col

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I am trying to scrape a simple table using Beautiful Soup. Here is my code: import requests from bs4 import BeautifulSoup url = 'https://gist.githubusercontent.com/anonymous/c8eedd8bf41098a8940b/raw/c7e01a76d753f6e8700b54821e26ee5dde3199ab/gistfile1.txt' r = requests.get(url) soup = BeautifulSoup(r.text) table = soup.find_all(class_='dataframe') first_name = [] last_name = [] age = [] preTestScore = [] postTestScore = [] for row in table.find_all('tr'): col = table.find_all('td') column_1 = col[0].string.strip() first_name.append(column_1)

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I'm getting result from API as follows: [ { "id": 1, "area": "", "zone": "T", "aisle": "", "side": "E", "col": 1, "level": 0, "position": 0, "name": "T - E - 1" }, { "id": 2, "area": "", "zone": "T", "aisle": "", "side": "E", "col": 60, "level": 0, "position": 0, "name": "T - E - 60" }, .... , { "id": 3370, "area": "", "zone": "T", "aisle": "", "side": "E", "col": 60, "level": 0, "position": 0, "name": "T - E - 60" } ] The result has 3370 records. I want to save it to AsyncStorage, thus I need to stringify it. But the problem is that I get

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由 翻译 强力驱动 问题: I'm drawing a bunch of lines with the Python Imaging Library's ImageDraw.line(), but they look horrid since I can't find a way to anti-alias them. How can I anti-alias lines in PIL? If PIL can't do it, is there another Python image manipulation library that can? 回答1: aggdraw provides nicer drawing than PIL. 回答2: This is a really quickly hacked together function to draw an anti-aliased line with PIL that I wrote after googling for the same issue, seeing this post and failing to install aggdraw and being on a tight deadline. It's an

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由 翻译 强力驱动 问题: I have the following dataframe showing the revenue of purchases. +-------+--------+-------+ | user_id | visit_id | revenue | +-------+--------+-------+ | 1 | 1 | 0 | | 1 | 2 | 0 | | 1 | 3 | 0 | | 1 | 4 | 100 | | 1 | 5 | 0 | | 1 | 6 | 0 | | 1 | 7 | 200 | | 1 | 8 | 0 | | 1 | 9 | 10 | +-------+--------+-------+ Ultimately I want the new column purch_revenue to show the revenue generated by the purchase in every row. As a workaround, I have also tried to introduce a purchase identifier purch_id which is incremented each time a purchase

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I am trying to scrape a simple table using Beautiful Soup. Here is my code: import requests from bs4 import BeautifulSoup url = 'https://gist.githubusercontent.com/anonymous/c8eedd8bf41098a8940b/raw/c7e01a76d753f6e8700b54821e26ee5dde3199ab/gistfile1.txt' r = requests.get(url) soup = BeautifulSoup(r.text) table = soup.find_all(class_='dataframe') first_name = [] last_name = [] age = [] preTestScore = [] postTestScore = [] for row in table.find_all('tr'): col = table.find_all('td') column_1 = col[0].string.strip() first_name.append(column_1)

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: This is the code for providing the COLUMN name when the row and col ID is provided but when I give values like row = 1 and col = 104 , it should return CZ , but it returns D@ row = 1 col = 104 div = col column_label = str() while div: (div, mod) = divmod(div, 26) column_label = chr(mod + 64) + column_label print column_label What is wrong with what I am doing? (This code is in reference for EXCEL Columns, where I provide the Row,Column ID value and expect the ALPHABETIC value for the same.) 回答1: EDIT: I feel I must admit, as pointed out by a

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I have a dataframe and I want to apply a function to each row. This function depends of other dataframes. Simplified example. I have three dataframes like below: df = sc.parallelize([ ['a', 'b', 1], ['c', 'd', 3] ]).toDF(('feat1', 'feat2', 'value')) df_other_1 = sc.parallelize([ ['a', 0, 1, 0.0], ['a', 1, 3, 0.1], ['a', 3, 10, 1.0], ['c', 0, 10, 0.2], ['c', 10, 25, 0.5] ]).toDF(('feat1', 'lower', 'upper', 'score')) df_other_2 = sc.parallelize([ ['b', 0, 4, 0.1], ['b', 4, 20, 0.5], ['b', 20, 30, 1.0], ['d', 0, 5, 0.05], ['d', 5, 22, 0.9] ])

查询 SQL SERVER 中某张表结构，sql 语句如下： SELECT tb.name AS tableName, col.name AS columnName, col.max_length AS length, col.is_nullable AS isNullable, t.name AS type, ( SELECT TOP 1 ind.is_primary_key FROM sys.index_columns ic LEFT JOIN sys.indexes ind ON ic.object_id = ind.object_id AND ic.index_id= ind.index_id AND ind.name LIKE ‘PK_%‘ WHERE ic.object_id = tb.object_id AND ic.column_id= col.column_id ) AS isPrimaryKey, com.value AS comment FROM sys.TABLES tb INNER JOIN sys.columns col ON col.object_id = tb.object_id LEFT JOIN sys.types t ON t.user_type_id = col.user_type_id LEFT JOIN sys.extended

A-链接： https://www.nowcoder.com/acm/contest/133/A 来源：牛客网 题目描述 现在有一棵被Samsara-Karma染了k种颜色的树，每种颜色有着不同的价值 Applese觉得Samsara-Karma染的太难看了，于是打算把整棵树重新染成同一种颜色 但是，由于一些奥妙重重的原因，每一次染色Applese可以选择两个有边相连的点，将其中一个染成另一个的颜色。而进行一次这样的操作需要付出两种颜色价值和的代价 现在，Applese的钱要用来买书(game)，所以他想要最小化代价 输入描述: 输入包括若干行 第一行包括一个数n，表示这棵树有n个节点 第二行包括n个数，第i个数表示第i个节点的颜色col i **注意：一个颜色的标号即价值 接下来的n - 1行，每行包括两个数u, v，表示u节点与v节点之间有一条无向边 n ≤ 100000, 1 ≤ col i ≤ 1e9，数据保证是一棵树 输出描述: 输出包括一行 第一行包括一个数，表示最小代价 示例1 输入 复制 4 2 3 4 3 1 2 2 3 3 4 输出 复制 12 边的输入根本就是多余的，直接枚举所有颜色统计最小的值即可。 　　 1 #include<bits/stdc++.h> 2 using namespace std; 3 #define ll long long 4

超大图像的二值化方法 1.可以采用分块方法， 2.先缩放处理就行二值化，然后还原大小 一：分块处理超大图像的二值化问题 def big_image_binary(image): print(image.shape) #( 4208 , 2368 , 3 )　　 #超大图像，屏幕无法显示完整 cw,ch = 256 , 256 h,w = image.shape[: 2 ] gray = cv.cvtColor(image,cv.COLOR_RGB2GRAY) #要二值化图像，要先进行灰度化处理 for row in range( 0 ,h,ch): for col in range( 0 ,w,cw): roi = gray[row:row+ch,col:col+ cw] #获取分块 # ret,binary = cv.threshold(roi, 0 , 255 ,cv.THRESH_BINARY| cv.THRESH_OTSU)　　#全局阈值 binary = cv.adaptiveThreshold(roi, 255 ,cv.ADAPTIVE_THRESH_GAUSSIAN_C,cv.THRESH_BINARY, 127 , 20 )　　#局部阈值 gray[row:row + ch, col:col + cw] = binary　　 #分块覆盖 print(np.std