Handling json list of dictionaries

Indeed the ideas is to import as single row and fold the array. In most cases using the https://doc.dataiku.com/dss/9.0/preparation/processors/array-fold.html would be enough and would look like this :

However, in your example, if I understand it correctly you have 3 array you want to fold. If you try to apply the array fold processor for the other columns it will perform a combination of all values.

One way to solve this and while still using a visual recipe would mean to split the dataset into 3 separate datasets and concat with pandas via python recipe.

Here is what my flow looks like :

Prepare recipe for each row:

# -*- coding: utf-8 -*-
import dataiku
import pandas as pd, numpy as np
from dataiku import pandasutils as pdu

# Read recipe inputs
dataset1 = dataiku.Dataset("json_1")
df_1 = sample_json_prepared.get_dataframe()
dataset2 = dataiku.Dataset("json_2")
df_2 = sample_json_row2.get_dataframe()
dataset3 = dataiku.Dataset("json_2")
df_3 = sample_json_row2.get_dataframe()



# Compute recipe outputs
# TODO: Write here your actual code that computes the outputs
# NB: DSS supports several kinds of APIs for reading and writing data. Please see doc.

merged_output_df = result = pd.concat([df_1, df_2, df_3], axis=1)


# Write recipe outputs
merged_output = dataiku.Dataset("merged_output")
merged_output.write_with_schema(merged_output_df)

Let me know if this helps or if you have any questions.