├── Aula_Pandas ├── Aula_Pandas1.ipynb ├── daily-minimum-temperatures-in-me.csv ├── test.csv └── train.csv ├── CRUD_operations └── CRUD_with_SQLite3 │ ├── README.md │ ├── __pycache__ │ ├── data.cpython-38.pyc │ ├── generate_data.cpython-38.pyc │ ├── options.cpython-38.pyc │ └── utils.cpython-38.pyc │ ├── data.db │ ├── generate_data.py │ ├── generate_data.pyc │ ├── main.py │ └── utils.py ├── Machine Learning ├── RegressaoLinear1.html ├── RegressaoLinear1.ipynb └── StudentsPerformanceExams.ipynb ├── README.md ├── Scraping ├── Scraping_stack_overflow.ipynb └── python_stackoverflow.csv ├── StudentsPerformance.csv └── Álgebra Linear ├── Algebra_Linear-Introducao(SymPy-NumPy).html └── Algebra_Linear-Introducao(SymPy-NumPy).ipynb /Aula_Pandas/test.csv: -------------------------------------------------------------------------------- 1 | PassengerId,Pclass,Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked 2 | 892,3,"Kelly, Mr. James",male,34.5,0,0,330911,7.8292,,Q 3 | 893,3,"Wilkes, Mrs. James (Ellen Needs)",female,47,1,0,363272,7,,S 4 | 894,2,"Myles, Mr. Thomas Francis",male,62,0,0,240276,9.6875,,Q 5 | 895,3,"Wirz, Mr. Albert",male,27,0,0,315154,8.6625,,S 6 | 896,3,"Hirvonen, Mrs. Alexander (Helga E Lindqvist)",female,22,1,1,3101298,12.2875,,S 7 | 897,3,"Svensson, Mr. Johan Cervin",male,14,0,0,7538,9.225,,S 8 | 898,3,"Connolly, Miss. 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Stella Anna",female,,8,2,CA. 2343,69.55,,S 795 | 794,0,1,"Hoyt, Mr. William Fisher",male,,0,0,PC 17600,30.6958,,C 796 | 795,0,3,"Dantcheff, Mr. Ristiu",male,25,0,0,349203,7.8958,,S 797 | 796,0,2,"Otter, Mr. Richard",male,39,0,0,28213,13,,S 798 | 797,1,1,"Leader, Dr. Alice (Farnham)",female,49,0,0,17465,25.9292,D17,S 799 | 798,1,3,"Osman, Mrs. Mara",female,31,0,0,349244,8.6833,,S 800 | 799,0,3,"Ibrahim Shawah, Mr. Yousseff",male,30,0,0,2685,7.2292,,C 801 | 800,0,3,"Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert)",female,30,1,1,345773,24.15,,S 802 | 801,0,2,"Ponesell, Mr. Martin",male,34,0,0,250647,13,,S 803 | 802,1,2,"Collyer, Mrs. Harvey (Charlotte Annie Tate)",female,31,1,1,C.A. 31921,26.25,,S 804 | 803,1,1,"Carter, Master. William Thornton II",male,11,1,2,113760,120,B96 B98,S 805 | 804,1,3,"Thomas, Master. Assad Alexander",male,0.42,0,1,2625,8.5167,,C 806 | 805,1,3,"Hedman, Mr. Oskar Arvid",male,27,0,0,347089,6.975,,S 807 | 806,0,3,"Johansson, Mr. Karl Johan",male,31,0,0,347063,7.775,,S 808 | 807,0,1,"Andrews, Mr. Thomas Jr",male,39,0,0,112050,0,A36,S 809 | 808,0,3,"Pettersson, Miss. Ellen Natalia",female,18,0,0,347087,7.775,,S 810 | 809,0,2,"Meyer, Mr. August",male,39,0,0,248723,13,,S 811 | 810,1,1,"Chambers, Mrs. Norman Campbell (Bertha Griggs)",female,33,1,0,113806,53.1,E8,S 812 | 811,0,3,"Alexander, Mr. William",male,26,0,0,3474,7.8875,,S 813 | 812,0,3,"Lester, Mr. James",male,39,0,0,A/4 48871,24.15,,S 814 | 813,0,2,"Slemen, Mr. Richard James",male,35,0,0,28206,10.5,,S 815 | 814,0,3,"Andersson, Miss. Ebba Iris Alfrida",female,6,4,2,347082,31.275,,S 816 | 815,0,3,"Tomlin, Mr. Ernest Portage",male,30.5,0,0,364499,8.05,,S 817 | 816,0,1,"Fry, Mr. Richard",male,,0,0,112058,0,B102,S 818 | 817,0,3,"Heininen, Miss. Wendla Maria",female,23,0,0,STON/O2. 3101290,7.925,,S 819 | 818,0,2,"Mallet, Mr. Albert",male,31,1,1,S.C./PARIS 2079,37.0042,,C 820 | 819,0,3,"Holm, Mr. John Fredrik Alexander",male,43,0,0,C 7075,6.45,,S 821 | 820,0,3,"Skoog, Master. Karl Thorsten",male,10,3,2,347088,27.9,,S 822 | 821,1,1,"Hays, Mrs. Charles Melville (Clara Jennings Gregg)",female,52,1,1,12749,93.5,B69,S 823 | 822,1,3,"Lulic, Mr. Nikola",male,27,0,0,315098,8.6625,,S 824 | 823,0,1,"Reuchlin, Jonkheer. John George",male,38,0,0,19972,0,,S 825 | 824,1,3,"Moor, Mrs. (Beila)",female,27,0,1,392096,12.475,E121,S 826 | 825,0,3,"Panula, Master. Urho Abraham",male,2,4,1,3101295,39.6875,,S 827 | 826,0,3,"Flynn, Mr. John",male,,0,0,368323,6.95,,Q 828 | 827,0,3,"Lam, Mr. Len",male,,0,0,1601,56.4958,,S 829 | 828,1,2,"Mallet, Master. Andre",male,1,0,2,S.C./PARIS 2079,37.0042,,C 830 | 829,1,3,"McCormack, Mr. Thomas Joseph",male,,0,0,367228,7.75,,Q 831 | 830,1,1,"Stone, Mrs. George Nelson (Martha Evelyn)",female,62,0,0,113572,80,B28, 832 | 831,1,3,"Yasbeck, Mrs. Antoni (Selini Alexander)",female,15,1,0,2659,14.4542,,C 833 | 832,1,2,"Richards, Master. George Sibley",male,0.83,1,1,29106,18.75,,S 834 | 833,0,3,"Saad, Mr. Amin",male,,0,0,2671,7.2292,,C 835 | 834,0,3,"Augustsson, Mr. Albert",male,23,0,0,347468,7.8542,,S 836 | 835,0,3,"Allum, Mr. Owen George",male,18,0,0,2223,8.3,,S 837 | 836,1,1,"Compton, Miss. Sara Rebecca",female,39,1,1,PC 17756,83.1583,E49,C 838 | 837,0,3,"Pasic, Mr. Jakob",male,21,0,0,315097,8.6625,,S 839 | 838,0,3,"Sirota, Mr. Maurice",male,,0,0,392092,8.05,,S 840 | 839,1,3,"Chip, Mr. Chang",male,32,0,0,1601,56.4958,,S 841 | 840,1,1,"Marechal, Mr. Pierre",male,,0,0,11774,29.7,C47,C 842 | 841,0,3,"Alhomaki, Mr. Ilmari Rudolf",male,20,0,0,SOTON/O2 3101287,7.925,,S 843 | 842,0,2,"Mudd, Mr. Thomas