새싹 AI데이터엔지니어 핀테커스 4주차 (월) - Math in Python

2023-09-18 16th Class

Matplotlib Basic

• ax, subplots & labels

def base_mat():  
    # matplotlib 기본 사용법  
    fig = plt.figure()  
    fig = plt.figure(figsize=(7, 7))  
    fig = plt.figure(figsize=(7, 7), facecolor='linen')  
    ax = fig.add_subplot()  
    ax.plot([2, 3, 1])  
    ax.scatter([2, 3, 1], [2, 3, 4])  

    # 폰트  
    figsize = (7, 7)  
    fig, ax = plt.subplots(figsize=figsize)  
    # fig 제목  
    fig.suptitle("Title of a Figure", fontsize=30, fontfamily='monospace')  

    # ax 제목  
    ax.set_title("Title of a ax", fontsize=30, fontfamily='monospace')  

    # 라벨 이름  
    ax.set_xlabel("X label", fontsize=20)  
    ax.set_ylabel("Y label", fontsize=20)  

    fig.suptitle("Title of a Figure", fontsize=30, color='darkblue', alpha=0.9)  
    ax.set_xlabel("X label", fontsize=20, color='darkblue', alpha=0.7)  
    ax.set_ylabel("Y label", fontsize=20, color='darkblue', alpha=0.7)  

    fig.tight_layout()

 

 

• twinx

def my_twinx():  
    # twinx: 한 그래프 공간에 2개 만들기  
    fig = plt.figure(figsize=(10, 10))  
    ax1 = fig.add_subplot()  
    ax2 = ax1.twinx()  

    ax1.set_xlim([0, 100])  
    ax1.set_ylim([0, 100])  
    ax2.set_ylim([0, 0.1])  

    ax1.set_title("Twinx Graph", fontsize=30)  
    ax1.set_ylabel("Data1", fontsize=20)  
    ax2.set_ylabel("Data2", fontsize=20)  

    # ax1.tick_params(labelsize=20, length=10, width=3, bottom=False,  
    #                 labelbottom=False, top=True, labeltop=True,    #                 right=True, labelright=True)  
    # ax1.tick_params(axis='x', labelsize=20, length=10, width=3, rotation=30)    ax1.tick_params(axis='y', labelsize=20, length=10, width=3, rotation=50)  

    fig.tight_layout()

 

 

• text

def txt_alignment():  
    figsize = (7, 7)  
    fig, ax = plt.subplots(figsize=figsize)  

    ax.set_xlim([-1, 1])  
    ax.set_ylim([-1, 1])  

    ax.grid()  
    # labelsize 라벨 폰트  
    ax.tick_params(axis='both', labelsize=15)  
    # ax.text(x=0, y=0, s='hello', fontsize=30)  
    # ax.text(x=0.5, y=0, s='hello2', fontsize=30)    # ax.text(x=0.5, y=-0.5, s='hello3', fontsize=30)  
    ax.text(x=0, y=0, va='center', ha='left', s='hello', fontsize=30)  
    # ax.text(x=0, y=0, va='center', ha='center', s='hello2', fontsize=30)  
    # ax.text(x=0, y=0, va='center', ha='right', s='hello3', fontsize=30)  

def align_test():  
    figsize = (7, 7)  
    fig, ax = plt.subplots(figsize=figsize)  

    ax.set_xlim([-1, 1])  
    ax.set_ylim([-1, 1])  

    ax.grid()  
    # 'top', 'bottom', 'center', 'baseline', 'center_baseline'  
    # 'center', 'right', 'left'    # ax.text(x=0, y=0, va='bottom', ha='right', s='Hello', fontsize=30)    ax.text(x=0, y=0, va='top', ha='left', s='Hello', fontsize=30)

• ticks

def tick_mt():  
    # figsize = (7, 7)  
    figsize = (14, 7)  
    fig, ax = plt.subplots(figsize=figsize)  

