating tables with Pipelines

    Our Pipelines feature is a powerful tool which allows report automatization. Let's say, for example, that you want to create an insight which shows dynamics of Argentina FX rates and a table with latest data, including percent changes. Wait! Did you just say "a table"!?

    **With Pipelines you can transform datasets in multiple ways (for

  •

    How can I create a Portfolio Tear-Sheet?

    Alphacast pipelines can be used to design and test portfolio and trading strategies. With the "Porfolio Analysis" Step on the pipeline editor you can create tear-sheets from daily returns and also dynamic rolling stats for different timeframes.


    Step 1. Load the data and calculate a daily return variable.

    You can