Table of Contents
Summary of common ideas for arrays:
Common functions for lists
多维列表的一个坑
第5天
217. 存在重复元素
53. 最大子数组和
1. 两数之和
暴力枚举可以
哈希表
88. 合并两个有序数组
双指针
(暴力) 追加后排序
350. 两个数组的交集 II
121. 买卖股票的最佳时机
566. 重塑矩阵
118. 杨辉三角
36. 有效的数独
73. 矩阵置零
Home Backend Development Python Tutorial How to solve pitfalls in Python multidimensional lists

How to solve pitfalls in Python multidimensional lists

May 14, 2023 pm 12:01 PM
python

Summary of common ideas for arrays:

(The default nums below is an array.) 1. Traverse the array Traversal:

for num in nums:
	xxxx
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Traversal with index

for idx,num in enumerate(nums):
	xxxx
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2. Dynamic programming (dp) Dynamic programming generally uses an array to save state. See 53. Maximum subarray and . Using arrays to save state is a very common practice. For example 36. Valid Sudoku, 73. Set matrix to zero.

3.Double pointer See 88. Merge two ordered arrays, 350. Intersection of two arrays II can be used for one array with left and right pointers. It can also be two pointers traversing two arrays. while index1<m and index2<n:

Common functions for lists

In Python, list is generally used to implement variable arrays. The following is listcommonly used functions. (Common operations for variable sequence types, only .sort is unique to list. Refer to the sequence operation documentation)

iterable are true (or the iterable is empty) Returns

多维列表的一个坑

创建多维列表,一般用

w, h = 2, 3
A = [[None] * w for i in range(h)]
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等价于

A = [None] * 3
for i in range(3):
    A[i] = [None] * 2
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而不是

 A = [[None] * 2] * 3
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原因在于用*对列表执行重复操作并不会创建副本,而只是创建现有对象的引用*3创建的是包含 3 个引用的列表,每个引用指向的是同一个长度为 2 的列表。 如果你给一项赋值,就会发现这个问题:

>>> A[0][0] = 5
>>> A
[[5, None], [5, None], [5, None]]<h2 id="第-天">第1天</h2>
<h3 id="存在重复元素">217. 存在重复元素</h3>
<p>给定数组,判断是否存在重复元素。
做法:</p>
<ol class=" list-paddingleft-2">
<li><p>直接遍历(穷举)</p></li>
<li><p>排序后,比较每个元素和下一个元素</p></li>
<li><p>哈希表</p></li>
</ol>
<p>直接遍历会超时。
2的时间复杂度是O(nlogn) 也就是排序的时间复杂度
3的时间复杂度是O(n),但需要额外的O(n)辅助空间。
(穷举法基本都能想到,但很容易超时,后面只有在穷举法能通过时才列出来。)</p>
<p>3比较简单,这里写一下3的做法:</p>
<pre class="brush:php;toolbar:false">return len(nums) != len(set(nums))
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53. 最大子数组和

给定数组,求其中一个连续数组和的最大值。

比较容易想到的是用一个数组记录目前位置最大的值(动态规划)。

dp[i] 表示以i位置结尾的连续数组和的最大值。 最后返回dp数组中最大值。

class Solution:
    def maxSubArray(self, nums: List[int]) -> int:
        length = len(nums)
        dp = [0 for i in range(length)]
        for i in range(length):
            dp[i] = max(dp[i - 1], 0) + nums[i]
        return max(dp)
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题解给出了一种省略dp数组的方法:

class Solution:
    def maxSubArray(self, nums: List[int]) -> int:
        pre = 0
        res = nums[0]
        for x in nums:
            pre = max(pre+x ,x)
            res = max(res, pre)
        return res
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第2天