Charles",male,16,0,0,S.O./P.P. 3,10.5,,S 844 | 843,1,1,"Serepeca, Miss. Augusta",female,30,0,0,113798,31,,C 845 | 844,0,3,"Lemberopolous, Mr. Peter L",male,34.5,0,0,2683,6.4375,,C 846 | 845,0,3,"Culumovic, Mr. Jeso",male,17,0,0,315090,8.6625,,S 847 | 846,0,3,"Abbing, Mr. Anthony",male,42,0,0,C.A. 5547,7.55,,S 848 | 847,0,3,"Sage, Mr. Douglas Bullen",male,,8,2,CA. 2343,69.55,,S 849 | 848,0,3,"Markoff, Mr. Marin",male,35,0,0,349213,7.8958,,C 850 | 849,0,2,"Harper, Rev. John",male,28,0,1,248727,33,,S 851 | 850,1,1,"Goldenberg, Mrs. Samuel L (Edwiga Grabowska)",female,,1,0,17453,89.1042,C92,C 852 | 851,0,3,"Andersson, Master. Sigvard Harald Elias",male,4,4,2,347082,31.275,,S 853 | 852,0,3,"Svensson, Mr. Johan",male,74,0,0,347060,7.775,,S 854 | 853,0,3,"Boulos, Miss. Nourelain",female,9,1,1,2678,15.2458,,C 855 | 854,1,1,"Lines, Miss. Mary Conover",female,16,0,1,PC 17592,39.4,D28,S 856 | 855,0,2,"Carter, Mrs. Ernest Courtenay (Lilian Hughes)",female,44,1,0,244252,26,,S 857 | 856,1,3,"Aks, Mrs. Sam (Leah Rosen)",female,18,0,1,392091,9.35,,S 858 | 857,1,1,"Wick, Mrs. George Dennick (Mary Hitchcock)",female,45,1,1,36928,164.8667,,S 859 | 858,1,1,"Daly, Mr. Peter Denis ",male,51,0,0,113055,26.55,E17,S 860 | 859,1,3,"Baclini, Mrs. Solomon (Latifa Qurban)",female,24,0,3,2666,19.2583,,C 861 | 860,0,3,"Razi, Mr. Raihed",male,,0,0,2629,7.2292,,C 862 | 861,0,3,"Hansen, Mr. Claus Peter",male,41,2,0,350026,14.1083,,S 863 | 862,0,2,"Giles, Mr. Frederick Edward",male,21,1,0,28134,11.5,,S 864 | 863,1,1,"Swift, Mrs. Frederick Joel (Margaret Welles Barron)",female,48,0,0,17466,25.9292,D17,S 865 | 864,0,3,"Sage, Miss. Dorothy Edith ""Dolly""",female,,8,2,CA. 2343,69.55,,S 866 | 865,0,2,"Gill, Mr. John William",male,24,0,0,233866,13,,S 867 | 866,1,2,"Bystrom, Mrs. (Karolina)",female,42,0,0,236852,13,,S 868 | 867,1,2,"Duran y More, Miss. Asuncion",female,27,1,0,SC/PARIS 2149,13.8583,,C 869 | 868,0,1,"Roebling, Mr. Washington Augustus II",male,31,0,0,PC 17590,50.4958,A24,S 870 | 869,0,3,"van Melkebeke, Mr. Philemon",male,,0,0,345777,9.5,,S 871 | 870,1,3,"Johnson, Master. Harold Theodor",male,4,1,1,347742,11.1333,,S 872 | 871,0,3,"Balkic, Mr. Cerin",male,26,0,0,349248,7.8958,,S 873 | 872,1,1,"Beckwith, Mrs. Richard Leonard (Sallie Monypeny)",female,47,1,1,11751,52.5542,D35,S 874 | 873,0,1,"Carlsson, Mr. Frans Olof",male,33,0,0,695,5,B51 B53 B55,S 875 | 874,0,3,"Vander Cruyssen, Mr. Victor",male,47,0,0,345765,9,,S 876 | 875,1,2,"Abelson, Mrs. Samuel (Hannah Wizosky)",female,28,1,0,P/PP 3381,24,,C 877 | 876,1,3,"Najib, Miss. Adele Kiamie ""Jane""",female,15,0,0,2667,7.225,,C 878 | 877,0,3,"Gustafsson, Mr. Alfred Ossian",male,20,0,0,7534,9.8458,,S 879 | 878,0,3,"Petroff, Mr. Nedelio",male,19,0,0,349212,7.8958,,S 880 | 879,0,3,"Laleff, Mr. Kristo",male,,0,0,349217,7.8958,,S 881 | 880,1,1,"Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)",female,56,0,1,11767,83.1583,C50,C 882 | 881,1,2,"Shelley, Mrs. William (Imanita Parrish Hall)",female,25,0,1,230433,26,,S 883 | 882,0,3,"Markun, Mr. Johann",male,33,0,0,349257,7.8958,,S 884 | 883,0,3,"Dahlberg, Miss. Gerda Ulrika",female,22,0,0,7552,10.5167,,S 885 | 884,0,2,"Banfield, Mr. Frederick James",male,28,0,0,C.A./SOTON 34068,10.5,,S 886 | 885,0,3,"Sutehall, Mr. Henry Jr",male,25,0,0,SOTON/OQ 392076,7.05,,S 887 | 886,0,3,"Rice, Mrs. William (Margaret Norton)",female,39,0,5,382652,29.125,,Q 888 | 887,0,2,"Montvila, Rev. Juozas",male,27,0,0,211536,13,,S 889 | 888,1,1,"Graham, Miss. Margaret Edith",female,19,0,0,112053,30,B42,S 890 | 889,0,3,"Johnston, Miss. Catherine Helen ""Carrie""",female,,1,2,W./C. 6607,23.45,,S 891 | 890,1,1,"Behr, Mr. Karl Howell",male,26,0,0,111369,30,C148,C 892 | 891,0,3,"Dooley, Mr. Patrick",male,32,0,0,370376,7.75,,Q 893 | -------------------------------------------------------------------------------- /CRUD_operations/CRUD_with_SQLite3/README.md: -------------------------------------------------------------------------------- 1 | # CRUD 2 | CRUD with Python and SQLite3. 3 | -------------------------------------------------------------------------------- /CRUD_operations/CRUD_with_SQLite3/__pycache__/data.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ronissonlucas/data_science/61981dbb6635dd0e09923f84c826b3506d80d647/CRUD_operations/CRUD_with_SQLite3/__pycache__/data.cpython-38.pyc -------------------------------------------------------------------------------- /CRUD_operations/CRUD_with_SQLite3/__pycache__/generate_data.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ronissonlucas/data_science/61981dbb6635dd0e09923f84c826b3506d80d647/CRUD_operations/CRUD_with_SQLite3/__pycache__/generate_data.cpython-38.pyc -------------------------------------------------------------------------------- /CRUD_operations/CRUD_with_SQLite3/__pycache__/options.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ronissonlucas/data_science/61981dbb6635dd0e09923f84c826b3506d80d647/CRUD_operations/CRUD_with_SQLite3/__pycache__/options.cpython-38.pyc -------------------------------------------------------------------------------- /CRUD_operations/CRUD_with_SQLite3/__pycache__/utils.