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Move expressions to top-level page
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‎docs/source/index.rst

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user-guide/library
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user-guide/cli
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user-guide/dataframe
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user-guide/expressions
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user-guide/sql/index
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user-guide/configs
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user-guide/faq

‎docs/source/user-guide/dataframe.md

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The query can be executed by calling the `collect` method.
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The API is well documented in the [API reference on docs.rs](https://docs.rs/datafusion/latest/datafusion/dataframe/struct.DataFrame.html)
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The DataFrame struct is part of DataFusion's prelude and can be imported with the following statement.
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```rust
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df.show();
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```
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The DataFrame API is well documented in the [API reference on docs.rs](https://docs.rs/datafusion/latest/datafusion/dataframe/struct.DataFrame.html).
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Refer to the [Expressions Refence](expressions) for available functions for building logical expressions for use with the
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DataFrame API.
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## DataFrame Transformations
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These methods create a new DataFrame after applying a transformation to the logical plan that the DataFrame represents.
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| registry | Return a `FunctionRegistry` used to plan udf's calls. |
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| schema | Returns the schema describing the output of this DataFrame in terms of columns returned, where each column has a name, data type, and nullability attribute. |
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| to_logical_plan | Return the logical plan represented by this DataFrame. |
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# Expressions
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DataFrame methods such as `select` and `filter` accept one or more logical expressions and there are many functions
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available for creating logical expressions. These are documented below.
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Expressions can be chained together using a fluent-style API:
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```rust
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// create the expression `(a > 5) AND (b < 7)`
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col("a").gt(lit(5)).and(col("b").lt(lit(7)))
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```
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## Identifiers
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| Function | Notes |
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| -------- | -------------------------------------------- |
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| col | Reference a column in a dataframe `col("a")` |
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## Literal Values
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| Function | Notes |
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| -------- | -------------------------------------------------- |
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| lit | Literal value such as `lit(123)` or `lit("hello")` |
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## Boolean Expressions
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| Function | Notes |
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| -------- | ----------------------------------------- |
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| and | `and(expr1, expr2)` or `expr1.and(expr2)` |
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| or | `or(expr1, expr2)` or `expr1.or(expr2)` |
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| not | `not(expr)` or `expr.not()` |
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## Comparison Expressions
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| Function | Notes |
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| -------- | --------------------- |
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| eq | `expr1.eq(expr2)` |
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| gt | `expr1.gt(expr2)` |
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| gt_eq | `expr1.gt_eq(expr2)` |
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| lt | `expr1.lt(expr2)` |
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| lt_eq | `expr1.lt_eq(expr2)` |
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| not_eq | `expr1.not_eq(expr2)` |
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## Math Functions
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In addition to the math functions listed here, some Rust operators are implemented for expressions, allowing
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expressions such as `col("a") + col("b")` to be used.
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| Function | Notes |
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| --------------------- | ------------------------------------------------- |
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| abs(x) | absolute value |
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| acos(x) | inverse cosine |
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| asin(x) | inverse sine |
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| atan(x) | inverse tangent |
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| atan2(y, x) | inverse tangent of y / x |
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| ceil(x) | nearest integer greater than or equal to argument |
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| cos(x) | cosine |
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| exp(x) | exponential |
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| floor(x) | nearest integer less than or equal to argument |
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| ln(x) | natural logarithm |
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| log10(x) | base 10 logarithm |
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| log2(x) | base 2 logarithm |
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| power(base, exponent) | base raised to the power of exponent |
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| round(x) | round to nearest integer |
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| signum(x) | sign of the argument (-1, 0, +1) |
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| sin(x) | sine |
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| sqrt(x) | square root |
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| tan(x) | tangent |
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| trunc(x) | truncate toward zero |
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## Conditional Expressions
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| Function | Notes |
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| -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| coalesce | Returns the first of its arguments that is not null. Null is returned only if all arguments are null. It is often used to substitute a default value for null values when data is retrieved for display. |
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| case | CASE expression. Example: `case(expr).when(expr, expr).when(expr, expr).otherwise(expr).end()`. |
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| nullif | Returns a null value if `value1` equals `value2`; otherwise it returns `value1`. This can be used to perform the inverse operation of the `coalesce` expression. |
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## String Expressions
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| Function | Notes |
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| ---------------- | ----- |
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| ascii | |
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| bit_length | |
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| btrim | |
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| char_length | |
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| character_length | |
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| concat | |
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| concat_ws | |
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| chr | |
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| initcap | |
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| left | |
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| length | |
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| lower | |
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| lpad | |
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| ltrim | |
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| md5 | |
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| octet_length | |
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| repeat | |
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| replace | |
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| reverse | |
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| right | |
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| rpad | |
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| rtrim | |
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| digest | |
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| split_part | |
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| starts_with | |
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| strpos | |
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| substr | |
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| translate | |
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| trim | |
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| upper | |
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## Regular Expressions
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| Function | Notes |
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| -------------- | ----- |
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| regexp_match | |
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| regexp_replace | |
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## Temporal Expressions
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| Function | Notes |
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| -------------------- | ------------ |
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| date_part | |
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| date_trunc | |
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| from_unixtime | |
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| to_timestamp | |
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| to_timestamp_millis | |
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| to_timestamp_micros | |
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| to_timestamp_seconds | |
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| now() | current time |
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## Other Expressions
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| Function | Notes |
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| -------- | ----- |
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| array | |
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| in_list | |
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| random | |
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| sha224 | |
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| sha256 | |
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| sha384 | |
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| sha512 | |
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| struct | |
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| to_hex | |
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## Aggregate Functions
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| Function | Notes |
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| ---------------------------------- | ----- |
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| avg | |
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| approx_distinct | |
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| approx_median | |
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| approx_percentile_cont | |
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| approx_percentile_cont_with_weight | |
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| count | |
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| count_distinct | |
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| cube | |
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| grouping_set | |
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| max | |
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| median | |
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| min | |
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| rollup | |
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| sum | |
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## Subquery Expressions
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| Function | Notes |
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| --------------- | --------------------------------------------------------------------------------------------- |
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| exists | |
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| in_subquery | `df1.filter(in_subquery(col("foo"), df2))?` is the equivalent of the SQL `WHERE foo IN <df2>` |
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| not_exists | |
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| not_in_subquery | |
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| scalar_subquery | |
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## User-Defined Function Expressions
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| Function | Notes |
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| ----------- | ----- |
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| create_udf | |
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| create_udaf | |

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