1. 两数之和

找出数组中两个数之和等于target的两数下标。

暴力枚举可以

但时间较长,时间复杂度$O(N^2)$

class Solution:
    def twoSum(self, nums: List[int], target: int) -> List[int]:
        n = len(nums)
        for i in range(n):
            for j in range(i + 1, n):
                if nums[i] + nums[j] == target:
                    return [i, j]
        
        return []
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哈希表

官方题解的一个比较巧妙的方式:使用哈希表(字典) 用字典记录出现过的数字的位置。 时间复杂度$O(N)$,空间复杂度$O(N)$

class Solution:
    def twoSum(self, nums: List[int], target: int) -> List[int]:
        hashtable = dict()
        for i, num in enumerate(nums):
            if target - num in hashtable:
                return [hashtable[target - num], i]
            hashtable[nums[i]] = i
        return []
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88. 合并两个有序数组

两个有序数组,将第二个数组nums2合并到第一个数组nums1

双指针

1.可以用双指针遍历两个数组:

class Solution:
    def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
        """
        Do not return anything, modify nums1 in-place instead.
        """
        # 两个中存在空数组的时,直接返回
        if m == 0:
            nums1[:] = nums2[:]
            return
        if n == 0:
            return

        index1,index2 = 0,0
        t = []
        while index1<m and index2<n:
            if nums1[index1] <= nums2[index2]:
                t.append(nums1[index1])
                index1 += 1
            else:
                t.append(nums2[index2])
                index2 += 1 
        
        if index1 < m:
            t += nums1[index1:m]
        else:
            t += nums2[index2:n]

        nums1[:] = t[:]
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官方版本,更简洁、清楚。

class Solution:
    def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
        """
        Do not return anything, modify nums1 in-place instead.
        """
        sorted = []
        p1, p2 = 0, 0
        while p1 < m or p2 < n:
            if p1 == m:
                sorted.append(nums2[p2])
                p2 += 1
            elif p2 == n:
                sorted.append(nums1[p1])
                p1 += 1
            elif nums1[p1] < nums2[p2]:
                sorted.append(nums1[p1])
                p1 += 1
            else:
                sorted.append(nums2[p2])
                p2 += 1
        nums1[:] = sorted
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(暴力) 追加后排序

  1. 更简单粗暴的方式是直接将nums2追加到nums1后,进行排序。 及其简单而且效果很好。

class Solution:
    def merge(self, nums1: List[int], m: int, nums2: List[int], n: int) -> None:
        """
        Do not return anything, modify nums1 in-place instead.
        """
        nums1[m:] = nums2
        nums1.sort()
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第3天

350. 两个数组的交集 II

以数组形式返回两数组的交集(数组形式,返回结果中每个元素出现的次数,应与元素在两个数组中都出现的次数一致)。 排序后双指针遍历。

class Solution:
    def intersect(self, nums1: List[int], nums2: List[int]) -> List[int]:
        nums1.sort()
        nums2.sort()
        i = 0
        j = 0
        result = []
        while i<len(nums1) and j<len(nums2):
            if(nums1[i]<nums2[j]):
                i+=1
            elif(nums1[i]>nums2[j]):
                j+=1
            else:
                result.append(nums1[i])
                i+=1
                j+=1
       
        return  result
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121. 买卖股票的最佳时机

只需要记录下当前最低价,遍历价格过程中,用当前价格-最低价 就是当前可获得的最大利润。另外如果出现了更低的价格,则最低价也要更新。(一个朴素的想法,要是我在最低点买进就好了) 总的最大利润就是这些利润中的最大值。

class Solution:
    def maxProfit(self, prices: List[int]) -> int:
        r = 0
        min_price = float('inf')  # float('inf')表示正无穷
        for price in prices:
            min_price = min(min_price, price)  # 截止到当前的最低价(买入价)
            r = max(r, price - min_price)  # 截止到目前的最高利润
        return r
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第4天