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ronissonlucas/data_science/61981dbb6635dd0e09923f84c826b3506d80d647/CRUD_operations/CRUD_with_SQLite3/__pycache__/utils.cpython-38.pyc -------------------------------------------------------------------------------- /CRUD_operations/CRUD_with_SQLite3/data.db: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ronissonlucas/data_science/61981dbb6635dd0e09923f84c826b3506d80d647/CRUD_operations/CRUD_with_SQLite3/data.db -------------------------------------------------------------------------------- /CRUD_operations/CRUD_with_SQLite3/generate_data.py: -------------------------------------------------------------------------------- 1 | import sqlite3 2 | from contextlib import closing 3 | 4 | def create_data(): 5 | 6 | with sqlite3.connect('data.db') as conn: 7 | with closing(conn.cursor()) as cursor: 8 | cursor.execute("""CREATE TABLE IF NOT EXISTS work( 9 | id INTEGER PRIMARY KEY AUTOINCREMENT, 10 | occupation VARCHAR(20) NOT NULL 11 | )""") 12 | 13 | with sqlite3.connect('data.db') as conn: 14 | with closing(conn.cursor()) as cursor: 15 | cursor.execute("""CREATE TABLE IF NOT EXISTS college( 16 | id INTEGER PRIMARY KEY AUTOINCREMENT, 17 | college_name VARCHAR(30) NOT NULL 18 | )""") 19 | 20 | with sqlite3.connect('data.db') as conn: 21 | with closing(conn.cursor()) as cursor: 22 | cursor.execute("""CREATE TABLE IF NOT EXISTS customer( 23 | id INTEGER PRIMARY KEY AUTOINCREMENT, 24 | name VARCHAR(60) NOT NULL, 25 | age INTEGER NOT NULL, 26 | phone VARCHAR(11) NOT NULL, 27 | id_occupation INTEGER, 28 | id_college INTEGER, 29 | FOREIGN KEY (id_occupation) REFERENCES work(id), 30 | FOREIGN KEY (id_college) REFERENCES college(id) 31 | )""") -------------------------------------------------------------------------------- /CRUD_operations/CRUD_with_SQLite3/generate_data.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ronissonlucas/data_science/61981dbb6635dd0e09923f84c826b3506d80d647/CRUD_operations/CRUD_with_SQLite3/generate_data.pyc -------------------------------------------------------------------------------- /CRUD_operations/CRUD_with_SQLite3/main.py: -------------------------------------------------------------------------------- 1 | from generate_data import create_data 2 | from utils import Data 3 | 4 | if __name__ == "__main__": 5 | create_data() 6 | data = Data('data.db') 7 | data.insert_college('Harvard') 8 | data.insert_college('Oxford') 9 | data.insert_college('USP') 10 | data.insert_college('UFBA') 11 | data.insert_occupation('Student') 12 | data.insert_one_customer('Yun', 25, '+0000000', 1, 1) 13 | data.insert_customers([ 14 | ('Chang', 27, '+8888888', 1, 2), 15 | ('Ping', 21, '+11111111', 1, 3)]) 16 | data.list_colleges() 17 | data.list_customers() 18 | data.list_occupations() 19 | data.del_customer_by_id(1) 20 | 21 | 22 | data.close_connection() 23 | 24 | 25 | 26 | -------------------------------------------------------------------------------- /CRUD_operations/CRUD_with_SQLite3/utils.py: -------------------------------------------------------------------------------- 1 | import sqlite3 2 | 3 | class Data(): 4 | 5 | def __init__(self, data): 6 | 7 | self.conn = sqlite3.connect(data) 8 | self.cursor = self.conn.cursor() 9 | 10 | def check(cursor, conn): 11 | "Function to check changes in the database." 12 | if cursor.rowcount == 1: 13 | conn.commit() 14 | print('Operation performed successfully.') 15 | else: 16 | print('Not found or error.') 17 | 18 | def insert_college(self, college:str): 19 | "Function to insert university records in the database." 20 | try: 21 | sql = f"""INSERT INTO college(college_name) VALUES ('{college}') """ 22 | self.cursor.execute(sql) 23 | except Exception as error: 24 | print(error) 25 | self.conn.rollback() 26 | else: 27 | self.conn.commit() 28 | print(f'The value {college} has been inserted into database.') 29 | 30 | def insert_occupation(self, occupation:str): 31 | "Function to insert occupation records in the database." 32 | try: 33 | sql = f"""INSERT INTO work(occupation) VALUES ('{occupation}') """ 34 | self.cursor.execute(sql) 35 | 36 | except Exception as error: 37 | print(error) 38 | self.conn.rollback() 39 | else: 40 | self.conn.commit() 41 | print(f'The value {occupation} has been inserted into database.') 42 | 43 | def insert_one_customer(self, name:str, 44 | age:int, phone:str, 45 | id_occupation:int, 46 | id_college:int): 47 | "Function to insert one customer record in the database." 48 | try: 49 | sql = """INSERT INTO customer (name, age, phone, id_occupation, id_college) VALUES (?,?,?,?,?) """ 50 | self.cursor.execute(sql, (name, age, phone, id_occupation, id_college)) 51 | except Exception as error: 52 | print(error) 53 | self.conn.rollback() 54 | else: 55 | self.conn.commit() 56 | print('The values were inserted in the table.') 