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"I wish there was a movie program that could do ...."

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Bauhaus
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"I wish there was a movie program that could do ...."

#1

Post by Bauhaus » September 13th, 2019, 5:45 pm

So I'm learning c# and thought of making a movie database.
Unfortunately there's already many movie catalogue software around so I need ideas....
Doesn't have to be about a database, could be something different, as long as it involves movies.
Could be a desktop application or web site.
So what would you like to see in a movie program ?

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maxwelldeux
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#2

Post by maxwelldeux » September 13th, 2019, 6:05 pm

A good question, but one I need to think on for a bit.

For others, what are some of the annoying things we do around here that could be solved by automation?

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blueboybob
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#3

Post by blueboybob » September 13th, 2019, 11:53 pm

I wish there was a program, that given my seen export.csv from imdb, gave me all kinds of charts/tables

imagine you upload your csv and it just gave break downs of when watched, year of movie, genra, director, etc.

like tableu but premade, just supply your csv

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maxwelldeux
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#4

Post by maxwelldeux » September 14th, 2019, 5:32 am

blueboybob wrote:
September 13th, 2019, 11:53 pm
I wish there was a program, that given my seen export.csv from imdb, gave me all kinds of charts/tables

imagine you upload your csv and it just gave break downs of when watched, year of movie, genra, director, etc.

like tableu but premade, just supply your csv
Shit, yo. That's in my wheelhouse. Let me noodle that.

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Ivan0716
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#5

Post by Ivan0716 » 54 minutes ago

blueboybob wrote:
September 13th, 2019, 11:53 pm
I wish there was a program, that given my seen export.csv from imdb, gave me all kinds of charts/tables

imagine you upload your csv and it just gave break downs of when watched, year of movie, genra, director, etc.

like tableu but premade, just supply your csv
I did something like that when I was learning python a while back, it reads the icm+imdb csv files, applies filters (ratings/checks/years etc.), and returns a list of films and a bunch of dataframes like these (the formatting gets fucked when I copy and paste it onto here but you get the idea):
SpoilerShow
Seen: 4402
Favourited: 323 (7.34%)
Disliked: 2 (0.05%)
Number of Unique Directors: 2056
Total Watch Time: 442389 minutes / 7373 hours 9 minutes
Longest Runtime: Berlin Alexanderplatz (931 mins)

Ratings
10: 80 (1.82%)
9: 241 (5.47%)
8: 540 (12.27%)
7: 1003 (22.79%)
6: 1118 (25.40%)
5: 716 (16.27%)
4: 424 (9.63%)
3: 196 (4.45%)
2: 70 (1.59%)
1: 14 (0.32%)
Average Rating: 6.14175

# of Films (%) Average Rating
Decade
1880s 2 (0.05%) 5.000
1890s 45 (1.02%) 4.511
1900s 55 (1.25%) 4.455
1910s 24 (0.55%) 5.167
1920s 85 (1.93%) 7.012
1930s 150 (3.41%) 6.867
1940s 238 (5.41%) 6.752
1950s 300 (6.82%) 6.900
1960s 561 (12.74%) 6.690
1970s 582 (13.22%) 6.036
1980s 394 (8.95%) 6.330
1990s 409 (9.29%) 6.213
2000s 754 (17.13%) 5.408
2010s 803 (18.24%) 5.943


# of Films (%) Average Rating
IMDb Rating Range
8+ 581 (13.2%) 7.620
7.5-7.9 1021 (23.19%) 7.019
7.0-7.4 1133 (25.74%) 6.379
6.5-6.9 738 (16.77%) 5.618
6.0-6.4 444 (10.09%) 4.876
5.5-5.9 239 (5.43%) 4.238
5.0-5.4 140 (3.18%) 3.771
1.0-4.9 104 (2.36%) 3.375
Average IMDb Rating: 7.05889

# of Films (%) Average Rating
Runtime Range (mins)
181+ 58 (1.32%) 7.862
151-180 131 (2.98%) 7.092
121-150 648 (14.72%) 6.639
106-120 868 (19.72%) 6.267
91-105 1478 (33.58%) 5.963
76-90 775 (17.61%) 5.952
41-75 153 (3.48%) 6.333
<=40 291 (6.61%) 5.199
Average Length: 100