    # ax.set_xlim([0, 10])  
    # ax.set_ylim([0, 10])    #    # ax.set_xlim([0, 10])    # ax.set_xticks([0, 1, 5, 10])  
    # set xticks (Major and minor ticks)    major_xticks = [i for i in range(0, 101, 20)]  
    minor_xticks = [i for i in range(0, 101, 5)]  

    ax.set_xticks(major_xticks)  
    ax.set_xticks(minor_xticks, minor=True)  

    ax.tick_params(axis='x', labelsize=20, length=10, width=3, rotation=30)  
    ax.tick_params(axis='x', which='minor', length=5, width=2)  


def tick_test():  
    figsize = (14, 7)  
    fig, ax = plt.subplots(figsize=figsize)  
    major_xticks = [i for i in range(0, 101, 20)]  
    minor_xticks = [i for i in range(0, 101, 5)]  

    major_yticks = [i for i in range(0, 11, 2)]  
    minor_yticks = [i for i in range(0, 11)]  

    ax.set_xticks(major_xticks)  
    ax.set_xticks(minor_xticks, minor=True)  

    ax.set_yticks(major_yticks)  
    ax.set_yticks(minor_yticks, minor=True)  

    ax.tick_params(axis='x', labelsize=20, length=10, width=3, rotation=30)  
    ax.tick_params(axis='x', which='minor', length=5, width=2)  

    ax.tick_params(axis='y', labelsize=20, length=10, width=3)  
    ax.tick_params(axis='y', which='minor', length=5, width=2)  

    ax.tick_params()

 

• colormat

def named_colors():  
    color_list = ['b', 'g', 'r', 'c', 'm', 'y']  

    fig, ax = plt.subplots(figsize=(5, 10))  
    ax.set_xlim([-1, 1])  
    ax.set_ylim([-1, len(color_list)])  

    for c_idx, c in enumerate(color_list):  
        # 3번째는 텍스트임  
        ax.text(0, c_idx, "color="+c, fontsize=20, ha='center', color=c)  


def named_colors2():  
    # 252, 186, 3  
    color_list = [(1., 0., 0.),  
                  (0., 1., 0.),  
                  (0., 0., 1.)]  

    fig, ax = plt.subplots(figsize=(5, 10))  
    ax.set_xlim([-1, 1])  
    ax.set_ylim([-1, len(color_list)])  

    for c_idx, c in enumerate(color_list):  
        ax.text(0, c_idx, f"color={c}", fontsize=20, ha='center', color=c)

 

• scattor plot with random value

def my_scatter():  
    np.random.seed(0)  

    n_data = 100  
    # 정규분포로 랜덤값 뽑기  
    x_data = np.random.normal(0, 1, (n_data,))  
    y_data = np.random.normal(0, 1, (n_data,))  

    fig, ax = plt.subplots(figsize=(7, 7))  
    # s는 점의 크기(marker size)  
    # ax.scatter(x_data, y_data, s=300, color='r')    
    ##########################    
    # ax.plot(x_data, y_data, 'o', color='red', markersize=10)  
    # uniform linspace    
    # x_min, x_max = -5, 5    
    # n_data = 300    
    #    
    # x_data = np.random.uniform(x_min, x_max, n_data)   
    # y_data = x_data + 0.5*np.random.normal(0, 1, n_data)    
    #    
    # pred_x = np.linspace(x_min, x_max, 2)    
    # pred_y = pred_x    
    #    
    # fix, ax = plt.subplots(figsize=(10, 10))    
    # ax.scatter(x_data, y_data)    
    #    
    # ax.plot(pred_x, pred_y, color='r', linewidth=3)  
    # size array and color array    
    # n_data = 10    
    # 
    # 양 옆이 정해져있고 일정하게 n_data만큼 추출  
    # x_data = np.linspace(0, 10, n_data)  
    # y_data = np.linspace(0, 10, n_data)    
    #    
    # s_arr = np.linspace(10, 500, n_data)    
    #    
    # fig, ax = plt.subplots(figsize=(10, 10))    
    # 
    # s는 size라서 점점 커짐  
    # ax.scatter(x_data, y_data, s=s_arr)  