566. 重塑矩阵

给定一个mxn的数组,重构为rxc的数组。 比较简单的想法是把数组拉平为一位数组,然后逐个填充到新的数组中:

class Solution:
    def matrixReshape(self, mat: List[List[int]], r: int, c: int) -> List[List[int]]:
        m,n = len(mat), len(mat[0])
        if m*n != r*c:
            return mat
        arr = []
        for row in mat:
            for x in row:
                arr.append(x)
        arr_index = 0
        newmat = [[0 for j in range(c)]for i in range(r)]
        for i in range(r):
            for j in range(c):
                newmat[i][j] = arr[arr_index]
                arr_index += 1
        return newmat
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官方提供了一种直接计算下标的方法:

class Solution:
    def matrixReshape(self, nums: List[List[int]], r: int, c: int) -> List[List[int]]:
        m, n = len(nums), len(nums[0])
        if m * n != r * c:
            return nums
        
        ans = [[0] * c for _ in range(r)]
        for x in range(m * n):
            ans[x // c][x % c] = nums[x // n][x % n]
        
        return ans
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118. 杨辉三角

找规律题。可以直接按照生成的规律生成数组。在「杨辉三角」中,每个数是它左上方和右上方的数的和。

class Solution:
    def generate(self, numRows: int) -> List[List[int]]:
        res = [[]for _ in range(numRows)]
        res[0] = [1]
        for i in range(1,numRows):
            res[i].append(1)
            for j in range(0,len(res[i-1])-1):
                res[i].append(res[i-1][j] + res[i-1][j+1])
            res[i].append(1)

        return res
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第5天

36. 有效的数独

判断当前数独是否有效(不需要填充数独) 只要用3个二维数组维护9行、9列、9个九宫格。

class Solution:
    def isValidSudoku(self, board: List[List[str]]) -> bool:
        row = [[] * 9 for _ in range(9)]
        col = [[] * 9 for _ in range(9)]
        nine = [[] * 9 for _ in range(9)]
        for i in range(len(board)):
            for j in range(len(board[0])):
                tmp = board[i][j]
                if not tmp.isdigit():
                    continue
                if (tmp in row[i]) or (tmp in col[j]) or (tmp in nine[(j // 3) * 3 + (i // 3)]):
                    return False
                row[i].append(tmp)
                col[j].append(tmp)
                nine[(j // 3) * 3 + (i // 3)].append(tmp)
        return True
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73. 矩阵置零

如果一个元素为 0 ,则将其所在行和列的所有元素都设为 0 。请使用 原地 算法。 A: 利用数组的首行和首列来记录 0 值 另外用两个布尔值记录首行首列是否需要置0

class Solution:
    def setZeroes(self, matrix: List[List[int]]) -> None:
        """
        Do not return anything, modify matrix in-place instead.
        """
        #标记
        m,n = len(matrix), len(matrix[0])
        row = any(x == 0 for x in matrix[0])
        col = any(matrix[r][0] == 0 for r in range(m) )
        
        for i in range(m):
            for j in range(n):
                if matrix[i][j] == 0:
                    matrix[i][0] = 0
                    matrix[0][j] = 0
                    
        #置零
        for i in range(1,m):
            for j in range(1,n):
                if matrix[i][0] == 0 or matrix[0][j] == 0:
                    matrix[i][j] = 0
        if row:
            for j in range(0,n):
                matrix[0][j] = 0
        if col:
            for i in range(0,m):
                matrix[i][0] = 0
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See all articles
function Function
nums.sort(key,reversed)(original)Follow The key is sorted in ascending order, reversed can specify whether to reverse.
sorted(nums,key,reversed)Usage is similar to nums.sort, but returns another array , the original array remains unchanged.
s.append(x)Append x to the end of the sequence
s.extend(t) or s = textend s
x in with the content of t s Determine whether x is in the array nums.
len(s)Return s length
max(s), min(s)Return sMaximum value, minimum value
all( iterable)Returns True# if all elements of
##any(iterable)True if any element of iterable is true. If the iterable is empty, returns False.