Milking a prices monitor to report on Argentina’s inflation

Category: Best data-driven reporting (small and large newsrooms)

Country/area: Argentina

Organisation: LA NACION

Organisation size: Big

Publication date: 14/03/2019

Credit: Pablo Fernández Blanco, Sofía Terrile, Gabriela Bouret, Cristian Bertelegni, Nicolás Bases, Gastón de la LLana, Giselle Ferro, Pablo Loscri, Luciana Coraggio, Bianca Pallaro, Florencia Fernández Blanco, Aldana López, Delfina Bertolotti

Project description:

If we had to pick a word that identifies Argentinians, it wouldn’t be tango. It would be inflation.

Argentina is one of the five countries with the highest inflation (IMF). Supermarket prices rise week after week.

We created  a price monitor that allows a weekly and monthly monitoring of goods. It presents a group of 365 from leading brands that are marketed nationally in 2,561 places and are representative of household consumption in Argentina.  At this point,  we have 54 million prices registered and it’s a great tool for data driven reporting, built in house from scratch.

Impact reached:

“Shopping Cart LA NACION” is used primarily by our newsroom to monitor and report on inflation.

We published a mix of content throughout 2019 using the database. Reporting varied in focus and type of data visualization.

Sometimes the story involves using the database and sometimes in combination with others.

Data was part of a substantial piece of reporting and stands on a foundation of data acquisition and analysis to tell the following stories.

“The Christmas products basket is 64% more expensive than last year” (Interactive Datavis and reporting on a selected special combination of products)  – Dic 2019)

“From 1999 to today: What can be done with a $ 100 bill?” Interactive Infography (December 2019)

“The Price Basket of LA NACION had an increase of 1,87% in the last four weeks” (Automated content with dedicated weekly evolution graph and designed ranking of 43 products – March 2019)

“Juice, yerba mate and milk, the products that increased the most in the last six months” (Open Data Table) 

 “In April, a family needed $ 29,494 to avoid falling into poverty” (Tableau Public interactive graph)

“The 10 products that rose the most in the last four weeks” (Automated content for top 10 products with dedicated interactive charts and graphs – March 2019)

Techniques/technologies used:

We decided to scrape the products ourselves from the official Precios Claros website. To do so, we activated a software that runs twice a week and records the information it collects in a database.

The updating process is fully automatic, since data is automatically collected twice a week, saved in a database, and then the front end updates, and the user may thus obtain the price variation of each product.

On the other hand, if it is necessary to add or remove products for users to see, we have an admin and back-end where the same journalists may modify the arrangement of a basket or create new ones to follow some other project, such as a school basket when school time begins, a Christmas basket or a set of products related to holidays.

First we developed one for the “LN Canasta” in SQL so we could prove the concept, then for “LN Changuito” we needed to automate it and connect it with both outputs, so we developed another version with Python and hosted in a Lambda with CloudWatch and PostgreSql, using in RDS for the database.

An ADMIN developed with Django/Python is used as a back-end to be able to make  sure that all processes work correctly. 

From the back-end, after updating the data weekly, a json file is created and hosted in S3 with the prices of the last four weeks for each product in each city. 

For the front-end an application developed with VUE.js, D3.js, CSS3 HTML5 was programmed. This one uses the json files published by the back-end in S3. Each user can choose different options to find out the price variation of the products he/she consumes through sets of goods that we call baskets

What was the hardest part of this project?

The hardest part of the project was getting the data. After three unsuccessful FOIA requests we decided to scrape the information we needed. For this, we had to define an initial list requested by the editor and then automate the process and make a flexible admin interface.

From the moment we began to save the data in the database, we checked the official website to verify and control the information. As we found inconsistencies in the prices published on the site, we decided to discard the outliers.

Jury must understand that reporting on inflation is not journalism as usual. Very few countries in the world have this macro ongoing economy struggle.

This project was an effort to counteract the government’s possible denial of the real inflation index and a way to help the newsroom and our audience to get stories that are meaningful depending on the time of the year (school classes, Christmas, etc) helping to bring down an abstract concept as inflation.

As a major national news outlet there is an editorial responsibility on how to report on this to avoid a spiral of escalation to hiperinflation. A delicate balance.

What can others learn from this project?

First of all they can visualize a problem that happens in very few economies of the world and get an idea on how to report on this kind of specific beat.

Journalists used to visit supemarkets every day with a notebook and pen to report on this issue, reporting on different neighbourhoods.

Sometimes we create tools or interactives that we consider useful but then they fail to engage newsroom or audience.

In this case we built a tool that is actually critically NEEDED by the newsroom and so it’s being used and loved to find news stories with different angles.

In this project we tackled a national, vital and ongoing beat while solving our journalists processes, builiding a database from scratch, updating it 2 a week and producing orginal reporting.


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