宋朝，武松为兄报仇，杀死了西门庆与潘金莲，千年之后，两个盗墓贼无意之间挖出了西门庆的尸体，此时正逢天狗食月，发生尸变，吸收了大量生人的阳气，法力大增，心里只记得金莲。在盗墓贼的协助下，找到了杨玉莲和保安小武。为了化解这场危机，一场人尸大战在所难免。
要是没命回去，不是害人家闺女当一辈子寡妇嘛。
27% of the people have no ideal and no goal in life.
Ferit Aslan (Can Yaman) is a very successful businessman, and is extremely organized. He wants the same manner of organization in both his private and professional life. Nazli (Ozge Giirel) who is studying gastronomy needs to find a job immediately as she is responsible for covering the expenses of the home she shares with her friend and sister. She is a stubborn and adamant personality, so she has a tough time keeping a job. Both completely opposites, meet each other in this series. ©IMDb.com
金妍雨有一个比她大18岁的姐姐，两人格格不入。妍雨公司的企划董事睿希精明干练、才貌双全，是集团社长的女儿，在家人的介绍下认识了律师姜东硕。
《冰川时代4》讲述的依然是那些生活在冰川时期的特殊动物“家庭”经历的冒险故事。那只永远追着松果的无敌贱，又苦逼的小松鼠奎特（克里斯·韦奇 Chris Wedge 配音 ）这次搞出了更大的事件，一个不小心让大陆板块四分五裂，使得猛犸象曼尼（雷·罗马诺 Ray Roman o 配音）、树懒希德（约翰·雷吉扎莫 John Leguizamo 配音）以及剑齿虎迪亚哥（丹尼斯·利瑞 Denis Leary 配音）因此和家人、伙伴失散分离，在板块激烈的运动并分裂漂移后，只能使用一块流冰作为临时的船只，展开一段惊奇的海上大冒险，在海上他们会遭遇险恶的自然环境，也会遇到海盗，而回家与家人团聚是他们的终极愿望，他们最后能否顺利回家呢？
贝弗利和穆瑞育有三个孩子，艾瑞卡（Hayley Orrantia 饰）、亚当（肖恩·吉布朗尼 Sean Giambrone 饰）和巴里（托伊·金太尔 Troy Gentile 饰），这三个活泼可爱，有时候又显得过于调皮的小鬼头给家中增添了不少欢声笑语。电视剧真实的记录下了一个大家庭中发生的风风雨雨，让人看来感同身受。
拆挡万事屋，一对超能力兄弟，“偶遇”被虚空灵魂附身的女孩，各种奇幻委托任务，最终打开了虚空之门和女孩的秘密……
MBC短幕剧，讲述了朝鲜时代君王李裪（尹斗俊 饰）与高三少女甘霖（金涩琪 饰）之间的奇幻成长罗曼史，向对于现实不安而奋斗的现代人传达共鸣和勇气。
该剧围绕四个家庭，讲述了家庭成员迎着阳光风雨努力奋斗，最终收获成长的故事。
Fu and I just covered the body with corn stalk, and when we finished, we went back to clean up. When we went back, Zhao Mou and Wang Jiying had already paved the beds in the master bedroom and the small bedroom, put the dirty quilts into the closet, took out the new quilts and paved them. I swept away all the cigarette butts in the room and Fu Gang went to the kitchen and the room outside to clean up. Wang Jiying found three plastic bags in his house, We put the rubbish in plastic bags, The bank card, mobile phone, snacks we bought, watermelon peel we ate, some clothes and flowers were put into plastic bags. At about 5 o'clock in the morning, we walked north along the river bank. Zhao Mou and Fu Gang and I respectively carried a garbage bag. Wang Jiying carried the computer mainframe. After we walked along the river for some distance, we threw the garbage and the computer mainframe into the river.
Fan Ren, who met the policeman in Sanwarm, ran away again. Qinglan was urged by the credit card company to repay the money. Koko was not satisfied with Yishang's marriage partner Yu Ying, so he came to Yishang to reconsider his marriage. Patrol officers found Fan Ren's license plate number. He came to Fan Ren's house to ring the doorbell, but did not answer. He happened to meet Fu Ying. Yu Ying came to Yishang's home in Korean clothes, but Koko showed an impatient expression. Yu Ying found Fu Ying, who was preparing a packed lunch for Matan. She hurriedly said it was for a friend who rented a house. Yu Ying was surprised. Yi Shang and Yu Ying finally took their parents to the hotel to meet.
2018年秋天，在梦想成为王者的18岁主人公面前，时光机突然出现。从时光机中现身的神秘少女告诉他：“我是从2068年过来的。魔王降临未来世界，他让人们饱受折磨，让世界陷入绝望之中”。为了改变未来绝望的世界而来到2018年的少女还对他说：“未来的你，成为了毁灭世界的魔王，时间的王者——时王”。命中注定会变身成为假面骑士时王的主人公，他不是英雄而是未来的魔王吗……他未来的命运究竟如何？这是一个主人公跨越时空，与历代平成假面骑士相遇，为了挽救过去、现在、未来而最终成为新时代王者的故事。
弟弟少义嗜赌成性，将房契地契输给陈剑锋的父亲陈子秋的手下，袍哥头目马三。少诚答应还钱，想用凌副
第十王国是由雪姑七友、小红帽、睡公主、灰姑娘、国王的新衣等等大家耳熟能详的童话故事，再加上人狼、食人怪、仙女、邪恶女王等等的幻想世界人物，所组合而成的一套史诗式浪漫爱情冒险故事。 故事内容基本上环绕着一对生活在美国纽约市，中央公园附近大厦的父女，在一次机缘巧合下遇到一只来自异世界，听得懂人们说话的一头狗，但亦因为这样而被来自异世界的人狼及食人怪追杀，他们为了逃避，结果与那一头狗走进了一度通往异世界的入口，进入了他们从没想到的世界——第九王国。 他们在异世界中，一方面要逃避邪恶女王的手下追杀，另一方面亦要找寻回到现实世界的方法，但他们每进入一个国度，也经历及见识了不同的世界，从而产生了不少刺激、紧张、浪漫的冒险故事。
这些女子中，倒有一半是因为心性要强，希望像玄武将军一样建功立业的。
南方某市法院开庭审理了一起毒杀案，被告人蒋漫枝（钟欣潼 饰）涉嫌用河豚毒素杀害其丈夫柳慕阳（张睿 饰）。辩护人栾珠（蒙亭宜 饰）坚称柳慕阳是自己误食了毒酸奶而非预谋杀害，此时另一条线索表明，八年前的一起强奸案，被害人就是如今的蒋漫枝，而强奸犯许一城竟然和被害者柳慕阳长得一模一样，千丝万缕的联系预示着这两起案件远没有那么简单。蒋漫枝为何会爱上曾性侵过自己的人，她又为何会再次痛下杀手？
Use Python for data analysis: This book is a detailed version of Python's pandas package. Learn this to master some basic pandas commands. However, this is not the point, because pandas is too slow to produce a large amount of data and may collapse (I don't know if there is any improvement now-!) The point is, through studying this book, I feel a little about the data operation and am familiar with the basic data operation process. All the operations in this book can be replaced by native Python, and Pandas package is not needed. Finding feelings is very important.
Step 2 Restrict detection
