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dataframe/docs/StardustDocs/topics/drop.md

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+[//]: # (title: drop / dropNulls / dropNaNs / dropNA)
+
+<!---IMPORT org.jetbrains.kotlinx.dataframe.samples.api.Access-->
+
+Removes all rows that satisfy [row condition](DataRow.md#row-conditions)
+
+**Related operations**: [](filterRows.md)
+
+<!---FUN dropWhere-->
+<tabs>
+<tab title="Properties">
+
+```kotlin
+df.drop { weight == null || city == null }
+```
+
+</tab>
+<tab title="Strings">
+
+```kotlin
+df.drop { it["weight"] == null || it["city"] == null }
+```
+
+</tab></tabs>
+<inline-frame src="resources/org.jetbrains.kotlinx.dataframe.samples.api.Access.dropWhere.html" width="100%"/>
+<!---END-->
+
+## dropNulls
+
+Remove rows with `null` values. This is a DataFrame equivalent of `filterNotNull`.
+
+See [column selectors](ColumnSelectors.md) for how to select the columns for this operation.
+
+<!---FUN dropNulls-->
+
+```kotlin
+df.dropNulls() // remove rows with null value in any column
+df.dropNulls(whereAllNull = true) // remove rows with null values in all columns
+df.dropNulls { city } // remove rows with null value in 'city' column
+df.dropNulls { city and weight } // remove rows with null value in 'city' OR 'weight' columns
+df.dropNulls(whereAllNull = true) { city and weight } // remove rows with null value in 'city' AND 'weight' columns
+```
+
+<inline-frame src="resources/org.jetbrains.kotlinx.dataframe.samples.api.Access.dropNulls.html" width="100%"/>
+<!---END-->
+
+## dropNaNs
+
+Remove rows with [`NaN` values](nanAndNa.md#nan) (`Double.NaN` or `Float.NaN`).
+
+See [column selectors](ColumnSelectors.md) for how to select the columns for this operation.
+
+<!---FUN dropNaNs-->
+
+```kotlin
+df.dropNaNs() // remove rows containing NaN in any column
+df.dropNaNs(whereAllNaN = true) // remove rows with NaN in all columns
+df.dropNaNs { weight } // remove rows where 'weight' is NaN
+df.dropNaNs { age and weight } // remove rows where either 'age' or 'weight' is NaN
+df.dropNaNs(whereAllNaN = true) { age and weight } // remove rows where both 'age' and 'weight' are NaN
+```
+
+<inline-frame src="resources/org.jetbrains.kotlinx.dataframe.samples.api.Access.dropNaNs.html" width="100%"/>
+<!---END-->
+
+## dropNA
+
+Remove rows with [`NA` values](nanAndNa.md#na) (`null`, `Double.NaN`, or `Float.NaN`).
+
+See [column selectors](ColumnSelectors.md) for how to select the columns for this operation.
+
+<!---FUN dropNA-->
+
+```kotlin
+df.dropNA() // remove rows containing null or NaN in any column
+df.dropNA(whereAllNA = true) // remove rows with null or NaN in all columns
+df.dropNA { weight } // remove rows where 'weight' is null or NaN
+df.dropNA { age and weight } // remove rows where either 'age' or 'weight' is null or NaN
+df.dropNA(whereAllNA = true) { age and weight } // remove rows where both 'age' and 'weight' are null or NaN
+```
+
+<inline-frame src="resources/org.jetbrains.kotlinx.dataframe.samples.api.Access.dropNA.html" width="100%"/>
+<!---END-->