在pandas中怎么样实现类似mysql查找语句的功能: select * from table where column_name = some_value; pandas中获取数据的有以下几种方法: 布尔索引 位置索引 标签索引 使用API 假设数据如下: import pandas as pd import numpy as np df = pd.DataFrame({'A': 'foo bar foo bar foo bar foo foo'.split(), 'B': 'one one
# coding:utf-8 import os, re for i in os.walk('d:'+os.sep): for txt in i[2]: try: txt = re.match(r'(.*)(\.txt)', txt).group(0) print os.path.join(i[0], txt) except: pass
堆排序做的,没有全部排序,找到第k个就结束 public int findKthLargest(int[] nums, int k) { int num = 0; if (nums.length <= 1) return nums[0]; int heapSize = nums.length; //1.构建最大堆 int half = (heapSize-2)/2; for (int i = half;i >= 0;i--) { adjust(nums,heapSize,i); } while