How To Rank Rows By Id In Pandas Python
I have a Dataframe like this: id points1 points2 1 44 53 1 76 34 1 63 66 2 23 34 2 44 56 I
Solution 1:
You need to use ascending=False inside rank
df.join(df.groupby('id')['points1', 'points2'].rank(ascending=False).astype(int).add_suffix('_rank'))
+---+----+---------+---------+--------------+--------------+
| | id | points1 | points2 | points1_rank | points2_rank |
+---+----+---------+---------+--------------+--------------+
| 0 | 1 | 44 | 53 | 3 | 2 |
| 1 | 1 | 76 | 34 | 1 | 3 |
| 2 | 1 | 63 | 66 | 2 | 1 |
| 3 | 2 | 23 | 34 | 2 | 2 |
| 4 | 2 | 44 | 56 | 1 | 1 |
+---+----+---------+---------+--------------+--------------+
Solution 2:
Use join with remove reset_index and for change columns names add add_suffix:
features = ["points1","points2"]
df = df.join(df.groupby('id')[features].rank(ascending=False).add_suffix('_rank').astype(int))
print (df)
id points1 points2 points1_rank points2_rank
0 1 44 53 3 2
1 1 76 34 1 3
2 1 63 66 2 1
3 2 23 34 2 2
4 2 44 56 1 1
Post a Comment for "How To Rank Rows By Id In Pandas Python"