57 | 58 | def insert_customers(self,list_customers:list): 59 | "Function to insert more than one customer record in the database." 60 | if isinstance(list_customers,list): 61 | #check if the inserted value is a list 62 | try: 63 | sql = "INSERT INTO customer(name, age, phone, id_occupation, id_college) VALUES (?,?,?,?,?)" 64 | self.cursor.executemany(sql, list_customers) 65 | except Exception as error: 66 | print(f'Error: {error}') 67 | self.conn.rollback() 68 | else: 69 | print('The values were inserted in the table.') 70 | self.conn.commit() 71 | else: 72 | raise TypeError('Inappropriate argument type.') 73 | 74 | def update_college(self,row_id:int): 75 | "Updates university registration." 76 | try: 77 | new_college_name = input('New college name: ') 78 | sql = f"UPDATE college SET college_name = '{new_college_name}' WHERE id = {row_id}" 79 | self.cursor.execute(sql) 80 | except Exception as error: 81 | print(f'Error: {error}') 82 | self.conn.rollback() 83 | else: 84 | Data.check(self.cursor, self.conn) 85 | 86 | def update_occupation(self, row_id:int): 87 | "Updates occupation registration." 88 | try: 89 | new_occupation = input('New occupation name: ') 90 | sql = f"UPDATE work SET occupation='{new_occupation}' WHERE id = {row_id}" 91 | self.cursor.execute(sql) 92 | except Exception as error: 93 | print(f'Error:{error}') 94 | self.conn.rollback() 95 | else: 96 | Data.check(self.cursor, self.conn) 97 | 98 | def update_customer(self,id_customer:int): 99 | "Updates customer registration." 100 | try: 101 | new_age = input('New age: ') 102 | new_phone = input('New phone: ') 103 | new_occupation = input('New occupation: ') 104 | sql = f"""UPDATE customer SET age = {new_age}, 105 | phone = '{new_phone}', id_occupation = {new_occupation} WHERE id = {id_customer} """ 106 | self.cursor.execute(sql) 107 | except Exception as error: 108 | print(f'Error: {error}') 109 | self.conn.rollback() 110 | else: 111 | Data.check(self.cursor, self.conn) 112 | 113 | def del_college(self,id_college:int): 114 | "Deletes a college record." 115 | try: 116 | self.cursor.execute( 117 | f"""DELETE FROM college WHERE id = ?""", 118 | (id_college,)) 119 | 120 | except Exception as error: 121 | print(f'Error: {error}') 122 | else: 123 | Data.check(self.cursor, self.conn) 124 | 125 | def del_occupation(self, id_occupation:int): 126 | "Deletes an occupation record." 127 | try: 128 | self.cursor.execute( 129 | f"""DELETE FROM work WHERE id = ?""", 130 | (id_occupation,)) 131 | 132 | except Exception as error: 133 | print(f'Error: {error}') 134 | else: 135 | Data.check(self.cursor, self.conn) 136 | 137 | def del_customer_by_id(self, id_customer:int): 138 | "Deletes a customer record by id." 139 | try: 140 | self.cursor.execute( 141 | f"""DELETE FROM customer WHERE id = ?""", 142 | (id_customer,) 143 | ) 144 | except Excpetion as error: 145 | print(f'Error: {error}') 146 | else: 147 | Data.check(self.cursor, self.conn) 148 | 149 | def list_colleges(self): 150 | "Shows all colleges in the database." 151 | try: 152 | self.cursor.execute("SELECT * FROM college") 153 | results = self.cursor.fetchall() 154 | if len(results)>0: 155 | for row_id, value in results: 156 | print(row_id, value) 157 | else: 158 | print('No values to show.') 159 | 160 | except Exception as error: 161 | print(f'Error: {error}') 162 | 163 | def list_occupations(self): 164 | "Shows all occupations in the database." 165 | try: 166 | self.cursor.execute("SELECT * FROM work") 167 | results = self.cursor.fetchall() 168 | if len(results)>0: 169 | for row_id, value in results: 170 | print(row_id, value) 171 | else: 172 | print('No values to show.') 173 | except Exception as error: 174 | print(f'Error: {error}') 175 | 176 | def list_customers(self): 177 | "Shows all customers of the database." 178 | try: 179 | self.conn.row_factory = sqlite3.Row 180 | results = self.cursor.execute("SELECT * FROM customer") 181 | 182 | for record in results: 183 | print('_'*50) 184 | print(f'Record {record[0]}'.center(50,' ')) 185 | print(f'\tName: {record[1]}') 186 | print(f'\tAge: {record[2]}') 187 | print(f'\tPhone: {record[3]}') 188 | print() 189 | print('_'*50) 190 | 191 | except Exception as error: 192 | print(f'Error: {error}') 193 | 194 | def search_customer(self, id_customer:int): 195 | "Fetch a customer by id." 196 | try: 197 | sql = f"""SELECT * FROM customer WHERE id = {id_customer}""" 198 | self.cursor.execute(sql) 199 | result = self.cursor.fetchone() 200 | 201 | except Exception as error: 202 | print(f'Error: {error}') 203 | else: 204 | if len(result)>0: 205 | return (f'Name: {result[1]}', 206 | f'Age: {result[2]}', 207 | f'Phone: {result[3]}', 208 | f'Id Occupation:: {result[4]}', 209 | f'Id college: {result[5]}') 210 | return 'Not found.' 211 | 212 | 213 | def close_connection(self): 214 | "Closes the connection to the server." 