**Grouping** is often used to get a result similar to *pivot tables* in Excel. Suppose that we want to compute mean value of column `A` for each given number of `LenB`. Then we can group our DataFrame by `LenB`, and call `mean`:
**Grouping** is often used to get a result similar to *pivot tables* in Excel. Suppose that we want to compute mean value of column `A` for each given number of `LenB`. Then we can group our DataFrame by `LenB`, and call `mean`:
```python
```python
df.groupby(by='LenB').mean()
df.groupby(by='LenB')[['A','DivA']].mean()
```
```
If we need to compute mean and the number of elements in the group, then we can use more complex `aggregate` function:
If we need to compute mean and the number of elements in the group, then we can use more complex `aggregate` function:
Lee Stott
2 weeks ago
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