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    <title>topic Re: How to apply Pandas functions on PySpark DataFrame? in Data Engineering</title>
    <link>https://community.databricks.com/t5/data-engineering/how-to-apply-pandas-functions-on-pyspark-dataframe/m-p/26175#M18288</link>
    <description>&lt;P&gt;Thanks for your reply. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I want to apply Pandas function on PySpark DataFrame (like how I use Pandas on DataFrames on a local laptop). But, I think the above example uses PySpark function "filter". &lt;/P&gt;</description>
    <pubDate>Sun, 23 Oct 2022 22:06:06 GMT</pubDate>
    <dc:creator>Mado</dc:creator>
    <dc:date>2022-10-23T22:06:06Z</dc:date>
    <item>
      <title>How to apply Pandas functions on PySpark DataFrame?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-to-apply-pandas-functions-on-pyspark-dataframe/m-p/26173#M18286</link>
      <description>&lt;P&gt;Hi, &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I want to apply Pandas functions (like isna, concat, append, etc) on PySpark DataFrame in such a way that computations are done on multi-node cluster.&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I don't want to convert PySpark DataFrame into Pandas DataFrame since, I think, only one node is used for computation. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;What is the best way you suggest to use Pandas functions on PySpark DataFrame while having all processes on multi-node cluster?&lt;/P&gt;</description>
      <pubDate>Sat, 22 Oct 2022 10:38:00 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-to-apply-pandas-functions-on-pyspark-dataframe/m-p/26173#M18286</guid>
      <dc:creator>Mado</dc:creator>
      <dc:date>2022-10-22T10:38:00Z</dc:date>
    </item>
    <item>
      <title>Re: How to apply Pandas functions on PySpark DataFrame?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-to-apply-pandas-functions-on-pyspark-dataframe/m-p/26174#M18287</link>
      <description>&lt;P&gt;The best is to use pandas on a spark, it is virtually interchangeable so it just different API for Spark data frame&lt;/P&gt;&lt;PRE&gt;&lt;CODE&gt;import pyspark.pandas as ps
&amp;nbsp;
psdf = ps.range(10)
sdf = psdf.to_spark().filter("id &amp;gt; 5")
sdf.show()&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;&lt;/P&gt;</description>
      <pubDate>Sun, 23 Oct 2022 21:00:08 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-to-apply-pandas-functions-on-pyspark-dataframe/m-p/26174#M18287</guid>
      <dc:creator>Hubert-Dudek</dc:creator>
      <dc:date>2022-10-23T21:00:08Z</dc:date>
    </item>
    <item>
      <title>Re: How to apply Pandas functions on PySpark DataFrame?</title>
      <link>https://community.databricks.com/t5/data-engineering/how-to-apply-pandas-functions-on-pyspark-dataframe/m-p/26175#M18288</link>
      <description>&lt;P&gt;Thanks for your reply. &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I want to apply Pandas function on PySpark DataFrame (like how I use Pandas on DataFrames on a local laptop). But, I think the above example uses PySpark function "filter". &lt;/P&gt;</description>
      <pubDate>Sun, 23 Oct 2022 22:06:06 GMT</pubDate>
      <guid>https://community.databricks.com/t5/data-engineering/how-to-apply-pandas-functions-on-pyspark-dataframe/m-p/26175#M18288</guid>
      <dc:creator>Mado</dc:creator>
      <dc:date>2022-10-23T22:06:06Z</dc:date>
    </item>
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