如何在 Pandas 中使用 nunique() 計算組內的唯一值？
- Susan Sarandon原創
- 2024-10-18 15:44:03535瀏覽
Counting Unique Values per Group in Pandas with nunique
In pandas, counting unique values in a group is possible using the nunique() method. This is particularly useful when working with data where you need to determine the number of distinct values within specific categories or groups.
Problem:
Consider a DataFrame with the following data:
| ID | domain |
|---|---|
| 123 | vk.com |
| 123 | vk.com |
| 123 | twitter.com |
| 456 | vk.com |
| 456 | facebook.com |
| 456 | vk.com |
| 456 | google.com |
| 789 | twitter.com |
| 789 | vk.com |
The task is to count the unique IDs for each domain in this DataFrame.
Solution:
To count unique values per group, use the nunique() method with the desired grouping columns. In this case, the domain column represents the groups:
<code class="python">df = df.groupby('domain')['ID'].nunique()
print(df)</code>
Output:
| domain | count |
|---|---|
| facebook.com | 1 |
| google.com | 1 |
| twitter.com | 2 |
| vk.com | 3 |
Additional Considerations:
- To remove any single quotes (') from the domain values, use the str.strip("'") method before grouping.
- To preserve the column name, use the as_index=False argument in groupby() and pass the nunique() method to the agg() function.
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