create a PySpark Schema for a tuple composed of a list and an array

Question

Can someone help please and tell me what should be the correct PySpark Schema for the following tuple:

([['__label__positif', '__label__négatif', '__label__neutre']], array([[0.60312474, 0.24436191, 0.15254335]]))

Thank you in advance

Answer 1

Have a look at the narrated code below:

import numpy as np

#this is the object you got from the fasttext model
pred = ([['__label__positif', '__label__négatif', '__label__neutre']], np.array([[0.60312474, 0.24436191, 0.15254335]]))
print(pred)

#At first we flatten this object to create a list with 6 elements
pred = [item for sublist in pred for subsubiter in sublist for item in subsubiter]
print(pred)

#pyspark doesn't work that well with numpy and therefore we cast the numpy floats to python floats
pred = [x.item() if type(x) == np.float64 else x for x in pred]
print(pred)

l = [tuple(pred)]

columns = ['one', 'two', 'three', 'four', 'five', 'six']

df=spark.createDataFrame(l, columns)
df.show()

Output:

([['__label__positif', '__label__négatif', '__label__neutre']], array([[0.60312474, 0.24436191, 0.15254335]])) 
['__label__positif', '__label__négatif', '__label__neutre', 0.60312474, 0.24436191, 0.15254335] 
['__label__positif', '__label__négatif', '__label__neutre', 0.60312474, 0.24436191, 0.15254335] 
+----------------+----------------+---------------+----------+----------+----------+ 
|             one|             two|          three|      four|      five|       six| 
+----------------+----------------+---------------+----------+----------+----------+ 
|__label__positif|__label__négatif|__label__neutre|0.60312474|0.24436191|0.15254335| 
+----------------+----------------+---------------+----------+----------+----------+