You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 donor
【Schema】
# Table: donations
[
(donationid:TEXT, Primary Key, Examples: [000000a91a14ed37bef82e125c102e77]),
(projectid:TEXT, Examples: [ffffac55ee02a49d1abc87ba6fc61135]),
(donor_acctid:TEXT, Examples: [22cbc920c9b5fa08dfb331422f5926b5]),
(donor_city:TEXT, Examples: [Peachtree City, Rockville, Salem]),
(donor_state:TEXT, Examples: [GA, MD, IN]),
(donor_zip:TEXT, Examples: [30269, 20853, 47167]),
(is_teacher_acct:TEXT, Examples: [f, t]),
(donation_timestamp:DATETIME, Examples: [2011-08-25 14:27:34.807000]),
(donation_to_project:REAL, Examples: [42.5, 26.83, 55.35]),
(donation_optional_support:REAL, Examples: [7.5, 4.73, 0.0]),
(donation_total:REAL, Examples: [50.0, 31.56, 55.35]),
(dollar_amount:TEXT, Examples: [10_to_100, under_10, 100_and_up]),
(donation_included_optional_support:TEXT, Examples: [t, f]),
(payment_method:TEXT, Examples: [no_cash_received, creditcard, paypal]),
(payment_included_acct_credit:TEXT, Examples: [f, t]),
(payment_included_campaign_gift_card:TEXT, Examples: [t, f]),
(payment_included_web_purchased_gift_card:TEXT, Examples: [f, t]),
(payment_was_promo_matched:TEXT, Examples: [f, t]),
(via_giving_page:TEXT, Examples: [f, t]),
(for_honoree:TEXT, Examples: [f, t]),
(donation_message:TEXT)
]
# Table: projects
[
(projectid:TEXT, Primary Key, Examples: [00001ccc0e81598c4bd86bacb94d7acb]),
(teacher_acctid:TEXT, Examples: [42d43fa6f37314365d08692e08680973]),
(schoolid:TEXT, Examples: [c0e6ce89b244764085691a1b8e28cb81]),
(school_ncesid:TEXT, Examples: [063627006187, 483702008193, 410327000109]),
(school_latitude:REAL, Examples: [36.57634, 32.911179, 45.166039]),
(school_longitude:REAL, Examples: [-119.608713, -96.72364, -122.414576]),
(school_city:TEXT, Examples: [Selma, Dallas, Colton]),
(school_state:TEXT, Examples: [CA, TX, OR]),
(school_zip:INTEGER, Examples: [93662, 75243, 97017]),
(school_metro:TEXT, Examples: [urban, rural, suburban]),
(school_district:TEXT, Examples: [Selma Unified Sch District]),
(school_county:TEXT, Examples: [Fresno, Dallas, Clackamas]),
(school_charter:TEXT, Examples: [f, t]),
(school_magnet:TEXT, Examples: [f, t]),
(school_year_round:TEXT, Examples: [f, t]),
(school_nlns:TEXT, Examples: [f, t]),
(school_kipp:TEXT, Examples: [f, t]),
(school_charter_ready_promise:TEXT, Examples: [f, t]),
(teacher_prefix:TEXT, Examples: [Mrs., Mr., Ms.]),
(teacher_teach_for_america:TEXT, Examples: [f, t]),
(teacher_ny_teaching_fellow:TEXT, Examples: [f, t]),
(primary_focus_subject:TEXT, Examples: [Literature & Writing, Literacy, Social Sciences]),
(primary_focus_area:TEXT, Examples: [Literacy & Language, History & Civics, Math & Science]),
(secondary_focus_subject:TEXT, Examples: [College & Career Prep]),
(secondary_focus_area:TEXT, Examples: [Applied Learning, Literacy & Language, Math & Science]),
(resource_type:TEXT, Examples: [Books, Technology, Other]),
(poverty_level:TEXT, Examples: [highest poverty, high poverty, moderate poverty]),
(grade_level:TEXT, Examples: [Grades 6-8, Grades PreK-2, Grades 3-5]),
(fulfillment_labor_materials:REAL, Examples: [30.0, 35.0, 9.0]),
(total_price_excluding_optional_support:REAL, Examples: [555.81, 296.47, 430.89]),
(total_price_including_optional_support:REAL, Examples: [653.89, 348.79, 506.93]),
(students_reached:INTEGER, Examples: [32, 22, 17]),
(eligible_double_your_impact_match:TEXT, Examples: [f, t]),
(eligible_almost_home_match:TEXT, Examples: [f, t]),
(date_posted:DATE, Examples: [2014-05-12])
]
# Table: essays
[
(projectid:TEXT, Examples: [ffffc4f85b60efc5b52347df489d0238]),
(teacher_acctid:TEXT, Examples: [c24011b20fc161ed02248e85beb59a90]),
(title:TEXT, Examples: [iMath]),
(short_description:TEXT),
(need_statement:TEXT),
(essay:TEXT)
]
# Table: resources
[
(resourceid:TEXT, Primary Key, Examples: [0000037fecc4461faf0e49328ae66661]),
(projectid:TEXT, Examples: [ffffc4f85b60efc5b52347df489d0238]),
(vendorid:INTEGER, Examples: [430, 82, 767]),
(vendor_name:TEXT, Examples: [Woodwind and Brasswind]),
(project_resource_type:TEXT, Examples: [Technology, Supplies, Other]),
(item_name:TEXT),
(item_number:TEXT, Examples: [249995.001, BB11216668, VX748]),
(item_unit_price:REAL, Examples: [149.0, 148.0, 69.95]),
(item_quantity:INTEGER, Examples: [4, 1, 2])
]
【Foreign keys】
donations.projectid=projects.projectid
resources.projectid=projects.projectid

    【Question】
    For the all donations to the project 'Bringing Drama to Life', what is the percentage of the donation is paid by credit card? Bringing Drama to Life' is the title; Percentage = Divide(Count(payment_method = 'creditcard'), Count(projectid))*100;

    【Evidence】
    Bringing Drama to Life' is the title; Percentage = Divide(Count(payment_method = 'creditcard'), Count(projectid))*100;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT CAST(SUM(CASE WHEN T2.payment_method LIKE 'creditcard' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(donationid) FROM essays AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T1.title LIKE 'Bringing Drama to Life'