Datasets:

AIAT
/

Machima-humangendataset

	thai_instruction,eng_instruction,table,sql,pandas,real_table
	จำนวนตั๋วทั้งหมดคือเท่าไร?,What is the total number of tickets?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data.shape[0],customer
	มีตั๋วกี่ใบที่อยู่ในสถานะ 'เปิด',How many tickets are in the 'Open' status?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Status'] == 'Open'].shape[0],customer
	เวลาตอบกลับโดยเฉลี่ยสำหรับตั๋วคือเท่าไร?,What is the average response time for tickets?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Response Time (hrs)'].mean(),customer
	มีการปิดตั๋วกี่ใบในการตอบกลับครั้งแรก?,How many tickets were closed on the first response?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['First Contact Resolution'] == 'Yes'].shape[0],customer
	จำนวนการโต้ตอบสูงสุดสำหรับตั๋วคือเท่าใด,What is the maximum number of interactions for a ticket?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Number of Interactions'].max(),customer
	ตั๋วกี่ใบที่มีลำดับความสำคัญ 'สูง'?,How many tickets have a priority of 'High'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Priority'] == 'High'].shape[0],customer
	เวลาแก้ไขขั้นต่ำในหน่วยวันสำหรับตั๋วใดๆ คือเท่าใด,What is the minimum resolution time in days for any ticket?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Resolution Time (days)'].min(),customer
	มีการกำหนดตั๋วใหม่กี่ใบ?,How many tickets were reassigned?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Reassigned'] == 'Yes'].shape[0],customer
	จำนวนการโต้ตอบโดยเฉลี่ยต่อตั๋วคือเท่าใด,What is the average number of interactions per ticket?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Number of Interactions'].mean(),customer
	ตั๋วกี่ใบมีเวลาตอบกลับมากกว่า 2 วัน?,How many tickets have a response time of more than 2 days?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Response Time (hrs)'] > 48].shape[0],customer
	วันเดียวกันมีการเปิดและปิดตั๋วกี่ใบ?,How many tickets were opened and closed on the same day?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[(data['Opened'] == data['Closed']) & (data['Closed'].notna())].shape[0],customer
	ลูกค้าที่ไม่ซ้ำทั้งหมดมีจำนวนเท่าใด,What is the total number of unique customers?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Customer ID'].nunique(),customer
	มีตั๋วกี่ใบที่เลื่อนระดับไปสู่ลำดับความสำคัญที่สูงกว่า,How many tickets escalated to a higher priority?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Priority Escalation'] == 'Yes'].shape[0],customer
	เวลาตอบสนองที่บันทึกไว้นานที่สุดคือเท่าไร?,What is the longest response time recorded?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Response Time (hrs)'].max(),customer
	ตั๋วกี่ใบที่มีการนับการโต้ตอบเป็นศูนย์?,How many tickets have an interaction count of zero?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Number of Interactions'] == 0].shape[0],customer
	เวลาแก้ไขโดยเฉลี่ยสำหรับตั๋วที่มีลำดับความสำคัญ 'ต่ำ' คือเท่าใด,What is the average resolution time for 'Low' priority tickets?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Priority'] == 'Low']['Resolution Time (days)'].mean(),customer
	มีตั๋วกี่ใบที่ได้รับคะแนนความพึงพอใจของลูกค้าที่ 5?,How many tickets received a customer satisfaction rating of 5?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Customer Satisfaction'] == 5].shape[0],customer
	กี่เปอร์เซ็นต์ของตั๋วที่ได้รับการแก้ไขภายในหนึ่งวัน?,What percentage of tickets are resolved within a day?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data[data['Resolution Time (days)'] <= 1].shape[0] / data.shape[0]) * 100,customer
	มีตัวแทนมากกว่าหนึ่งคนจัดการตั๋วกี่ใบ?,How many tickets were handled by more than one agent?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Agents Involved'] > 1].shape[0],customer
	จำนวนการโต้ตอบเฉลี่ยของตั๋วทั้งหมดคือเท่าใด,What is the median number of interactions for all tickets?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Number of Interactions'].median(),customer
	ตั๋วกี่ใบที่ไม่มีตัวแทนที่ได้รับมอบหมาย?,How many tickets have no assigned agent?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Assigned Agent'].isna()].shape[0],customer
	จำนวนตั๋วทั้งหมดที่มีปัญหาร้ายแรงคือเท่าใด,What is the total number of tickets with a critical issue?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Issue Type'] == 'Critical'].shape[0],customer
	มีตั๋วกี่ใบที่ได้รับการแก้ไขหลังจากการโต้ตอบมากกว่า 5 ครั้ง,How many tickets were resolved after more than 5 interactions?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Number of Interactions'] > 5].shape[0],customer
	เวลาแก้ไขที่สั้นที่สุดที่บันทึกไว้คือเท่าใด,What is the shortest resolution time recorded?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Resolution Time (days)'].min(),customer
	มีตั๋วกี่ใบที่มีโน้ตเกิน 100 ตัวอักษร?,How many tickets have notes exceeding 100 characters?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Ticket Notes'].str.len() > 100].shape[0],customer
	เวลาเฉลี่ยในการแก้ปัญหาสำหรับตั๋วที่มีลำดับความสำคัญ 'ด่วน' คือเท่าใด,What is the average resolution time for tickets with priority 'Urgent'?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Priority'] == 'Urgent']['Resolution Time (days)'].mean(),customer
