Question

我一直在尝试使用嵌套循环遍历pandas DataFrame的行，外部循环，并且每行检查规则的条件，元组列表：[（Attribute，Value），（Att，Val）]，匹配DataFrame行中的Att，Val对，内部循环。如果规则中的所有条件都满足，我希望记录行的索引，如果一个或多个条件失败，我希望突破内循环而不记录行索引并继续到下一行。

我已经尝试将break语句放在内部循环，外部循环等中，但我无法按照自己的意愿使用它。非常感谢任何帮助我的尝试。

def rule_coverage(self, rule):

    for index,row in self.data.iterrows():  

        for selector in rule:

            if row[selector[0]]  != selector[1]:
                break

        coverage.append(index)

 return self.data.iloc[coverage]

Answer 1

我做这样的事情：

让img = cv2.imread('imgs/bulls.jpg') hsv_img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) court_color = np.uint8([[[160,221,248]]]) hsv_court_color = cv2.cvtColor(court_color, cv2.COLOR_BGR2HSV) hue = hsv_court_color[0][0][0] # define range of blue color in HSV lower_color = np.array([hue - 10,10,10]) upper_color = np.array([hue + 10,255,255]) # Threshold the HSV image to get only blue colors mask = cv2.inRange(hsv_img, lower_color, upper_color) # Bitwise-AND mask and original image res = cv2.bitwise_and(img,img, mask= mask) plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)), plt.title('Original Image'), plt.show() plt.imshow(mask, cmap='Greys'), plt.title('Mask'), plt.savefig('imgs/mask.jpg'), plt.show() # Erosion kernel = np.ones((2,2),np.uint8) erosions2 = cv2.erode(mask,kernel,iterations = 5) # Dilation dilation = cv2.dilate(mask,kernel,iterations = 3) # Opening opening = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel) # Closing closing = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)成为代表s

的pandas.Series

rule

重新分配数据框以与s = pd.Series(dict(rule))

对齐

然后比较并返回整行的真实位置

d, s = self.data.align(s, 'inner', 1)

Answer 2

同志们，我设法通过遵循许多其他帖子的建议来解决问题，这些帖子建议将内部循环重构为将所需结果返回到外部循环的函数。感谢您给出的所有建议。解决方案如下，上部函数是前内部循环，而下部函数是现在简化的外部循环。

def check_rule_datapoint(self, datapoint, complex):
    """
    Function to check if a given data point satisfies
    the conditions of a given complex. Data point 
    should be a pandas Series. Complex should be a
    tuple or a list of tuples where each tuple is of
    the form ('Attribute', 'Value').
    """
    if type(complex) == tuple:
        if datapoint[complex[0]] == complex[1]:
            return True
        else:
            return False

    if type(complex) == list:
        result = True   
        for selector in complex:
            if datapoint[selector[0]] != selector[1]:
                result = False

        return result       

def complex_coverage(self, complex):
    """ Returns set of instances of the data 
        which complex(rule) covers.
    """

    #import ipdb;ipdb.set_trace(context=8)
    coverage = []

    #iterate over dataframe rows
    for index,row in self.data.iterrows():
        if self.check_rule_datapoint(row, complex):
            coverage.append(index)

    return self.data.iloc[coverage]

Python嵌套循环，如果条件不满足则中断

2 个答案: