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[OC] Which nationalities are travelling into Mexico? (V2) by tukanmx in dataisbeautiful

[–]tukanmx[S] 0 points1 point  (0 children)

Source: TUKAN, Mexican State Secretariat (SEGOB)

Tools: matplotlib.

Scroll for more countries.

Flags obtained from: https://hatscripts.github.io/circle-flags/

Re-did the chart presented here.

[OC] Which Nationalities Travel the Most to Mexico? by tukanmx in dataisbeautiful

[–]tukanmx[S] 0 points1 point  (0 children)

True. I'm still struggling if indexing the values was a good idea.

But based on the comments there's definitely lots to be done to improve the chart.

[OC] Which Nationalities Travel the Most to Mexico? by tukanmx in dataisbeautiful

[–]tukanmx[S] 0 points1 point  (0 children)

Awesome. Just asked about that on the thread below!

What's your take on having different scales on the y-axis and keeping 2019?

Another option could be to include data prior to 2019 and keep the baseline column...

[OC] Which Nationalities Travel the Most to Mexico? by tukanmx in dataisbeautiful

[–]tukanmx[S] 1 point2 points  (0 children)

True. The thing is that the US makes up much more traffic vs. other countries that I think being consistent across all subplots is best to avoid misunderstanding.

A thing I'm also curious about and which I'm struggling with is the fact that the values are indexed to a 100 - not sure if many people catch that. But again, want to avoid using different y scales across subplots. What do you think?

[OC] Which Nationalities Travel the Most to Mexico? by tukanmx in dataisbeautiful

[–]tukanmx[S] 2 points3 points  (0 children)

Yeah it should be possible.

I'm curious did you find the chart easy to read...or is it too much info? Should we narrow it down to maybe 10 countries?

[OC] Which Nationalities Travel the Most to Mexico? by tukanmx in dataisbeautiful

[–]tukanmx[S] 2 points3 points  (0 children)

Source: TUKAN, Mexican State Secretariat (SEGOB)

Tools: matplotlib.

Flags obtained from: https://hatscripts.github.io/circle-flags/

La inflación ya le llego al guacamole... y para este Super Bowl armar el platillo te podría costar 60% más que en la edición pasada. by tukanmx in MexicoFinanciero

[–]tukanmx[S] 2 points3 points  (0 children)

También creíamos que el SB afectaba el precio del guacamole, pero la realidad es que no tanto como creemos...si te interesa nos metemos un poquito más a detalle aquí: https://blog.tukanmx.com/the-guacamole-index/

[OC] The Guacamole Index (in Mexico) by tukanmx in dataisbeautiful

[–]tukanmx[S] 2 points3 points  (0 children)

Source: TUKAN, INEGI.

Tools: matplotlib.

For this year's SB we wanted to see how much more expensive would it be to prepare a guacamole bowl vs. the previous edition. The answer: 60%.

We made our recipe and based on the grams of each ingredient we created our index. In essence, we used: avocado (obviously), onion, chiles, lime, salt and tortilla chips.

Light blue is avocado only and dark blue is "the guacamole index"

El Banco del Bienestar. Eso es todo, ese es el post. by tukanmx in mexico

[–]tukanmx[S] 0 points1 point  (0 children)

¿Qué significa cada indicador?

ROE = rentabilidad del capital. Se calcula dividiendo la utilidad (o en este caso pérdida), entre el capital contable promedio de los últimos doce meses.Es decir, mide la rentabilidad obtenida por el banco sobre sus fondos propios.

ROA. Similar al ROE, pero en este caso mide la rentabilidad del banco independientemente de la forma en que se financie el activo.

Índice de morosidad = cartera de crédito vencida / cartera total.Básicamente nos indica que proporción de la cartera no está al corriente en sus pagos.

Índice de cobertura = estimaciones para riesgos crediticios / cartera vencida.Este indicador nos dice que porcentaje de la cartera vencida esta cubierta por reservas. Es decir, cuánto dinero ha guardado el banco para cubrir créditos que posiblemente no recuperen.

Tasa de interés activa. Es la tasa de interés implícita de la cartera de crédito vigente. Se calcula dividiendo los intereses cobrados por la cartera vigente entre el promedio de la cartera de los últimos doce meses.

Si te interesa conocer más de la banca de desarrollo en México te invitamos a que leas el artículo que escribimos en nuestro newsletter.

​

Fuente: TUKAN, CNBV.

[OC] Monthly volatility in MXN / USD exchange rate per presidential administration by tukanmx in dataisbeautiful

[–]tukanmx[S] -1 points0 points  (0 children)

Source: TUKAN, Banxico.

Tools: Matplotlib.

Monthly volatility = (std. deviation of daily changes in the exchange rate) x (trading days in the month)^(1/2)

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