This article mainly gives you a detailed explanation of python in pandas. Dataframe exclude specific Line Method sample code, the text gives the detailed sample code, I believe that everyone's understanding and learning has a certain reference value, the need for friends to see together below.
Pandas. Dataframe Exclude specific lines
If we want a filter like Excel, as long as one or more of the rows, you c
[Spark] [Python]spark example of obtaining Dataframe from Avro fileGet the file from the following address:Https://github.com/databricks/spark-avro/raw/master/src/test/resources/episodes.avroImport into the HDFS system:HDFs Dfs-put Episodes.avroRead in:Mydata001=sqlcontext.read.format ("Com.databricks.spark.avro"). Load ("Episodes.avro")Interactive Run Results:In [7]: Mydata001=sqlcontext.read.format ("Com.
[Example of a limited record taken in Spark][python]dataframethe continuationIn [4]: Peopledf.select ("Age")OUT[4]: Dataframe[age:bigint]In [5]: Mydf=people.select ("Age")---------------------------------------------------------------------------Nameerror Traceback (most recent)----> 1 Mydf=people.select ("Age")Nameerror:name ' People ' is not definedIn [6]: Mydf=peopledf.select ("Age")In [7]: Mydf.take (3)
dagscheduler.scala:100617/10/03 06:00:34 INFO Scheduler. Dagscheduler:submitting 1 missing tasks from Resultstage 1 (mappartitionsrdd[5) at count at Nativemethodaccessorimpl.java :-2)17/10/03 06:00:34 INFO Scheduler. Taskschedulerimpl:adding Task Set 1.0 with 1 tasks17/10/03 06:00:34 INFO Scheduler. Tasksetmanager:starting task 0.0 in Stage 1.0 (TID 1, localhost, partition 0,node_local, 1999 bytes)17/10/03 06:00:34 INFO executor. Executor:running task 0.0 in Stage 1.0 (TID 1)17/10/03 06:00:34 I
[Spark] [Python] Example of a dataframe in which a limited record is taken:SqlContext = Hivecontext (SC)PEOPLEDF = SqlContext.read.json ("People.json")Peopledf.limit (3). Show ()===[Email protected] ~]$ HDFs dfs-cat People.json{"Name": "Alice", "Pcode": "94304"}{"Name": "Brayden", "age": +, "Pcode": "94304"}{"Name": "Carla", "age": +, "Pcoe": "10036"}{"Name": "Diana", "Age": 46}{"Name": "Etienne", "Pcode":
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