https://github.com/simatwa/movies-dataset
A collection of movies dataset for your ML project or any other task.
https://github.com/simatwa/movies-dataset
data-science database dataset-generation datasets movie-data-analysis movie-dataset
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A collection of movies dataset for your ML project or any other task.
- Host: GitHub
- URL: https://github.com/simatwa/movies-dataset
- Owner: Simatwa
- License: mit
- Created: 2024-11-01T09:56:09.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-20T22:01:00.000Z (over 1 year ago)
- Last Synced: 2025-03-04T20:44:10.734Z (over 1 year ago)
- Topics: data-science, database, dataset-generation, datasets, movie-data-analysis, movie-dataset
- Language: Python
- Homepage:
- Size: 31.4 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
Movies-Dataset
A collection of movies dataset for your ML project or any other task.
You can access the datasets from [/data](/data) in csv format.
Alternatively you can generate your own using the procedures given below.
# Installation
- Ensure you have [Python3.10+](https://python.org) installed.
1. Clone
```sh
git clone https://github.com/Simatwa/movies-dataset.git
cd movies-dataset
```
2. Install requirements
```sh
pip install -r requirements.txt
```
# Usage
Running `python -m data_hunter` will retrieve data from the two categories available *(Hollywood, Bollywood)* across all genres available i.e *(Action, Adventure, Animation, Biography, Comedy, Crime, Documentary, Drama, Family, Fantasy, Film-Noir, History, Horror, Music, Musical, Mystery, Romance, Sci-Fi, Sport, Thriller, War, Western)*
You can pass other options such as `limit`, `dir` etc so as to meet your specific needs.
For more usage info you can run $ python -m data_hunter --help
```
usage: data-hunter [-h]
[-g [[Action|Adventure|Animation|Biography|Comedy|Crime|Documentary|Drama|Family|Fantasy|Film-Noir|History|Horror|Music|Musical|Mystery|Romance|Sci-Fi|Sport|Thriller|War|Western] ...]]
[-c [[Bollywood|Bollywood|_] ...]] [-l LIMIT]
[-d DIR] [-p PREFIX] [-q] [-w] [-t] [-v]
A collection of movies dataset for your ML project or any other
task.
options:
-h, --help show this help message and exit
-g, --genres [[Action|Adventure|Animation|Biography|Comedy|Crime|Documentary|Drama|Family|Fantasy|Film-Noir|History|Horror|Music|Musical|Mystery|Romance|Sci-Fi|Sport|Thriller|War|Western] ...]
Movie genres - ['_']
-c, --categories [[Bollywood|Bollywood|_] ...]
Movie category - ['_']
-l, --limit LIMIT Total movies per genre(multiple of 20) -
1000000
-d, --dir DIR Parent directory to save the datasets to -
/home/smartwa/git/smartwa/movies-dataset
-p, --prefix PREFIX Datasets filename prefix -
-q, --quiet Do not stdout any informative texts - False
-w, --overwrite Clear all $prefix*.csv file in the $dir -
False
-t, --trace Maintain trace of the hunting progress -
False
-v, --version show program's version number and exit
There's no gurantee that the data generated are correct.
```
# Direct Links
| No. | Genre | Link |
|-----|-------|------|
| 1 | Action | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/action.csv``` |
| 2 | Adventure | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/adventure.csv``` |
| 3 | Animation | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/animation.csv``` |
| 4 | Biography | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/biography.csv``` |
| 5 | Comedy | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/comedy.csv``` |
| 6 | Crime | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/crime.csv``` |
| 7 | Documentary | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/documentary.csv``` |
| 8 | Drama | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/drama.csv``` |
| 9 | Family | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/family.csv``` |
| 10 | Fantasy | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/fantasy.csv``` |
| 11 | Film-Noir | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/film-noir.csv``` |
| 12 | History | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/history.csv``` |
| 13 | Horror | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/horror.csv``` |
| 14 | Music | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/music.csv``` |
| 15 | Musical | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/musical.csv``` |
| 16 | Mystery | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/mystery.csv``` |
| 17 | Romance | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/romance.csv``` |
| 18 | Sci-Fi | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/sci-fi.csv``` |
| 19 | Sport | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/sport.csv``` |
| 20 | Thriller | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/thriller.csv``` |
| 21 | War | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/war.csv``` |
| 22 | Western | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/western.csv``` |
# Combined Datasets Link
| No. | Identity | Link |
|-----|-------|------|
| 1 | Combined `csv` | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/combined.csv``` |
| 2 | Sqlite3 Database | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/combined.db``` |
| 2 | Sqlite3 Database (Relational) | ```https://raw.githubusercontent.com/Simatwa/movies-dataset/main/data/combined-relational.db``` |
# Further details
In order to make work easier, there's [cli](cli.py) that comes handy in manipulating the data. This is just but not limited to converting them to various formats and even piling them into one sqlite3 database.