215 | self.cursor.close() 216 | self.conn.close() -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Data Science 2 | Repositório de aulas ministradas, notebooks, projetos de aprendizagem e práticas em scraping e SQL. 3 | 4 | 5 | ## Estatística 6 | 7 | [Regressão Linear](https://github.com/ronissonlucas/data_science/blob/main/Machine%20Learning/RegressaoLinear1.ipynb) 8 | 9 | ## Álgebra Linear 10 | 11 | [Introdução à Álgebra Linear usando SymPy e NumPy](https://github.com/ronissonlucas/data_science/blob/main/%C3%81lgebra%20Linear/Algebra_Linear-Introducao(SymPy-NumPy).ipynb) 12 | 13 | 14 | ## Práticas em Machine Learning 15 | 16 | [Students Performance in Exams](https://github.com/ronissonlucas/data_science/blob/main/Machine%20Learning/StudentsPerformanceExams.ipynb) 17 | 18 | ## Scraping 19 | 20 | [Scraping do StackOverflow - Perguntas sobre Python](https://github.com/ronissonlucas/data_science/blob/main/Scraping/Scraping_stack_overflow.ipynb) 21 | [Dados - Scraping StackOverflow](https://github.com/ronissonlucas/data_science/blob/main/Scraping/python_stackoverflow.csv) 22 | 23 | 24 | ## Aulas Pandas 25 | [Pandas](https://github.com/ronissonlucas/data_science/blob/main/Aula_Pandas/Aula_Pandas1.ipynb) 26 | 27 | ## CRUD SQLite3 28 | [CRUD SQLite3 1 ](https://github.com/ronissonlucas/data_science/tree/main/CRUD_operations/CRUD_with_SQLite3) 29 | 30 | ## CRUD PostgreSQL 31 | -------------------------------------------------------------------------------- /Scraping/Scraping_stack_overflow.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "* Scraping de perguntas sobre Python no StackOverflow" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": 1, 13 | "metadata": {}, 14 | "outputs": [], 15 | "source": [ 16 | "import requests\n", 17 | "from bs4 import BeautifulSoup\n", 18 | "import pandas as pd" 19 | ] 20 | }, 21 | { 22 | "cell_type": "code", 23 | "execution_count": 2, 24 | "metadata": {}, 25 | "outputs": [], 26 | "source": [ 27 | "n = 155 #define a quantidade de páginas para fazer o scraping" 28 | ] 29 | }, 30 | { 31 | "cell_type": "code", 32 | "execution_count": 3, 33 | "metadata": {}, 34 | "outputs": [], 35 | "source": [ 36 | "dados = list() \n", 37 | "#laço para percorrer o total de páginas\n", 38 | "for i in range(1, n+1):\n", 39 | " \n", 40 | " #define a url e a requisição necessária\n", 41 | " url = 'https://pt.stackoverflow.com/questions/tagged/python?tab=newest&page='+str(i)+'&pagesize=50'\n", 42 | " req = requests.get(url)\n", 43 | " soup = BeautifulSoup(req.text, 'html.parser')\n", 44 | " \n", 45 | " #seleciona informações específicas para cada post\n", 46 | " for pergunta in soup.select('.question-summary'):\n", 47 | " titulo = pergunta.find('a').text\n", 48 | " data = pergunta.select_one('.relativetime').text\n", 49 | " visitas = pergunta.select_one('.views').text.split()[0] #pega apenas o número\n", 50 | " votos = pergunta.select_one('.vote-count-post').text\n", 51 | " \n", 52 | " info = {\n", 53 | " 'Título':titulo, \n", 54 | " 'Data':data, \n", 55 | " 'Visitas':visitas,\n", 56 | " 'Votos':votos}\n", 57 | " \n", 58 | " dados.append(info)\n", 59 | " " 60 | ] 61 | }, 62 | { 63 | "cell_type": "code", 64 | "execution_count": 4, 65 | "metadata": {}, 66 | "outputs": [], 67 | "source": [ 68 | "#cria o dataframa a partir dos dados coletados\n", 69 | "df = pd.DataFrame(dados, index = range(1, len(dados)+1))" 70 | ] 71 | }, 72 | { 73 | "cell_type": "code", 74 | "execution_count": 5, 75 | "metadata": {}, 76 | "outputs": [], 77 | "source": [ 78 | "#remove 'mil' da coluna Visitas e muda tipo de dado\n", 79 | "df['Visitas'] = df['Visitas'].apply(lambda n:float(n.replace('mil','000')))\n", 80 | "df['Votos'] = df['Votos'].astype(int)" 81 | ] 82 | }, 83 | { 84 | "cell_type": "code", 85 | "execution_count": 6, 86 | "metadata": {}, 87 | "outputs": [], 88 | "source": [ 89 | "#ordena o dataset pela coluna Visitas\n", 90 | "df = df.sort_values(by = 'Visitas', ascending = False)" 91 | ] 92 | }, 93 | { 94 | "cell_type": "code", 95 | "execution_count": 7, 96 | "metadata": {}, 97 | "outputs": [ 98 | { 99 | "data": { 100 | "text/html": [ 101 | "
\n", 102 | "\n", 115 | "\n", 116 | " \n", 117 | " \n", 118 | " \n", 119 | " \n", 120 | " \n", 121 | " \n", 122 | " \n", 123 | " \n", 124 | " \n", 125 | " \n", 126 | " \n", 127 | " \n", 128 | " \n", 129 | " \n", 130 | " \n", 131 | " \n", 132 | " \n", 133 | " \n", 134 | " \n", 135 | " \n", 136 | " \n", 137 | " \n", 138 | " \n", 139 | " \n", 140 | " \n", 141 | " \n", 142 | " \n", 143 | " \n", 144 | " \n", 145 | " \n", 146 | " \n", 147 | " \n", 148 | " \n", 149 | " \n", 150 | " \n", 151 | " \n", 152 | " \n", 153 | " \n", 154 | " \n", 155 | " \n", 156 | " \n", 157 | " \n", 158 | " \n", 159 | " \n", 160 | " \n", 161 | " \n", 162 | " \n", 163 | " \n", 164 | " \n", 165 | " \n", 166 | " \n", 167 | " \n", 168 | " \n", 169 | " \n", 170 | " \n", 171 | " \n", 172 | " \n", 173 | " \n", 174 | " \n", 175 | " \n", 176 | " \n", 177 | " \n", 178 | " \n", 179 | " \n", 180 | " \n", 181 | " \n", 182 | " \n", 183 | " \n", 184 | " \n", 185 | " \n", 186 | " \n", 187 | " \n", 188 | " \n", 189 | " \n", 190 | " \n", 191 | " \n", 192 | " \n", 193 | " \n", 194 | " \n", 195 | " \n", 196 | " \n", 197 | "
