Data Wrangling
Single Line to Multiline
Description :
Single Line to Multiline operation is used to convert Single Line JSON to Multiline JSON.
The resulting JSON string can be used to store or transmit data in a structured format.
Number of Parameters : 1
Parameter : Chopkey
Chopkey Adds a new key on the fly with its value as a static value or dynamic value.
Below is an example where we are using chopkey operation to add new key.
['dataset_response']['data']Delimiter to JSON
Description :
Delimiter to JSON operation is used to convert Delimiter data to JSON data.
The resulting JSON string can be used to store or transmit data in a structured format.
Number of Parameters : 6
Parameter : Key_data
Key_data holds the value of delimiter data which we want to convert into JSON data.
Below is an example where we are using DataTable as key.
['DataTable']Parameter : Delimiter
Delimiter is used to separate values in a list, record or file.
Below is an example where we are using , as delimiter.
,Parameter : Fields
Files is used in to specify headers name, it is not mandatory if the user wants then they can specify the fields else it will be passed as empty and pre defined fields will be generated.
Below is an example where we are using headers Customer ID, Organization Name, Month and Item as header name.
"Customer ID","Organization Name","Month","Item"Parameter : Autodetect_column_names
Autodetect_column_names if the user defines fields then it will be false else it will be true.
Below is an example we are taking true which is for pre defined field.
true
Parameter : Skip_header
If user defines the fields it will be true else it will be false.
Below is an example we are taking false which is for predefined fields.
falseParameter : Response_key
Response_key is the key in which our delimiter data will be stored
Below is an example where the JSON data will be store datatable.
datatable
JSON to Delimiter
Description :
JSON to Delimiter is used to convert JSON data to Delimiter data.
The resulting Delimiter data can be used to store or transmit data in a structured format.
Number of Parameters : 6
Parameter : Key_data
Key_data holds the value of JSON data which needs to be converted into delimiter data.
Below is an example where we are giving the key name ['items'] which holds our JSON data.
['items']Parameter : Delimiter
Delimiter is used to separate values in a list, record, or file.
Below is an example where we using \t as delimiter.
\tParameter : Fields
Files is used in to specify headers name, it is not mandatory if the user wants then they can specify the fields else it will be passed as empty and pre defined fields will be generated.
Below is an example where we are using values like Item1,Item2 and Item3 as header name.
"Item1","Item2","Item3" Parameter : Autodetect_column_names
Autodetect_column_names if the user defines fields then it will be false else it will be true.
Below is an example we are taking true which is for pre defined field.
trueParameter : Skip_header
If user defines the fields it will be true else it will be false.
Below is an example we are taking false which is for predefined fields.
falseParameter : Response_key
Response_key is the key in which our delimiter data will be stored
Below is an example where the JSON data will be store delimiter_data.
delimiter_data
Data Aggregation
Description:
Data aggregation operation is used for the processing of raw data, this will also help in the grouping, summarizing, and processing of the data to make it easier to understand and analyze.
Number of Parameters : 3
Parameter : Agg_data_key
Agg_data_key is passed as empty for multiline data and will have data key in case of single line data.
Below is an example where we using ['product_data_response']['items'] as agg_data_key for singleline data
['product_data_response']['items']
Parameter : Groupby_key
Groupby_key gives key name that the user wants to group by, basically this is a unique identifier in the dataset.
Below is an example where we using Orders as Groupby_key as a unique identifier of a dataset which is having Order and Order Line Items, for the one Order we can have multiple items.
"Orders"Parameter : Array_key
Array_key gives the key where the user wants to hold the common keys, the user can provide any key name
Below is an example where Order Lines holds a common key.
"Order Lines"
Parameter : Array_key_nested_columns
Array_key_nested_columns gives the key name as comma separated keys that should be reflected in the level of groupby_key. This will be outside the array key.
Below is an example where we using id, name and year as column names
"id","name","year"Unpivot
Description:
An unpivot operation is used to convert single object into list of object based on transposed values tracking transpose key name parameters.
Number of Parameters : 2
Parameter : Transpose_key_name
Transpose_key_name used in specify name of key which needs to be transposed
Below is an example where we using bucket_type and bucket_value as values that needs to be transpose.
"bucket_type","bucket_value"
Parameter : Transpose value
Transpose value used in specify the values which needs to be transposed
Below is an example where the transpose values are on_hand, purchase_orders and goods_in_transit
"on_hand", "purchase_orders","goods_in_transit"
Pivot
Description:
In pivot operation we are combining multiple dictionaries (object) into a single dictionary (object) based on the transposed value and the transposed key name provided by the user.
Number of Parameters : 3
Parameter : Get key
Get key is will be passed as empty for multiline data and will have get key in case of single line data.
Below is an example where we are using get key as ['product_data_response']['items'] because of singleline data.
['product_data_response']['items'] Parameter : Transpose_key_name
Transpose_key_name specifies name of the key which needs to be transposed.
Below is an example where we are using Item Id and Item Name as key name.
"Item Id","Item Name"
Parameter : Transpose value
Transpose value specifies which values needs to be transposed.
Below is an example where we are using some particular item ids to be transposed OrderID-1, OrderID-2, OrderID-3
"OrderID-1", "OrderID-2", "OrderID-3"Single Line to Tuple
Description:
Single Line to Tuple operation is used to convert a single line of data to a tuple.
Number of Parameters : 3
Parameter : Singleline_key
Singleline_key helps in reading the dataset from a single line.
Below is an example where we are using a key DataTable holds the single line data.
"DataTable"Parameter : Table_headers
Table_headers specifies the sequence of the converted tuple data.
Below is an example where we are using a key names Item, Customer and Month the values of these key names will appear in same sequence in the tuple data.
"Item","Customer","Month"Parameter : Tuple_key
Tuple_key is the key which is holds tuple data.
Below is an example where we are using datatable as tuple key.
datatableTuple to Singleline
Description:
Tuple to Singleline operation is used in convert a tuple into a single line, which involves taking a tuple and converting it to a singleline string.
Number of Parameters : 3
Parameter : Tuple_key
Tuple_key is used to read the user's tuple data.
Below is an example where we are using DataTable which holds the tuple data .
'DataTable'Parameter : Table_headers
Table_headers are the headers or key name of the new JSON.
Below is an example where we are using key name's Item, Customer and Month as the values of these key names will appear in same sequence in the singleline data.
"Item","Customer","Month"Parameter : Singleline_key
Singleline_key helps in to storing the converted singleline data.
Below is an example where we are using datatable to store the singleline data.
"datatable"