[jira] [Updated] (SPARK-6119) better support for working with missing data
[ https://issues.apache.org/jira/browse/SPARK-6119?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin updated SPARK-6119: --- Description: Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. Some ideas: 1. Support replacing all null value for a column (or all columns) with a fixed value. 2. Support replacing a set of values with another set of values. 3. interpolate was: Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. Some ideas: 1. Support replacing all null value for a column with a fixed value. 2. Support replacing all null value for all columns with a fixed value. better support for working with missing data Key: SPARK-6119 URL: https://issues.apache.org/jira/browse/SPARK-6119 Project: Spark Issue Type: Sub-task Components: SQL Reporter: Reynold Xin Labels: DataFrame Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. Some ideas: 1. Support replacing all null value for a column (or all columns) with a fixed value. 2. Support replacing a set of values with another set of values. 3. interpolate -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-6119) better support for working with missing data
[ https://issues.apache.org/jira/browse/SPARK-6119?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin updated SPARK-6119: --- Labels: DataFrame (was: ) better support for working with missing data Key: SPARK-6119 URL: https://issues.apache.org/jira/browse/SPARK-6119 Project: Spark Issue Type: Sub-task Components: SQL Reporter: Reynold Xin Labels: DataFrame Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-6119) better support for working with missing data
[ https://issues.apache.org/jira/browse/SPARK-6119?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin updated SPARK-6119: --- Summary: better support for working with missing data (was: missing data support) better support for working with missing data Key: SPARK-6119 URL: https://issues.apache.org/jira/browse/SPARK-6119 Project: Spark Issue Type: Sub-task Components: SQL Reporter: Reynold Xin Labels: DataFrame Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-6119) better support for working with missing data
[ https://issues.apache.org/jira/browse/SPARK-6119?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin updated SPARK-6119: --- Description: Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. Some ideas: 1. Support replacing all null value for a column with a fixed value. 2. Support replacing all null value for all columns with a fixed value. was: Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. better support for working with missing data Key: SPARK-6119 URL: https://issues.apache.org/jira/browse/SPARK-6119 Project: Spark Issue Type: Sub-task Components: SQL Reporter: Reynold Xin Labels: DataFrame Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. Some ideas: 1. Support replacing all null value for a column with a fixed value. 2. Support replacing all null value for all columns with a fixed value. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-6119) better support for working with missing data
[ https://issues.apache.org/jira/browse/SPARK-6119?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin updated SPARK-6119: --- Description: Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. Some ideas: 1. Support replacing all null value for a column (or all columns) with a fixed value. 2. Support dropping rows with null values (dropna). 3. Support replacing a set of values with another set of values (i.e. map join) was: Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. Some ideas: 1. Support replacing all null value for a column (or all columns) with a fixed value. 2. Support replacing a set of values with another set of values. 3. interpolate better support for working with missing data Key: SPARK-6119 URL: https://issues.apache.org/jira/browse/SPARK-6119 Project: Spark Issue Type: Sub-task Components: SQL Reporter: Reynold Xin Labels: DataFrame Real world data can be messy. An important feature of data frames is support for missing data. We should figure out what we want to do here. Some ideas: 1. Support replacing all null value for a column (or all columns) with a fixed value. 2. Support dropping rows with null values (dropna). 3. Support replacing a set of values with another set of values (i.e. map join) -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
