Participants

The participants object used for fetching information about individual survey user data. It automatically creates a Pandas DataFrame in the background of the process.

egytech_api.core.Participants(egytech_api.models.ParticipantsQueryParams)

Attributes

Name	Type	Description	Allowed Values
title [Optional]	string	The job title of requested participants.	['ai_automation', 'backend', 'crm', 'data_analytics', 'data_engineer', 'data_scientist', 'devops_sre_platform', 'embedded', 'engineering_manager', 'executive', 'frontend', 'fullstack', 'hardware', 'mobile', 'product_manager', 'product_owner', 'research', 'scrum', 'security', 'system_arch', 'technical_support', 'testing', 'ui_ux']
level [Optional]	string	The career level of requested participants.	['c_level', 'director', 'group_product_manager', 'intern', 'junior', 'manager', 'mid_level', 'principal', 'senior', 'senior_manager', 'senior_principal', 'senior_staff', 'staff', 'team_lead', 'vp']
min_yoe [Optional]	integer	The minimum years of experience for participants to be included in the query results.	Integer between 0 and 20
max_yoe [Optional]	integer	The maximum years of experience for participants to be included in the query results.	Integer between 1 and 26.
gender [Optional]	string	The gender of participants included in the query results.	['male', 'female']
cs_degree [Optional]	boolean	Whether the included participants have a computer science degree or not.	True, False
business_market [Optional]	string	The market scope of the included participants' companies.	['global', 'regional', 'local']
business_size [Optional]	string	The size of the included participants' companies.	['large', 'medium', 'small']
business_focus [Optional]	string	The primary business focus of the included participants' companies.	['product', 'software_house']
business_line [Optional]	string	The business line the participants' companies operate in.	['b2b', 'b2c', 'both']
include_relocated [Optional]	boolean	Include participants who have relocated.	True, False
include_remote [Optional]	boolean	Include participants who work remotely for companies abroad.	True, False

Note: Attribute ordering on instance creation doesn't matter. Although not recommended, a dictionary can also be used instead of attributes to create a Participants instance.

Note: The supported values for query parameters in the API call differ with cs_degree vs include_relocated and include_remote. Allowed user inputs are boolean, as all of them have 2 possible values. At pydantic model serialization level (the step that produces the dictionary to-be-used for the API call query parameters), this is fixed and only egytech fyi api-supported values are used.

Methods

get_df()

Returns a pandas.DataFrame instance of the fetched data.

Parameters

No parameters

Returns

Type	Description
pandas.DataFrame	A pandas.DataFrame instance containing the fetched data as one row per fetched participant survey.

save_csv(filename: str)

Parameters

Name	Type	Description	Example
filename	str	The name of the .csv file to dump the fetched data in (without extension). No extension is needed explicitly as it's added during the file-saving process.	"my_awesome_data"

Returns

None

This method is simply a placeholder for the pandas.DataFrame.to_csv() method. It simply saves the generated pandas.DataFrame instance to a .csv file and excludes the index. You can customize your own function parameters for this by simply calling the get_df() method, and manipulating the resulting pandas.DataFrame as you want.

save_excel(filename: str)

Parameters

Name	Type	Description	Example
filename	str	The name of the .xlsx file to dump the fetched data in (without extension). No extension is needed explicitly as it's added during the file-saving process.	"my_awesome_data"

Returns

None

This method is simply a placeholder for the pandas.DataFrame.to_excel() method. It simply saves the generated pandas.DataFrame instance to a .xlsx file and excludes the index. You can customize your own function parameters for this by simply calling the get_df() method, and manipulating the resulting pandas.DataFrame as you want.

This function uses "xlsxwriter" as the excel writer engine by default. Customization is available by calling to_excel() on a pandas.DataFrame instead.