TítuloDataVisitasVotos
6584Como limitar números decimais em Python?9/01/17 às 18:51103000.018
7353Como gerar números aleatórios em Python?24/07/15 às 0:0294000.013
6273Como quebrar a linha?26/04/17 às 18:4468000.05
7537Como “arredondar” um float em Python?21/12/14 às 1:1567000.023
6232Vetores em Python6/05/17 às 2:2357000.07
6186Como criar uma matriz em python17/05/17 às 23:2256000.05
7317Como concatenar multiplas Strings em Python?26/08/15 às 18:3856000.010
7296Como converter uma variável string para int?17/09/15 às 20:5253000.010
7371Como limpar o console no Python?3/07/15 às 15:2451000.024
7405Encoding utf-8 permite acentos?5/06/15 às 1:0147000.010
\n", 198 | "
" 199 | ], 200 | "text/plain": [ 201 | " Título Data \\\n", 202 | "6584 Como limitar números decimais em Python? 9/01/17 às 18:51 \n", 203 | "7353 Como gerar números aleatórios em Python? 24/07/15 às 0:02 \n", 204 | "6273 Como quebrar a linha? 26/04/17 às 18:44 \n", 205 | "7537 Como “arredondar” um float em Python? 21/12/14 às 1:15 \n", 206 | "6232 Vetores em Python 6/05/17 às 2:23 \n", 207 | "6186 Como criar uma matriz em python 17/05/17 às 23:22 \n", 208 | "7317 Como concatenar multiplas Strings em Python? 26/08/15 às 18:38 \n", 209 | "7296 Como converter uma variável string para int? 17/09/15 às 20:52 \n", 210 | "7371 Como limpar o console no Python? 3/07/15 às 15:24 \n", 211 | "7405 Encoding utf-8 permite acentos? 5/06/15 às 1:01 \n", 212 | "\n", 213 | " Visitas Votos \n", 214 | "6584 103000.0 18 \n", 215 | "7353 94000.0 13 \n", 216 | "6273 68000.0 5 \n", 217 | "7537 67000.0 23 \n", 218 | "6232 57000.0 7 \n", 219 | "6186 56000.0 5 \n", 220 | "7317 56000.0 10 \n", 221 | "7296 53000.0 10 \n", 222 | "7371 51000.0 24 \n", 223 | "7405 47000.0 10 " 224 | ] 225 | }, 226 | "execution_count": 7, 227 | "metadata": {}, 228 | "output_type": "execute_result" 229 | } 230 | ], 231 | "source": [ 232 | "df.head(n = 10)" 233 | ] 234 | }, 235 | { 236 | "cell_type": "code", 237 | "execution_count": 8, 238 | "metadata": {}, 239 | "outputs": [ 240 | { 241 | "data": { 242 | "text/html": [ 243 | "
\n", 244 | "\n", 257 | "\n", 258 | " \n", 259 | " \n", 260 | " \n", 261 | " \n", 262 | " \n", 263 | " \n", 264 | " \n", 265 | " \n", 266 | " \n", 267 | " \n", 268 | " \n", 269 | " \n", 270 | " \n", 271 | " \n", 272 | " \n", 273 | " \n", 274 | " \n", 275 | " \n", 276 | " \n", 277 | " \n", 278 | " \n", 279 | " \n", 280 | " \n", 281 | " \n", 282 | " \n", 283 | " \n", 284 | " \n", 285 | " \n", 286 | " \n", 287 | " \n", 288 | " \n", 289 | " \n", 290 | " \n", 291 | " \n", 292 | " \n", 293 | " \n", 294 | " \n", 295 | " \n", 296 | " \n", 297 | " \n", 298 | " \n", 299 | " \n", 300 | " \n", 301 | " \n", 302 | " \n", 303 | " \n", 304 | " \n", 305 | " \n", 306 | " \n", 307 | " \n", 308 | " \n", 309 | " \n", 310 | " \n", 311 | " \n", 312 | " \n", 313 | " \n", 314 | " \n", 315 | " \n", 316 | " \n", 317 | " \n", 318 | " \n", 319 | " \n", 320 | " \n", 321 | " \n", 322 | " \n", 323 | " \n", 324 | " \n", 325 | " \n", 326 | " \n", 327 | " \n", 328 | " \n", 329 | " \n", 330 | " \n", 331 | " \n", 332 | " \n", 333 | " \n", 334 | " \n", 335 | " \n", 336 | " \n", 337 | " \n", 338 | " \n", 339 | "
TítuloDataVisitasVotos
66Exibindo PDF (criado em python) na WEB com nod...26/12/20 às 14:2810.01
88Como levar uma função que retorna valores do t...20/12/20 às 18:3810.0-1
998Atualização de caractere e retorno do charriot...26/06/20 às 10:5910.00
2811extends de templates a partir do projeto para ...29/05/19 às 11:469.00
61Erro de variavel com o OneHotEncoder27/12/20 às 15:379.00
81Erro durante deploy python em heroku22/12/20 às 1:129.0-2
978Definir um estado inicial usando a suite_gym d...29/06/20 às 22:108.00
15ERRO ao add na tableWidget2 dias atrás8.0-1
164meu display nao abre no pygame pelo vs code10/12/20 às 13:116.00
92Utilizando um modelo de GAN com pytorch no goo...20/12/20 às 2:275.0-1
\n", 340 | "
" 341 | ], 342 | "text/plain": [ 343 | " Título Data \\\n", 344 | "66 Exibindo PDF (criado em python) na WEB com nod... 26/12/20 às 14:28 \n", 345 | "88 Como levar uma função que retorna valores do t... 20/12/20 às 18:38 \n", 346 | "998 Atualização de caractere e retorno do charriot... 26/06/20 às 10:59 \n", 347 | "2811 extends de templates a partir do projeto para ... 