Using a variety of data manipulation techniques to explore different aspects of Lego's history.
The Rebrickable database includes data on every LEGO set that has ever been sold; the names of the sets, what bricks they contain, what color the bricks are, etc.
Source : Rebrickable
The Lego Database Schema
| Dataset | Description | Columns |
|---|---|---|
colors.csv |
This file contains information on LEGO colors, including a unique ID for each color, its name, and approximate RGB value, and whether it's transparent | id Unique ID for this color. name The human-readable name of the color. rgb The approximate RGB color. is_trans Whether or not the given color is transparent/translucent. |
inventories.csv |
This table contains information on inventories, including a unique ID, it's version and the set number. | id Unique ID for this inventory entry. version Version number. set_num Set number (form sets.csv). |
inventory_parts.csv |
This table contains information part inventories, including a unique ID number, the part number, the color of the part, how many are included and whether it's a spare. | inventory_id Unique ID for the inventory this part is appearing in. This is the same as the id value in inventories.csv. part_num Unique ID for the part. color_id Unique ID for the color, as per colors.csv. quantity The number of copies of this part included in the set! is_spare Whether or not this is a spare part. Spare parts are additional parts not needed to finish the set. |
inventory_sets.csv |
This file contains information on what inventory is included in which sets, including the inventory ID, the set number and the quantity of that inventory that are included. | inventory_id Unique inventory ID from inventories.csv. set_num Unique set ID from sets.csv. quantity The quantity of the inventory included. |
part_categories.csv |
This dataset includes information on the part category (what type of part it is) and a unique ID for that part category. | id Unique ID for the part category. name The category of stuff the part is in. |
part_relationships.csv |
This dataset includes information on the different relationships of parts. | rel_type Relationship type of the part. child_part_num Child part category ID. parent_part_num Parent category unique ID |
parts.csv |
This dataset includes information on lego parts, including a unique ID number, the name of the part, and what part category it's from. | part_num Unique ID for the part. name Name of the part. part_cat_id Part category unique ID (from part_categories.csv). |
sets.csv |
This file contains information on LEGO sets, including a unique ID number, the name of the set, the year it was released, its theme and how many parts it includes. | set_num Unique set ID. name The name of the set. year Year the set was published. theme_id Unique ID for the theme used for the set (from themes.csv). num_parts The number of parts included in the set. |
themes.csv |
This file includes information on lego themes. Each theme is given a unique ID number, a name, and (if it's part of a bigger theme) which theme it's part of. | id Theme unique ID. name Name of the theme. parent_id Unique ID for the larger theme, if there is one. |
#### Colors dataset ```python colors = pd.read_csv('datasets/colors.csv') display(colors.head()) ```
| id | name | rgb | is_trans | |
|---|---|---|---|---|
| 0 | -1 | Unknown | 0033B2 | f |
| 1 | 0 | Black | 05131D | f |
| 2 | 1 | Blue | 0055BF | f |
| 3 | 2 | Green | 237841 | f |
| 4 | 3 | Dark Turquoise | 008F9B | f |
It would be interesting to explore the distribution of transparent vs. non-transparent colors.
### Sets dataset
sets = pd.read_csv('datasets/sets.csv')
display(sets.head())| set_num | name | year | theme_id | num_parts | |
|---|---|---|---|---|---|
| 0 | 00-1 | Weetabix Castle | 1970 | 414 | 471 |
| 1 | 0011-2 | Town Mini-Figures | 1978 | 84 | 12 |
| 2 | 0011-3 | Castle 2 for 1 Bonus Offer | 1987 | 199 | 2 |
| 3 | 0012-1 | Space Mini-Figures | 1979 | 143 | 12 |
| 4 | 0013-1 | Space Mini-Figures | 1979 | 143 | 12 |
Let's see how the number of sets changed over the years
Let's also observe the change in themes over the years
