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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.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 addsholds athe newvalue key-valueof delimiter data which we want to eachconvert record,into theJSON user can iterate through the records and add the new key-value to each one.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 headerheaders names.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 areif the user defines fields then it will be false forelse sameit headerwill whichbe istrue. for flat files it's true otherwise false.

Below is an example we are taking true which is for pre defined field. 

"false"true


Parameter : Skip_header

Skip_headerIf usesuser "false" ifdefines the userfields wantsit firstlinewill ofbe flatfiletrue aselse headers
it will be false.
Below is an example .we are taking false which is for predefined fields.

 "true" false


Parameter : Response_key

Response_key is the key in which theour user's JSONdelimiter data will be stored.

stored

Below is an example of the key where  the JSON data will be stored.store datatable. 



"datatable"datatable




JSON to Delimiter

Description :

JSON to Delimiter is used to convert JSON data to Delimiter that represents the object.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 addsholds athe newvalue key-valueof JSON data which needs to eachbe record,converted theinto userdelimiter can iterate through the records and add the new key-value to each one.data.

Below is an example where we usingare giving the key name ['itemsitems'] aswhich keyholds dataour 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.

"\t"t

Parameter : Fields

Files is used in to specify headers name.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 adds a new key onif the flyuser withdefines itsfields valuethen as a static value or dynamic value. Thisit will addbe keyfalse andelse itsit valuewill forbe eachtrue. record. 

Below is an example .we are taking true which is for pre defined field. 

"true"true

Parameter : Skip_header

Skip_headerIf usesuser "false" ifdefines the userfields wantsit firstlinewill ofbe flatfiletrue aselse headers
it will be false.
Below is an example .we are taking false which is for predefined fields.

"false"false

Parameter : 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"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 usedpassed toas 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:

UnpivotAn unpivot operation helpsis inused theto dataconvert transformationsingle process.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: 

PivotIn operationspivot operation we are usedcombining inmultiple pivotingdictionaries data, which involves converting long data to wide data. They are often used in data analysis to transform data(object) into ana easiersingle format.

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 usedwill tobe 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 get['product_data_response']['items'] key.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 to readholds the data from a single line data.

"DataTable"

Parameter : Table_headers

Table_headers specifies the keysequence name that is available insideof the array.converted tuple data. 

Below is an example where we are using a key names Item, CustomeCustomerr and Month thatthe arevalues availableof insidethese key names will appear in same sequence in the arraystuple data.

"Item","Customer","Month"

Parameter : Tuple_key

Tuple_key is the key which is used to save theholds tuple data.

Below is an example where we are using datatable as tuple key.

datatable



Tuple to Singleline

Description: 

Tuple to Singleline operation is used in convert a tuple tointo a single line, which involves taking a tuple and converting it to a singleline string.

Number of Parameters : 3

Parameter : Singleline_keyTuple_key

Singleline_keyTuple_key is used to read the user's tuple data.

Below is an example where we are using DataTable towhich readholds 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, CustomeCustomerr and Month as the newvalues headerof names.these key names will appear in same sequence in the singleline data.

"Item","Customer","Month"

Parameter : Tuple_keySingleline_key

Singleline_key helps in to savestoring the newconverted singleline data.

Below is an example where we are using datatable asto tuplestore keythe singleline data.

"datatable"




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