29/05/19 às 11:46 \n", 348 | "61 Erro de variavel com o OneHotEncoder 27/12/20 às 15:37 \n", 349 | "81 Erro durante deploy python em heroku 22/12/20 às 1:12 \n", 350 | "978 Definir um estado inicial usando a suite_gym d... 29/06/20 às 22:10 \n", 351 | "15 ERRO ao add na tableWidget 2 dias atrás \n", 352 | "164 meu display nao abre no pygame pelo vs code 10/12/20 às 13:11 \n", 353 | "92 Utilizando um modelo de GAN com pytorch no goo... 20/12/20 às 2:27 \n", 354 | "\n", 355 | " Visitas Votos \n", 356 | "66 10.0 1 \n", 357 | "88 10.0 -1 \n", 358 | "998 10.0 0 \n", 359 | "2811 9.0 0 \n", 360 | "61 9.0 0 \n", 361 | "81 9.0 -2 \n", 362 | "978 8.0 0 \n", 363 | "15 8.0 -1 \n", 364 | "164 6.0 0 \n", 365 | "92 5.0 -1 " 366 | ] 367 | }, 368 | "execution_count": 8, 369 | "metadata": {}, 370 | "output_type": "execute_result" 371 | } 372 | ], 373 | "source": [ 374 | "df.tail(n = 10)" 375 | ] 376 | }, 377 | { 378 | "cell_type": "code", 379 | "execution_count": 9, 380 | "metadata": {}, 381 | "outputs": [], 382 | "source": [ 383 | "df.to_csv('python_stackoverflow.csv', index = False)" 384 | ] 385 | } 386 | ], 387 | "metadata": { 388 | "kernelspec": { 389 | "display_name": "Python 3", 390 | "language": "python", 391 | "name": "python3" 392 | }, 393 | "language_info": { 394 | "codemirror_mode": { 395 | "name": "ipython", 396 | "version": 3 397 | }, 398 | "file_extension": ".py", 399 | "mimetype": "text/x-python", 400 | "name": "python", 401 | "nbconvert_exporter": "python", 402 | "pygments_lexer": "ipython3", 403 | "version": "3.8.5" 404 | } 405 | }, 406 | "nbformat": 4, 407 | "nbformat_minor": 4 408 | } 409 | -------------------------------------------------------------------------------- /StudentsPerformance.csv: -------------------------------------------------------------------------------- 1 | "gender","race/ethnicity","parental level of education","lunch","test preparation course","math score","reading score","writing score" 2 | "female","group B","bachelor's degree","standard","none","72","72","74" 3 | "female","group C","some college","standard","completed","69","90","88" 4 | "female","group B","master's degree","standard","none","90","95","93" 5 | "male","group A","associate's degree","free/reduced","none","47","57","44" 6 | "male","group C","some college","standard","none","76","78","75" 7 | "female","group B","associate's degree","standard","none","71","83","78" 8 | "female","group B","some college","standard","completed","88","95","92" 9 | "male","group B","some college","free/reduced","none","40","43","39" 10 | "male","group D","high school","free/reduced","completed","64","64","67" 11 | "female","group B","high school","free/reduced","none","38","60","50" 12 | "male","group C","associate's degree","standard","none","58","54","52" 13 | "male","group D","associate's degree","standard","none","40","52","43" 14 | "female","group B","high school","standard","none","65","81","73" 15 | "male","group A","some college","standard","completed","78","72","70" 16 | "female","group A","master's degree","standard","none","50","53","58" 17 | "female","group C","some high school","standard","none","69","75","78" 18 | "male","group C","high school","standard","none","88","89","86" 19 | "female","group B","some high school","free/reduced","none","18","32","28" 20 | "male","group C","master's degree","free/reduced","completed","46","42","46" 21 | "female","group C","associate's degree","free/reduced","none","54","58","61" 22 | "male","group D","high school","standard","none","66","69","63" 23 | "female","group B","some college","free/reduced","completed","65","75","70" 24 | "male","group D","some college","standard","none","44","54","53" 25 | "female","group C","some high school","standard","none","69","73","73" 26 | "male","group D","bachelor's degree","free/reduced","completed","74","71","80" 27 | "male","group A","master's degree","free/reduced","none","73","74","72" 28 | "male","group B","some college","standard","none","69","54","55" 29 | "female","group C","bachelor's degree","standard","none","67","69","75" 30 | "male","group C","high school","standard","none","70","70","65" 31 | "female","group D","master's degree","standard","none","62","70","75" 32 | "female","group D","some college","standard","none","69","74","74" 33 | "female","group B","some college","standard","none","63","65","61" 34 | "female","group E","master's degree","free/reduced","none","56","72","65" 35 | "male","group D","some college","standard","none","40","42","38" 36 | "male","group E","some college","standard","none","97","87","82" 37 | "male","group E","associate's degree","standard","completed","81","81","79" 38 | "female","group D","associate's degree","standard","none","74","81","83" 39 | "female","group D","some high school","free/reduced","none","50","64","59" 40 | "female","group D","associate's degree","free/reduced","completed","75","90","88" 41 | "male","group B","associate's degree","free/reduced","none","57","56","57" 42 | "male","group C","associate's degree","free/reduced","none","55","61","54" 43 | "female","group C","associate's degree","standard","none","58","73","68" 44 | "female","group B","associate's degree","standard","none","53","58","65" 45 | "male","group B","some college","free/reduced","completed","59","65","66" 46 | "female","group E","associate's degree","free/reduced","none","50","56","54" 47 | "male","group B","associate's degree","standard","none","65","54","57" 48 | "female","group A","associate's degree","standard","completed","55","65","62" 