CODEWITHSUNDEEP
pythonpysparkconcatenation
I. A
I. A

Reputation: 2312

How to Concat 2 column of ArrayType on axis = 1 in Pyspark dataframe?

I have a the following dataframe:

I would like to concatenate the lat and lon into a list. Where mmsi is similar to an ID (This is unique)

+---------+--------------------+--------------------+
|     mmsi|                 lat|                 lon|
+---------+--------------------+--------------------+
|255801480|[47.1018366666666...|[-5.3017783333333...|
|304182000|[44.6343033333333...|[-63.564803333333...|
|304682000|[41.1936, 41.1715...|[-8.7716, -8.7514...|
|305930000|[49.5221333333333...|[-3.6310166666666...|
|306216000|[42.8185133333333...|[-29.853155, -29....|
|477514400|[47.17205, 47.165...|[-58.6317, -58.60...|

Therefore, I would like to concatenate the lat and lon array but on axis = 1, that is, I would like to have at the end a list of lists, in a separate column, like:

[[47.1018366666666, -5.3017783333333], ... ]

How is that could be possible in pyspark dataframe? I have tried concat, but that will return: 

[47.1018366666666, 44.6343033333333, ..., -5.3017783333333, -63.564803333333, ...]

Any help is much appreciated!

Upvotes: 1

Views: 571

Answers (1)

Vamsi Prabhala
Vamsi Prabhala

Reputation: 49260

Starting Spark version 2.4, you can use the inbuilt function arrays_zip.

from pyspark.sql.functions import arrays_zip
df.withColumn('zipped_lat_lon',arrays_zip(df.lat,df.lon)).show()

Upvotes: 1

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