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# functions
> 
# module pixeltable.functions
General Pixeltable UDFs.
This parent module contains general-purpose UDFs that apply to multiple data types.
## func map()
```python Signature theme={null}
map(
expr: pixeltable.exprs.expr.Expr,
fn: Callable[[pixeltable.exprs.expr.Expr], Any]
) -> pixeltable.exprs.expr.Expr
```
Applies a mapping function to each element of a list.
**Parameters:**
* **`expr`** (`pixeltable.exprs.expr.Expr`): The list expression to map over; must be an expression of type `pxt.Json`.
* **`fn`** (`typing.Callable[[pixeltable.exprs.expr.Expr], typing.Any]`): An operation on Pixeltable expressions that will be applied to each element of the JSON array.
**Examples:**
Given a table `tbl` with a column `data` of type `pxt.Json` containing lists of integers, add a computed column that produces new lists with each integer doubled:
```python theme={null}
tbl.add_computed_column(
doubled=pxt.functions.map(t.data, lambda x: x * 2)
)
```
## uda count()
```python Signatures theme={null}
# Signature 1:
@pxt.uda
count(val: pxt.String | None) -> pxt.Int
# Signature 2:
@pxt.uda
count(val: pxt.Bool | None) -> pxt.Int
# Signature 3:
@pxt.uda
count(val: pxt.Int | None) -> pxt.Int
# Signature 4:
@pxt.uda
count(val: pxt.Float | None) -> pxt.Int
# Signature 5:
@pxt.uda
count(val: pxt.Timestamp | None) -> pxt.Int
# Signature 6:
@pxt.uda
count(val: pxt.Json | None) -> pxt.Int
# Signature 7:
@pxt.uda
count(val: pxt.Array | None) -> pxt.Int
# Signature 8:
@pxt.uda
count(val: pxt.Image | None) -> pxt.Int
# Signature 9:
@pxt.uda
count(val: pxt.Video | None) -> pxt.Int
# Signature 10:
@pxt.uda
count(val: pxt.Audio | None) -> pxt.Int
# Signature 11:
@pxt.uda
count(val: pxt.Document | None) -> pxt.Int
# Signature 12:
@pxt.uda
count(val: pxt.Date | None) -> pxt.Int
# Signature 13:
@pxt.uda
count(val: pxt.UUID | None) -> pxt.Int
# Signature 14:
@pxt.uda
count(val: pxt.Binary | None) -> pxt.Int
```
Aggregate function that counts the number of non-null values in a column or grouping.
**Parameters:**
* **`val`** (`String | None`): The value to count.
**Returns:**
* `pxt.Int`: The count of non-null values.
**Examples:**
Count the number of non-null values in the `value` column of the table `tbl`:
```python theme={null}
tbl.select(pxt.functions.count(tbl.value)).collect()
```
Group by the `category` column and compute the count of non-null values in the `value` column for each category, assigning the name `'category_count'` to the new column:
```python theme={null}
tbl.group_by(tbl.category).select(
tbl.category, category_count=pxt.functions.count(tbl.value)
).collect()
```
## uda max()
```python Signatures theme={null}
# Signature 1:
@pxt.uda
max(val: pxt.String | None) -> pxt.String | None
# Signature 2:
@pxt.uda
max(val: pxt.Int | None) -> pxt.Int | None
# Signature 3:
@pxt.uda
max(val: pxt.Float | None) -> pxt.Float | None
# Signature 4:
@pxt.uda
max(val: pxt.Bool | None) -> pxt.Bool | None
# Signature 5:
@pxt.uda
max(val: pxt.Timestamp | None) -> pxt.Timestamp | None
```
Aggregate function that computes the maximum value in a column or grouping.
**Parameters:**
* **`val`** (`String | None`): The value to compare.
**Returns:**
* `pxt.String | None`: The maximum value, or `None` if there are no non-null values.
**Examples:**
Compute the maximum value in the `value` column of the table `tbl`:
```python theme={null}
tbl.select(pxt.functions.max(tbl.value)).collect()
```
Group by the `category` column and compute the maximum value in the `value` column for each category, assigning the name `'category_max'` to the new column:
```python theme={null}
tbl.group_by(tbl.category).select(
tbl.category, category_max=pxt.functions.max(tbl.value)
).collect()
```
## uda mean()
```python Signatures theme={null}
# Signature 1:
@pxt.uda
mean(val: pxt.Int | None) -> pxt.Float | None
# Signature 2:
@pxt.uda
mean(val: pxt.Float | None) -> pxt.Float | None
```
Aggregate function that computes the mean (average) of non-null values of a numeric column or grouping.
**Parameters:**
* **`val`** (`Int | None`): The numeric value to include in the mean.
**Returns:**
* `pxt.Float | None`: The mean of the non-null values, or `None` if there are no non-null values.
**Examples:**
Compute the mean of the values in the `value` column of the table `tbl`:
```python theme={null}
tbl.select(pxt.functions.mean(tbl.value)).collect()
```
Group by the `category` column and compute the mean of the `value` column for each category, assigning the name `'category_mean'` to the new column:
```python theme={null}
tbl.group_by(tbl.category).select(
tbl.category, category_mean=pxt.functions.mean(tbl.value)
).collect()
```
## uda min()
```python Signatures theme={null}
# Signature 1:
@pxt.uda
min(val: pxt.String | None) -> pxt.String | None
# Signature 2:
@pxt.uda
min(val: pxt.Int | None) -> pxt.Int | None
# Signature 3:
@pxt.uda
min(val: pxt.Float | None) -> pxt.Float | None
# Signature 4:
@pxt.uda
min(val: pxt.Bool | None) -> pxt.Bool | None
# Signature 5:
@pxt.uda
min(val: pxt.Timestamp | None) -> pxt.Timestamp | None
```
Aggregate function that computes the minimum value in a column or grouping.
**Parameters:**
* **`val`** (`String | None`): The value to compare.
**Returns:**
* `pxt.String | None`: The minimum value, or `None` if there are no non-null values.
**Examples:**
Compute the minimum value in the `value` column of the table `tbl`:
```python theme={null}
tbl.select(pxt.functions.min(tbl.value)).collect()
```
Group by the `category` column and compute the minimum value in the `value` column for each category, assigning the name `'category_min'` to the new column:
```python theme={null}
tbl.group_by(tbl.category).select(
tbl.category, category_min=pxt.functions.min(tbl.value)
).collect()
```
## uda sum()
```python Signatures theme={null}
# Signature 1:
@pxt.uda
sum(val: pxt.Int | None) -> pxt.Int | None
# Signature 2:
@pxt.uda
sum(val: pxt.Float | None) -> pxt.Float | None
```
Aggregate function that computes the sum of non-null values of a numeric column or grouping.
**Parameters:**
* **`val`** (`Int | None`): The numeric value to add to the sum.
**Returns:**
* `pxt.Int | None`: The sum of the non-null values, or `None` if there are no non-null values.
**Examples:**
Sum the values in the `value` column of the table `tbl`:
```python theme={null}
tbl.select(pxt.functions.sum(tbl.value)).collect()
```
Group by the `category` column and compute the sum of the `value` column for each category, assigning the name `'category_total'` to the new column:
```python theme={null}
tbl.group_by(tbl.category).select(
tbl.category, category_total=pxt.functions.sum(tbl.value)
).collect()
```
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