Life's a garden. Dig it.
You're developing the comment system for a social platform for AFOLs (Adult Fans Of Legos). The comment data looks like this.
import numpy as np
import pandas as pd
comments = pd.DataFrame([
[32, pd.NA, 'Legos are awesome'],
[12, pd.NA, 'Legos are okay..'],
[11, 12, 'Just okay??'],
[4, 12, 'Okay, troll..'],
[31, 4, "I'm serious"],
[75, 12, 'yeah, nah'],
[41, 75, 'u from down undah?'],
[5, 41, 'nah, yeah'],
[82, pd.NA, 'I love legos'],
[81, 82, 'U 4 rl?'],
[71, 81, 'no'],
[95, 82, 'Me too!'],
[96, 82, 'same']
], columns=['id', 'parent_id', 'comment'])
# Make id the index
comments.set_index('id', inplace=True)
print(comments)
# parent_id comment
# id
# 32 <NA> Legos are awesome
# 12 <NA> Legos are okay..
# 11 12 Just okay??
# 4 12 Okay, troll..
# 31 4 I'm serious
# 75 12 yeah, nah
# 41 75 u from down undah?
# 5 41 nah, yeah
# 82 <NA> I love legos
# 81 82 U 4 rl?
# 71 81 no
# 95 82 Me too!
# 96 82 sameEach comment can have one or none parent_id that identifies its parent comment.
Insert a column called n_descendants in comments that displays how many total comments are nested below each comment. For example, comment 12 has six descendants.
Solution¶
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