pivot

数据结构与算法学习笔记之 适合大规模的数据排序

由 梦想的初衷 提交于 2021-02-20 13:35:47
前言 　　 在数据排序的算法中，不同数据规模应当使用合适的排序算法才能达到最好的效果，如小规模的数据排序，可以使用冒泡排序、插入排序，选择排序，他们的时间复杂度都为O（n 2 ），大规模的数据排序就可以使用归并排序和快速排序，时间复杂度为O（nlogn）。今天我们就来看一下归并排序和快速排序 。 正文 　　 归并排序的原理 　　 核心思想（分治思想）： 　　　　排序数组，将数组从中间分成前后两部分，对前后两部分分别排序，然后合在一起，这个数组就是有序的。 　　 归并排序的性能分析 　　1.归并排序是一个稳定的排序算法：在合并的过程中，如果A[p...q]和A[q+1...r]之间中有相同的元素，先把A[p...q]中的元素放入tmp数组。这样就保证了值相同的元素，在合并前后的先后顺序不变。 　　2.归并排序的时间复杂度是O（nlogn）：在解决递归问题时，我们得出一个结论：递归问题可以写成递推公式，递归代码的时间复杂度也可以写成递推公式 　　我们假设对n个元素进行归并排序需要的时间是T（n），那分解成两个子数组排序的时间都是T(n/2)，套用结论可以得到归并排序的时间复杂度的计算公式就是： 　　 T(1) = C； n=1 时，只需要常量级的执行时间，所以表示为 C。 T(n) = 2*T(n/2) + n； n>1 再次将这个公式分解: T(n) = 2*T(n/2) + n =

SQL turning rows into columns and populating with values

由 一世执手 提交于 2021-02-19 08:22:08
问题 I'm not quite sure why this table was designed this way, but it's making it hard to solve my problem. Looking at the data: NAME TYPE_NAME DEFAULT_VALUE VALUE TEST 1 Currency Null 14 TEST 1 Event Count 0 0 TEST 1 Usage 8 Null TEST 1 Events Amt 0 0 TEST 1 Usage Amt Null 13 TEST 1 From Date Null 5 TEST 1 To Date 6 Null TEST 1 Traffic Scenario Null 2 TEST 1 Band 1 Null TEST 1 Service 15 Null TEST 1 Tariff Rate Name Null 4 TEST 2 Currency EUR 0 TEST 2 Event Count Null 9 TEST 2 Usage 10 Null TEST 2

How to flatten a PostgreSQL result

由 Deadly 提交于 2021-02-19 05:04:28
问题 I have experiments, features, and feature_values. Features have values in different experiments. So I have something like: Experiments: experiment_id, experiment_name Features: feature_id, feature_name Feature_values: experiment_id, feature_id, value Lets say, I have three experiments (exp1, exp2, exp3) and three features (feat1, feat2, feat3). I would like to have a SQL-result that looks like: feature_name | exp1 | exp2 | exp3 -------------+------+------+----- feat1 | 100 | 150 | 110 feat2 |

Sorting Excel column with Python

由 对着背影说爱祢 提交于 2021-02-18 14:00:28
问题 Let's say I have a list like this: time type value 80 1A 10 100 1A 20 60 18 56 80 18 7 80 2A 10 100 2A 10 80 28 10 100 28 20 and I need to change it to be like this: time type 60 80 100 1A 10 20 1B 56 7 2A 10 10 2B 10 20 So far what I did is just basic sorting of the column: target_column = 0 book = open_workbook('result.xls') sheet = book.sheets()[0] data = [sheet.row_values(i) for i in range(sheet.nrows)] labels = data[0] data = data[1:] data.sort(key= lambda x: x[target_column]) bk = xlwt

Sorting Excel column with Python

由 喜你入骨 提交于 2021-02-18 13:59:35
问题 Let's say I have a list like this: time type value 80 1A 10 100 1A 20 60 18 56 80 18 7 80 2A 10 100 2A 10 80 28 10 100 28 20 and I need to change it to be like this: time type 60 80 100 1A 10 20 1B 56 7 2A 10 10 2B 10 20 So far what I did is just basic sorting of the column: target_column = 0 book = open_workbook('result.xls') sheet = book.sheets()[0] data = [sheet.row_values(i) for i in range(sheet.nrows)] labels = data[0] data = data[1:] data.sort(key= lambda x: x[target_column]) bk = xlwt

