print(row['firstname'] + "," +row['lastname']) Frequently Asked Questions What are the different ways to iterate the rows of a PySpark DataFrame? There are several ways to iterate through rows of a DataFrame in PySpark. We can use methods likecollect(),foreach(),toLocalIterator(), or...
Like any other data structure, Pandas Series also has a way to iterate (loop through) over rows and access elements of each row. You can use the for loop to iterate over the pandas Series. AdvertisementsYou can also use multiple functions to iterate over a pandas Series like iteritems(),...
I want to iterate every row of a dataframe without using collect. Here is my current implementation: val df = spark.read.csv("/tmp/s0v00fc/test_dir") import scala.collection.mutable.Map var m1 = Map[Int, Int]() var m4 = Map[Int, Int]() var j = 1 def Test(m:Int, ...
\Documents\ArcGIS\Default.gdb" fc = ws + "\\MyFeatureClass" #create a NumPy array from the input feature class nparr = arcpy.da.FeatureClassToNumPyArray(fc, '*') #create a pandas DataFrame object from the NumPy array df = DataFrame(nparr, columns=['ObjectId', 'Lay...
<generator object DataFrame.items at 0x7f3c064c1900> We can use this to generate pairs ofcol_nameanddata. These pairs will contain a column name and every row of data for that column. Let's loop through column names and their data: ...