List to DataFrame in pyspark

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Can someone tell me how to convert a list containing strings to a Dataframe in pyspark. I am using python 3.6 with spark 2.2.1. I am just started learning spark environment and my data looks like below

my_data =[['apple','ball','ballon'],['cat','camel','james'],['none','focus','cake']]

Now, i want to create a Dataframe as follows

---------------------------------
|ID | words                     |
---------------------------------
 1  | ['apple','ball','ballon'] |
 2  | ['cat','camel','james']   |

I even want to add ID column which is not associated in the data


You can convert the list to a list of Row objects, then use spark.createDataFrame which will infer the schema from your data:

from pyspark.sql import Row
R = Row('ID', 'words')

# use enumerate to add the ID column
spark.createDataFrame([R(i, x) for i, x in enumerate(my_data)]).show() 
+---+--------------------+
| ID|               words|
+---+--------------------+
|  0|[apple, ball, bal...|
|  1| [cat, camel, james]|
|  2| [none, focus, cake]|
+---+--------------------+

List to DataFrame in pyspark, You can convert the list to a list of Row objects, then use spark.createDataFrame which will infer the schema from your data: from pyspark.sql  Convert the list to data frame. The list can be converted to RDD through parallelize function: # Convert list to RDD rdd = spark.sparkContext.parallelize(data) # Create data frame df = spark.createDataFrame(rdd,schema) print(df.schema) df.show() Complete script


Try this -

data_array = []
for i in range (0,len(my_data)) :
    data_array.extend([(i, my_data[i])])

df = spark.createDataframe(data = data_array, schema = ["ID", "words"])

df.show()

How to create dataframe from list in Spark SQL?, here is how - from pyspark.sql.types import * cSchema = StructType([StructField("​WordList", ArrayType(StringType()))]) # notice extra square  This article shows how to convert a Python dictionary list to a DataFrame in Spark using Python. PySpark Parsing Dictionary as DataFrame" master = "local


Try this -- the simplest approach

  from pyspark.sql import *
  x = Row(utc_timestamp=utc, routine='routine name', message='your message')
  data = [x]
  df = sqlContext.createDataFrame(data) 

PySpark: Convert Python Array/List to Spark Data Frame, PySpark: Convert Python Array/List to Spark Data Frame. Import types. First, let's import the data types we need for the data frame. Create Spark session. Define the schema. Convert the list to data frame. Complete script. Sample output. Summary. This articles show you how to convert a Python dictionary list to a Spark DataFrame. The code snippets runs on Spark 2.x environments. Input. The input data (dictionary list looks like the following):


Convert List to Spark Data Frame in Python / Spark, In Spark, SparkContext.parallelize function can be used to convert list of objects to RDD and then RDD can be converted to DataFrame object through  In Spark, it’s easy to convert Spark Dataframe to Pandas dataframe through one line of code: df_pd = df.toPandas() In this page, I am going to show you how to convert a list of PySpark row objects to a Pandas data frame. Prepare the data frame The fo


Transforming Python Lists into Spark Dataframes, Data represented as dataframes are generally much easier to transform, filter, or write to a target source. In Spark, loading or querying data  Spark version : 2.1 For example, in pyspark, i create a list test_list = [['Hello', 'world'], ['I', 'am', 'fine']] then how to create a dataframe form the test_list, where the dataframe's type is like below: DataFrame[words: array<string>]


pyspark.sql module, DataFrame. schema – a StructType or list of column names. default None. samplingRatio – the sample ratio of rows used for inferring  >>> mvv_array = [int(row.mvv) for row in mvv_list.collect()] >>> mvv_array Out: [1,2,3,4] But if you try the same for the other column, you get: >>> mvv_count = [int(row.count) for row in mvv_list.collect()] Out: TypeError: int() argument must be a string or a number, not 'builtin_function_or_method' This happens because count is a built-in method.