49 | "female","group C","high school","standard","none","66","71","76" 50 | "female","group D","associate's degree","free/reduced","completed","57","74","76" 51 | "male","group C","high school","standard","completed","82","84","82" 52 | "male","group E","some college","standard","none","53","55","48" 53 | "male","group E","associate's degree","free/reduced","completed","77","69","68" 54 | "male","group C","some college","standard","none","53","44","42" 55 | "male","group D","high school","standard","none","88","78","75" 56 | "female","group C","some high school","free/reduced","completed","71","84","87" 57 | "female","group C","high school","free/reduced","none","33","41","43" 58 | "female","group E","associate's degree","standard","completed","82","85","86" 59 | "male","group D","associate's degree","standard","none","52","55","49" 60 | "male","group D","some college","standard","completed","58","59","58" 61 | "female","group C","some high school","free/reduced","none","0","17","10" 62 | "male","group E","bachelor's degree","free/reduced","completed","79","74","72" 63 | "male","group A","some high school","free/reduced","none","39","39","34" 64 | "male","group A","associate's degree","free/reduced","none","62","61","55" 65 | "female","group C","associate's degree","standard","none","69","80","71" 66 | "female","group D","some high school","standard","none","59","58","59" 67 | "male","group B","some high school","standard","none","67","64","61" 68 | "male","group D","some high school","free/reduced","none","45","37","37" 69 | "female","group C","some college","standard","none","60","72","74" 70 | "male","group B","associate's degree","free/reduced","none","61","58","56" 71 | "female","group C","associate's degree","standard","none","39","64","57" 72 | "female","group D","some college","free/reduced","completed","58","63","73" 73 | "male","group D","some college","standard","completed","63","55","63" 74 | "female","group A","associate's degree","free/reduced","none","41","51","48" 75 | "male","group C","some high school","free/reduced","none","61","57","56" 76 | "male","group C","some high school","standard","none","49","49","41" 77 | "male","group B","associate's degree","free/reduced","none","44","41","38" 78 | "male","group E","some high school","standard","none","30","26","22" 79 | "male","group A","bachelor's degree","standard","completed","80","78","81" 80 | "female","group D","some high school","standard","completed","61","74","72" 81 | "female","group E","master's degree","standard","none","62","68","68" 82 | "female","group B","associate's degree","standard","none","47","49","50" 83 | "male","group B","high school","free/reduced","none","49","45","45" 84 | "male","group A","some college","free/reduced","completed","50","47","54" 85 | "male","group E","associate's degree","standard","none","72","64","63" 86 | "male","group D","high school","free/reduced","none","42","39","34" 87 | "female","group C","some college","standard","none","73","80","82" 88 | "female","group C","some college","free/reduced","none","76","83","88" 89 | "female","group D","associate's degree","standard","none","71","71","74" 90 | "female","group A","some college","standard","none","58","70","67" 91 | "female","group D","some high school","standard","none","73","86","82" 92 | "female","group C","bachelor's degree","standard","none","65","72","74" 93 | "male","group C","high school","free/reduced","none","27","34","36" 94 | "male","group C","high school","standard","none","71","79","71" 95 | "male","group C","associate's degree","free/reduced","completed","43","45","50" 96 | "female","group B","some college","standard","none","79","86","92" 97 | "male","group C","associate's degree","free/reduced","completed","78","81","82" 98 | "male","group B","some high school","standard","completed","65","66","62" 99 | "female","group E","some college","standard","completed","63","72","70" 100 | "female","group D","some college","free/reduced","none","58","67","62" 101 | "female","group D","bachelor's degree","standard","none","65","67","62" 102 | "male","group B","some college","standard","none","79","67","67" 103 | "male","group D","bachelor's degree","standard","completed","68","74","74" 104 | "female","group D","associate's degree","standard","none","85","91","89" 105 | "male","group B","high school","standard","completed","60","44","47" 106 | "male","group C","some college","standard","completed","98","86","90" 107 | "female","group C","some college","standard","none","58","67","72" 108 | "female","group D","master's degree","standard","none","87","100","100" 109 | "male","group E","associate's degree","standard","completed","66","63","64" 110 | "female","group B","associate's degree","free/reduced","none","52","76","70" 111 | "female","group B","some high school","standard","none","70","64","72" 112 | "female","group D","associate's 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