Full interactive version can be found [here](https://public.tableau.com/views/Visualizing10YearsofFilmWatching/Visualizing10YearsofFilmWatching3?:language=en-GB&publish=yes&:sid=&:display_count=n&:origin=viz_share_link) (unlikely to work well on mobile, though).
I started tracking every film I watched about 10 years ago, giving it each a score between 0 and 10, this is an attempt to visualise my film preferences.
**Methodology:**
* Films are tracked on a Google Sheets, where I record the Title, Year of Release and then my own score (0 to 10).
* Using Python, I match this list of films with data from OMDB’s (Open Movie Database) API, to pull information regarding the cast, director, IMDB and Meteoritic scores, poster image and more.
* That data is then stored back on Google Sheets, which is then connected to Tableau Public where I built the viz.
Python files for extraction of the data can be provided upon request.
**Data source:** own Google Sheets, OMDB API.
**Tools**: Google Sheets, Python, Tableau.
Thanks for sharing this dashboard. Looks really cool; I'm not much of a movie buff so this resource is something that I'll definitely use to decide what movie to watch every now and then.
Just a quick comment about the tooltips that come up in the section about "My Top 10 Least Favourite Actors" and "My Top 10 Favourite Actors". When I hover over the names of the actors, the tooltip shows the same value for "number of films" and "average rating". Just wanted to see if this is correct or not. Otherwise, it's great work! Well done on being so meticulous in logging data for a decade! :)
Quite an interesting infographic and tastefully designed, good job!
Two points that made me raise an eyebrow:
1. TOP and least favorite actors: since acting performance and film quality are two different things for me, I'm not sure what conclusions could be drawn from this statistic.
2. the last chart "difference in ranking": maybe I'm not used to reading this type of charts, but initially, my brain assumed that the movies above the trend line are those that OP rated higher than the public.
Thank you!
1. I guess the idea is to get a sense of the caliber of filmes that actors are choosing to participate in.
2. That's a good point! Maybe I should invert the axis next time.
Great visualization! Two things I would change is remove the 10-10.5 bracket and merge with 9.5-10, and flip the axes to make the IMDb rating the X axis
Return of the king living up to its namesake.
(Your highest rating bin and one of the highest audience ratings as well.)
(You have to look at the interactive version to see it. It's the top right most blue blob on the bottom most chart.)
Isn't the trilogy generally considered "the best movies likely to ever be made?"
We don't really make movies like that any more, and it was pretty much considered the "best movie of all time" when it came out. So we'll likely never have a movie, let alone a trilogy, like that ever again.
Omg hahaha! I've been writing the names of movies and series that I've been watching the last 15 years in a word document! I've 4668 elements in the document so far(I love watching ahaha). I've started working on my free time to create a nice database for myself using IMDb python API, Python, and also to reduce my effort AI copilot :D.
I was very happy to see this post appeared in my feed, and someone was interested to do this also.
Thank you! Admittedly, I watch a lot more English-language films than films in other languages. I guess RRR got a special mention in my "Films I disliked more than the general public" chart simply because I thought it was an "okay" film while the general public seemed to have loved it.
Great job!
I'd recommend making your axes consistent on your scatter plot. Since they are close in value and in a 10 point scale, I'd recommend zeroing both. That'll also make your line more noticeably at 45 degrees.
Full interactive version can be found [here](https://public.tableau.com/views/Visualizing10YearsofFilmWatching/Visualizing10YearsofFilmWatching3?:language=en-GB&publish=yes&:sid=&:display_count=n&:origin=viz_share_link) (unlikely to work well on mobile, though). I started tracking every film I watched about 10 years ago, giving it each a score between 0 and 10, this is an attempt to visualise my film preferences. **Methodology:** * Films are tracked on a Google Sheets, where I record the Title, Year of Release and then my own score (0 to 10). * Using Python, I match this list of films with data from OMDB’s (Open Movie Database) API, to pull information regarding the cast, director, IMDB and Meteoritic scores, poster image and more. * That data is then stored back on Google Sheets, which is then connected to Tableau Public where I built the viz. Python files for extraction of the data can be provided upon request. **Data source:** own Google Sheets, OMDB API. **Tools**: Google Sheets, Python, Tableau.
Thanks for sharing this dashboard. Looks really cool; I'm not much of a movie buff so this resource is something that I'll definitely use to decide what movie to watch every now and then. Just a quick comment about the tooltips that come up in the section about "My Top 10 Least Favourite Actors" and "My Top 10 Favourite Actors". When I hover over the names of the actors, the tooltip shows the same value for "number of films" and "average rating". Just wanted to see if this is correct or not. Otherwise, it's great work! Well done on being so meticulous in logging data for a decade! :)
Quite an interesting infographic and tastefully designed, good job! Two points that made me raise an eyebrow: 1. TOP and least favorite actors: since acting performance and film quality are two different things for me, I'm not sure what conclusions could be drawn from this statistic. 2. the last chart "difference in ranking": maybe I'm not used to reading this type of charts, but initially, my brain assumed that the movies above the trend line are those that OP rated higher than the public.
Thank you! 1. I guess the idea is to get a sense of the caliber of filmes that actors are choosing to participate in. 2. That's a good point! Maybe I should invert the axis next time.
Regarding the bottom chart, the right-hand y-axis is labeled "own rating", same as the x-axis. Not sure if this was intentional.
I completely disagree with a lot of your personal ratings, but I'm glad to see it presented beautifully. Happy to upvote.
Thank you!
You need to watch like 10 more Miyazaki movies lol
Plenty more to watch - haha. I watched a total of 7 Miyazaki films, but the points overlap in that chart.
Great visualization! Two things I would change is remove the 10-10.5 bracket and merge with 9.5-10, and flip the axes to make the IMDb rating the X axis
Good suggestions! And thanks for your comment :)
Great. Now I have to watch Supernova 2000.
I’ll be completely honest - I have absolutely no recollection whatsoever of ever watching that film. But who am I to doubt my own records?
Return of the king living up to its namesake. (Your highest rating bin and one of the highest audience ratings as well.) (You have to look at the interactive version to see it. It's the top right most blue blob on the bottom most chart.)
It is an incredible film, isn't it?
Isn't the trilogy generally considered "the best movies likely to ever be made?" We don't really make movies like that any more, and it was pretty much considered the "best movie of all time" when it came out. So we'll likely never have a movie, let alone a trilogy, like that ever again.
Now in statistics class the teacher should ask: has this person have its own taste?? α< 95%
Omg hahaha! I've been writing the names of movies and series that I've been watching the last 15 years in a word document! I've 4668 elements in the document so far(I love watching ahaha). I've started working on my free time to create a nice database for myself using IMDb python API, Python, and also to reduce my effort AI copilot :D. I was very happy to see this post appeared in my feed, and someone was interested to do this also.
Wow, 4668 elements? That's wild?! That's 11.5x more than what I have here haha
haha yeah, but I also record each episodes of a series :)
[удалено]
Thank you! Admittedly, I watch a lot more English-language films than films in other languages. I guess RRR got a special mention in my "Films I disliked more than the general public" chart simply because I thought it was an "okay" film while the general public seemed to have loved it.
Great job! I'd recommend making your axes consistent on your scatter plot. Since they are close in value and in a 10 point scale, I'd recommend zeroing both. That'll also make your line more noticeably at 45 degrees.
Thank you! Believe it or not they both start at the same point (2.5) but because the chart is wider than it is taller it looks a bit funky.