# of Films (%) Average Rating
iCM Checks Range
10000+ 778 (17.67%) 6.150
5000-9999 379 (8.61%) 6.314
1000-4999 1031 (23.42%) 6.483
400-999 584 (13.27%) 6.154
<400 1630 (37.03%) 5.877
Average # of Check: 7919

# of Films (%) Average Rating
officialtoplistcount
42 2 (0.05%) 8.000
40 1 (0.02%) 7.000
38 1 (0.02%) 10.000
37 2 (0.05%) 8.000
36 4 (0.09%) 8.000
35 2 (0.05%) 8.500
34 1 (0.02%) 8.000
33 7 (0.16%) 7.571
32 9 (0.2%) 9.000
31 5 (0.11%) 7.600
30 3 (0.07%) 7.667
29 5 (0.11%) 8.800
28 10 (0.23%) 8.700
27 11 (0.25%) 7.636
26 10 (0.23%) 7.300
25 14 (0.32%) 7.786
24 19 (0.43%) 7.737
23 20 (0.45%) 7.900
22 18 (0.41%) 7.611
21 23 (0.52%) 7.652
20 25 (0.57%) 7.760
19 29 (0.66%) 7.828
18 32 (0.73%) 7.219
17 28 (0.64%) 7.821
16 35 (0.8%) 7.829
15 41 (0.93%) 7.488
14 42 (0.95%) 7.524
13 57 (1.29%) 7.228
12 58 (1.32%) 7.483
11 57 (1.29%) 6.930
10 76 (1.73%) 7.237
9 80 (1.82%) 7.062
8 98 (2.23%) 7.112
7 105 (2.39%) 7.076
6 132 (3.0%) 6.864
5 156 (3.54%) 6.776
4 246 (5.59%) 6.642
3 278 (6.32%) 6.590
2 465 (10.56%) 6.191
1 848 (19.26%) 5.636
0 1347 (30.6%) 5.248

Genres
# of Films (%) Average Rating
Action 682 (15.49%) 5.440
Adult 3 (0.07%) 3.667
Adventure 421 (9.56%) 5.526
Animation 184 (4.18%) 6.014
Biography 128 (2.91%) 6.523
Comedy 1000 (22.72%) 5.823
Crime 945 (21.47%) 6.277
Documentary 127 (2.89%) 5.005
Drama 2713 (61.63%) 6.632
Family 192 (4.36%) 5.674
Fantasy 385 (8.75%) 5.920
Film-Noir 180 (4.09%) 6.571
History 158 (3.59%) 6.698
Horror 590 (13.4%) 5.369
Music 102 (2.32%) 6.354
Musical 80 (1.82%) 6.349
Mystery 623 (14.15%) 6.115
News 3 (0.07%) 3.667
Romance 731 (16.61%) 6.452
Sci-Fi 321 (7.29%) 5.572
Short 279 (6.34%) 5.253
Sport 48 (1.09%) 5.563
Thriller 1190 (27.03%) 5.887
War 204 (4.63%) 6.717
Western 159 (3.61%) 6.018

Top 10 most seen directors:
# of Films
Milton Manaki 42
Janaki Manaki 42
Alfred Hitchcock 26
Johnnie To 25
Fritz Lang 23
Lucio Fulci 21
Luis Buñuel 20
Jesús Franco 19
Stan Brakhage 19
Akira Kurosawa 18

Top 10 directors by average rating (min 3 films):
Average Rating
Andrei Tarkovsky 9.286
Sergio Leone 8.833
Jean-Pierre Melville 8.750
Ingmar Bergman 8.706
Kar-Wai Wong 8.700
Ágnes Hranitzky 8.667
Edward Yang 8.429
Marcel Carné 8.375
Krzysztof Kieslowski 8.300
Hsiao-Hsien Hou 8.299
I've been using it quite a lot to help me make lists (I can't imagine managing my <400 list without it now).

Technical it can give me a bunch of graphs as well, but I didn't care enough to mess around with matplotlib for long enough to actually make them readable. :ermm:
SpoilerShow
Image

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