    # color array    
    # n_data = 10    
    # 
    # linspace 균일한 간격으로 추출  
    # x_data = np.linspace(0, 10, n_data)  
    # y_data = np.linspace(0, 10, n_data)    
    #    
    # c_arr = [(c/n_data, c/n_data, c/n_data) for c in range(n_data)]    
    #    
    # fig, ax = plt.subplots(figsize=(10, 10))    # # s= 점 사이즈, c= 점 컬러  
    # ax.scatter(x_data, y_data, s=500, c=c_arr)  

    # size array and color array    n_data = 500  
    x_data = np.random.normal(0, 1, size=(n_data, ))  
    y_data = np.random.normal(0, 1, size=(n_data, ))  
    s_arr = np.random.uniform(100, 500, n_data)  
    c_arr = [np.random.uniform(0, 1, 3) for _ in range(n_data)]  

    fig, ax = plt.subplots(figsize=(10, 10))  
    # ax.scatter(x_data, y_data, s=s_arr, c=c_arr)  

    ax.scatter(x_data, y_data, s=s_arr, c=c_arr, alpha=0.3)

 

 

 

Python (Mathmatical Algorithms Basic)

• 평균

def e109():  
    # mean  
    score1 = 10  
    score2 = 20  
    score3 = 30  
    n_student = 3  
    mean = (score1 + score2 + score3) / n_student  
    print(mean)  

    score1 += 10  
    score2 += 10  
    score3 += 10  
    print(score1, score2, score3)  
    mean = (score1 + score2 + score3) / n_student  
    print(mean)

20.0
20 30 40
30.0

• Mean subtraction

def e110():  
    # Mean Subtraction  
    # 평균 값을 구하고, 그 평균을 각 값에서 뺀 다음에 평균을 구하면 0이됨  
    score1 = 10  
    score2 = 20  
    score3 = 30  
    n_student = 3  

    score_mean = (score1 + score2 + score3) / n_student  

    score1 -= score_mean  
    score2 -= score_mean  
    score3 -= score_mean  

    score_mean = (score1 + score2 + score3) / n_student  
    print(score_mean)

0.0

• 분산

def e111():  
    # 분산  
    score1 = 10  
    score2 = 20  
    score3 = 30  
    n_student = 3  

    mean = (score1 + score2 + score3) / n_student  
    square_of_mean = mean**2  

    # 분산 = 편차 제곱의 평균  
    mean_of_square = (score1**2 + score2**2 + score3**2) / n_student  
    print("square of mean: ", square_of_mean)  
    print("mean of square: ", mean_of_square)

square of mean:  400.0
mean of square:  466.6666666666667

• standard deviation

def e112():  
    # standard deviation  
    score1 = 10  
    score2 = 20  
    score3 = 30  
    n_student = 3  

    score_mean = (score1 + score2 + score3) / n_student  
    square_of_mean = score_mean**2  
    # 제곱 평균  
    mean_of_square = (score1**2 + score2**2 + score3**2) / n_student  
    # 분산 = 제곱 평균 - 평균 제곱  
    score_variance = mean_of_square - square_of_mean  
    score_std = score_variance ** 0.5  

    # ** 0.5 루트  
    print("mean: ", score_mean)  
    print("variance: ", score_variance)  
    print("standard deviation: ", score_std)

mean:  20.0
variance:  66.66666666666669
standard deviation:  8.16496580927726

💛 배운점/느낀점

• matplotlib ax 객체 사용 방법 익힘
• 수식을 코드로 구현하는 방법을 익힘
• 내일은 파이썬으로 ML 관련 수식 코드 작성 학습 계속