Q17:
Create a function called sets_from_minifig that takes as input a minifig number (as a string) and returns a list of sets a minifig has appeared in.
Return a DataFrame (sorted by set_num and then by version) with the following columns: set_num, version,name_sets, fig_num, fig_name.
The index should go from 0 to n-1.
Here is a possible implementation for the `sets_from_minifig` function:
```python
import pandas as pd
def sets_from_minifig(minifig_num):
# Assuming we have a dataframe called 'minifigs' with columns ['set_num', 'version', 'fig_num', 'fig_name']
# and another dataframe called 'sets' with columns ['set_num', 'version', 'name_sets']
# Filter the minifigs dataframe to get the rows where fig_num matches the input minifig_num
filtered_minifigs = minifigs[minifigs['fig_num'] == minifig_num]
# Join the filtered_minifigs dataframe with the sets dataframe based on set_num and version columns
result = pd.merge(filtered_minifigs, sets, on=['set_num', 'version'])
# Sort the result dataframe by set_num and then by version
result = result.sort_values(by=['set_num', 'version'])
# Reindex the dataframe so the index goes from 0 to n-1
result = result.reset_index(drop=True)
return result
```
Note that this implementation assumes you have two dataframes: `minifigs` and `sets`. `minifigs` should have columns `['set_num', 'version', 'fig_num', 'fig_name']`, while `sets` should have columns `['set_num', 'version', 'name_sets']`. You may need to adjust the code and replace these dataframe names with your actual dataframe names.
To create the function `sets_from_minifig`, you will need to follow these steps:
Step 1: Import the required libraries
First, import the required libraries, `pandas` and `requests`, using the following code:
```python
import pandas as pd
import requests
```
Step 2: Define the function `sets_from_minifig`
Define the function `sets_from_minifig` that takes the `minifig_number` as input and returns a DataFrame of sets the minifig has appeared in, sorted by `set_num` and then by `version`. Here's the code for the function:
```python
def sets_from_minifig(minifig_number):
# Set the base URL for the API request
base_url = 'https://rebrickable.com/api/v3/lego/minifigs/'
# Send an API request to get the minifig data
response = requests.get(base_url + minifig_number)
# Check if the request was successful
if response.status_code == 200:
minifig_data = response.json()
# Create an empty list to store the sets
sets = []
# Loop through each set the minifig has appeared in
for appearance in minifig_data['sets']:
# Get the set details
set_num = appearance['set_num']
version = appearance['version']
set_name = appearance['set_name']
# Get the minifig details
fig_num = appearance['fig_num']
fig_name = appearance['fig_name']
# Append the set details to the list
sets.append({
'set_num': set_num,
'version': version,
'name_sets': set_name,
'fig_num': fig_num,
'fig_name': fig_name
})
# Create a DataFrame from the list of sets
sets_df = pd.DataFrame(sets)
# Sort the DataFrame by set_num and then by version
sets_df = sets_df.sort_values(['set_num', 'version'])
# Set the index of the DataFrame
sets_df = sets_df.reset_index(drop=True)
return sets_df
else:
print('Error:', response.status_code)
return None
```
Step 3: Call the function with a minifig number
To use the `sets_from_minifig` function, you can call it with the desired minifig number as a string. For example:
```python
minifig_number = '1234'
sets_df = sets_from_minifig(minifig_number)
print(sets_df)
```
Make sure to replace `'1234'` with your desired minifig number.
This code will send an API request to retrieve the minifig data, parse it, and return a DataFrame with the desired columns (`set_num`, `version`, `name_sets`, `fig_num`, and `fig_name`) sorted as requested.
Note: In order for this code to work, you will need to have an API key from Rebrickable and replace it in the `requests.get()` function call in the `sets_from_minifig` function. Additionally, ensure that the API request and response handling is done correctly based on the specific API documentation.