	มีตั๋วกี่ใบที่ได้รับคะแนนความพึงพอใจของลูกค้าต่ำกว่า 3,How many tickets received a customer satisfaction rating below 3?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Customer Satisfaction'] < 3].shape[0],customer
	ตั๋วกี่เปอร์เซ็นต์ที่ต้องการความช่วยเหลือด้านเทคนิค?,What percentage of tickets required technical assistance?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data[data['Technical Assistance'] == 'Yes'].shape[0] / data.shape[0]) * 100,customer
	ในเดือนที่แล้วมีการเปิดตั๋วกี่ใบ?,How many tickets were opened in the last month?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Opened'] >= (pd.Timestamp.now() - pd.DateOffset(days=30))].shape[0],customer
	เวลาตอบกลับเฉลี่ยสำหรับตั๋วทั้งหมดคือเท่าไร?,What is the median response time for all tickets?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data['Response Time (hrs)'].median(),customer
	มีตั๋วกี่ใบที่มีอายุมากกว่าหนึ่งปี?,How many tickets are older than one year?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Opened'] <= (pd.Timestamp.now() - pd.DateOffset(days=365))].shape[0],customer
	จำนวนการโต้ตอบโดยเฉลี่ยสำหรับตั๋วประเด็นสำคัญคือเท่าใด,What is the average number of interactions for critical issue tickets?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Issue Type'] == 'Critical']['Number of Interactions'].mean(),customer
	มีตั๋วกี่ใบที่ถูกยกระดับและปิดในวันเดียวกัน,How many tickets were escalated and closed on the same day?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[(data['Priority Escalation'] == 'Yes') & (data['Opened'] == data['Closed'])].shape[0],customer
	ตั๋วเปิดนานที่สุดเมื่อใด?,What is the longest time a ticket has been open?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(pd.Timestamp.now() - data['Opened'].min()).days,customer
	ตั๋วมีเอกสารแนบกี่ใบ?,How many tickets have attachments?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Attachments'] == 'Yes'].shape[0],customer
	เวลาตอบกลับโดยเฉลี่ยสำหรับตั๋วที่มีลำดับความสำคัญ 'ปานกลาง' คือเท่าใด,What is the average response time for 'Moderate' priority tickets?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Priority'] == 'Moderate']['Response Time (hrs)'].mean(),customer
	ตั๋วถูกเปิดใหม่กี่ใบ?,How many tickets have been reopened?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Status'] == 'Reopened'].shape[0],customer
	มีการจัดการตั๋วกี่เปอร์เซ็นต์โดยไม่มีการติดตามผลจากลูกค้า,What percentage of tickets were handled without any customer follow-up?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data[data['Customer Follow-Up'] == 'No'].shape[0] / data.shape[0]) * 100,customer
	วันหยุดสุดสัปดาห์มีการเปิดตั๋วกี่ใบ?,How many tickets were opened on weekends?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Opened'].dt.dayofweek >= 5].shape[0],customer
	เวลาเฉลี่ยในการแก้ไขสำหรับตั๋วที่มีลำดับความสำคัญ 'สูง' คือเท่าใด,What is the median resolution time for 'High' priority tickets?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Priority'] == 'High']['Resolution Time (days)'].median(),customer
	มีตั๋วกี่ใบที่มีทั้งปัญหาที่มีลำดับความสำคัญสูงและวิกฤติ,How many tickets have both high priority and critical issues?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[(data['Priority'] == 'High') & (data['Issue Type'] == 'Critical')].shape[0],customer
	ตั๋วยังคงเปิดอยู่โดยเฉลี่ยกี่วัน?,What is the average number of days tickets remain open?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(pd.Timestamp.now() - data['Opened']).dt.days.mean(),customer
	มีตั๋วกี่ใบที่ได้รับการติดตามลูกค้ามากกว่า 3 ครั้ง?,How many tickets have received more than 3 customer follow-ups?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Customer Follow-Ups'] > 3].shape[0],customer
	ระยะเวลาที่สั้นที่สุดที่ตั๋วยังคงเปิดอยู่คือเท่าไร?,What is the shortest time a ticket has remained open?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data['Closed'] - data['Opened']).dt.days.min(),customer
	มีตั๋วกี่ใบที่เพิ่มขึ้นเนื่องจากปัญหาทางเทคนิค,How many tickets have escalated due to technical issues?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Escalation Reason'] == 'Technical Issue'].shape[0],customer
	เวลาตอบกลับโดยเฉลี่ยสำหรับตั๋วที่ปิดในวันเดียวกับที่เปิดคือเท่าไร?,What is the average response time for tickets closed on the same day they were opened?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Opened'] == data['Closed']]['Response Time (hrs)'].mean(),customer
	มีตั๋วกี่ใบที่ได้รับการแก้ไขโดยไม่มีการยกระดับ?,How many tickets were resolved without escalation?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[(data['Escalated'] == 'No') & (data['Status'] == 'Resolved')].shape[0],customer
	ตั๋วมีเวลาตอบกลับน้อยกว่า 1 ชั่วโมงกี่เปอร์เซ็นต์,What percentage of tickets have a response time under 1 hour?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,(data[data['Response Time (hrs)'] < 1].shape[0] / data.shape[0]) * 100,customer
	วันหยุดมีการเปิดตั๋วกี่ใบ?,How many tickets were opened on holidays?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Opened'].dt.date.isin(holidays)].shape[0],customer
	จำนวนวันเฉลี่ยในการปิดตั๋วพร้อมเอกสารแนบคือเท่าใด,What is the median number of days tickets with attachments take to close?,"this is a detail of this database it have 3 suffix
	1.start with ###, This is a name of column
	2.start with Description:, This is a Description of column
	3.start with Data Type:, This is a Data Type of column """"""


