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@vgiri2015
Created September 15, 2016 19:19
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#Create a Method to handle the Non Ascii to Ascii conversion
def nonasciitoascii(unicodestring):
return unicodestring.encode("ascii","ignore")
#Create a Sample Dataframe
from pyspark.sql.window import Window
from pyspark.sql.functions import count, col
from pyspark.sql import Row
d=[ Row(coltype='regular', value="Happy Coding"),
Row(coltype='non ascii', value="hello aåbäcö"),
Row(coltype='non ascii',value="6Â 918Â 417Â 712"),
Row(coltype='non ascii',value="SAN MATEO� �?A "),
Row(coltype='non ascii',value="SAINT-LOUIS (CANADA� � AL)")]
data = sqlContext.createDataFrame(d)
#data.show()
data = sqlContext.createDataFrame(d)
#Apply this Conversion on the Dataframe
convertedudf = udf(nonasciitoascii)
converted = data.select('coltype','value').withColumn('converted',convertedudf(data.value))
converted.show()
@Arpit9873
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Hi , i get this as the output when i run your code . How do i get the correct value for converted ? Please can you help .

+---------+--------------------+-----------+
| coltype| value| converted|
+---------+--------------------+-----------+
| regular| Happy Coding| [B@2d5d8dd4|
|non ascii| hello aåbäcö| [B@1f1744a2|
|non ascii| 6Â 918Â 417Â 712| [B@7fbc580a|
|non ascii| SAN MATEO� �?A |[B@61ef3346|
|non ascii|SAINT-LOUIS (CANA...| [B@534ecdd5|
+---------+--------------------+-----------+

@vdhyani96
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@Arpit9873 I know this is a very old thread, but for anyone else who might come across this one day - You just have to cast the return object as a string like this:

def nonasciitoascii(unicodestring):
    return str(unicodestring.encode("ascii", "replace"))

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