MySQL pivot row into dynamic number of columns

由 痴心易碎 提交于 2021-02-17 06:34:07
问题 Lets say I have three different MySQL tables: Table products : id | name 1 Product A 2 Product B Table partners : id | name 1 Partner A 2 Partner B Table sales : partners_id | products_id 1 2 2 5 1 5 1 3 1 4 1 5 2 2 2 4 2 3 1 1 I would like to get a table with partners in the rows and products as columns. So far I was able to get an output like this: name | name | COUNT( * ) Partner A Product A 1 Partner A Product B 1 Partner A Product C 1 Partner A Product D 1 Partner A Product E 2 Partner B

How to pivot on dynamic values in Snowflake

由 僤鯓⒐⒋嵵緔 提交于 2021-02-16 20:06:51
问题 I want to pivot a table based on a field which can contain "dynamic" values (not always known beforehand). I can make it work by hard coding the values (which is undesirable): SELECT * FROM my_table pivot(SUM(amount) FOR type_id IN (1,2,3,4,5,20,50,83,141,...); But I can't make it work using a query to provide the values dynamically: SELECT * FROM my_table pivot(SUM(amount) FOR type_id IN (SELECT id FROM types); --- 090150 (22000): Single-row subquery returns more than one row. SELECT * FROM

How to pivot on dynamic values in Snowflake

由 我只是一个虾纸丫 提交于 2021-02-16 20:04:05
问题 I want to pivot a table based on a field which can contain "dynamic" values (not always known beforehand). I can make it work by hard coding the values (which is undesirable): SELECT * FROM my_table pivot(SUM(amount) FOR type_id IN (1,2,3,4,5,20,50,83,141,...); But I can't make it work using a query to provide the values dynamically: SELECT * FROM my_table pivot(SUM(amount) FOR type_id IN (SELECT id FROM types); --- 090150 (22000): Single-row subquery returns more than one row. SELECT * FROM

SQL Server Dynamic pivot for an unknow number of columns

由 ▼魔方 西西 提交于 2021-02-15 07:44:29
问题 The question has been asked before, but in a slightly different scenario (one that doesn't seem to fit to my question) so.. I have data that looks like this Name |Item |Note George|Paperclip |Two boxes George|Stapler |blue one George|Stapler |red one George|Desk lamp |No light bulb Mark |Paperclip |One box 2" Mark |Paperclip |One box 4" Mark |Block Notes|a blue one ..? |..? |..? And I would want to pivot by name, to obtain Name |Paperclip|Stapler|Desk Lamp|Block Notes George| 1| 2| 1| NULL

Unity 镜子效果

由 青春壹個敷衍的年華 提交于 2021-02-13 00:40:41
1 Create Mirror —— 创建镜子 本教程，无需自己找镜子Shader，只需2个脚本即可在Unity中创建一个简单的模拟镜面反射效果 1. 在场景中创建一个 Plane —— 用来作为镜子 2. 同时创建一个材质球 /Material —— 给到 Plane 上 3. 修改新创建的 Material 的 Shader 为 Unlit/Texture 2 Create Camera —— 创建一个新相机 1. 新建一个 Render Texture（我改名为 Plane 便于区分和理解） 2. 右键 层次列表/Hierarchy —— 创建一个新的 Camera 3. 将新建的 Render Texture（Plane）给新建的 Camera 组件中的 Target Texture 4. 给新建的 Camera相机，添加脚本 ChinarMirrorPlane 并将 Main Camera与 Plane 拖到 Inspector 面板中对应的属性里 5. 给新建的 Camera相机，添加脚本 ChinarMirror ，并将 Plane 拖至 Inspector 面板中 注意： 一定要修改 Plane 材质的属性为： 具体流程其实很简单，如下 两个脚本，都需要挂载到 Camera： using UnityEngine; /// <summary> /// 镜子管理脚本 —
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