	###Ticket_ID
	Description: A unique identifier for each ticket.

	Data Type: numerical;

	##Customer_Email
	Description: The email address of the customer (Domain name - @example.com is intentional for user data privacy concern).

	Data Type: Text;


	###Customer_Age
	Description: The age of the customer.

	Data Type: numeric;

	###Customer_Gender
	Description: The gender of the customer.

	Data Type: Categorical;

	###Product_Purchased  Description: The tech product purchased by the customer.

	Data Type: Text;

	###Date_of_Purchase
	Description: The date when the product was purchased.

	Data Type: Date;

	###Ticket_Type
	Description: The type of ticket (e.g., technical issue, billing inquiry, product inquiry).

	Data Type: Categorical;

	###Ticket_Subject
	Description: The subject/topic of the ticket.

	Data Type: Categorical;

	###Ticket_Description
	Description: The description of the customer's issue or inquiry.
	Ticket_Status: The status of the ticket (e.g., open, closed, pending customer response).

	Data Type: Text;

	###Resolution
	Description: The resolution or solution provided for closed tickets.

	Data Type: Text;

	###Ticket_Priority
	Description: The priority level assigned to the ticket (e.g., low, medium, high, critical).

	Data Type: Categorical;

	###Ticket_Channel
	Description: The channel through which the ticket was raised (e.g., email, phone, chat, social media).

	Data Type: Categorical;

	###First_Response_Time
	Description:The time taken to provide the first response to the customer.

	Data Type: Date;

	###Time_to_Resolution
	Description: The time taken to resolve the ticket.

	Data Type: Date;

	###Customer_Satisfaction_Rating
	Description: The customer's satisfaction rating for closed tickets (on a scale of 1 to 5).

	Data Type: Numeric;
	###",,data[data['Attachments'] == 'Yes']['Resolution Time (days)'].median(),customer