vertical-align | 易学教程

行内块和文字垂直对齐vertical-agign

阅读更多关于行内块和文字垂直对齐vertical-agign

vertical-align 垂直对齐（对于块级元素无效，主要用来控制表单或者图片与文字对齐的）图片和文字默认是基线对齐属性： baseline 基线 top 顶线 middle 中线 bottom 底线 vertical-align 另一个作用去除文字底侧空白缝隙有一个特性：图片或者表单等行内块元素，他的底线和父级盒子的基线对齐，装图片底层会有一个空白缝隙解决方法1：display: block; 解决方法2： vertical-align: top 来源： https://www.cnblogs.com/guniang/p/11935738.html

pandas 之数据合并

阅读更多关于 pandas 之数据合并

import numpy as np import pandas as pd Data contained in pandas objects can be combined together in a number of ways: pandas.merge connects rows in DataFrame based on one or more keys. This will be familiar to users of SQL or other relational databases, as it impliemnts(工具) database join oprations. pandas.concat concatenates or "stacks" together objects along an axis. The combine_first instance method enables splicing(拼接) together overlapping data to fill in missing values in one object with values from another. I will address each of these and give a number of examples. They'll be utilized in

pandas 之多层索引

阅读更多关于 pandas 之多层索引

In many applications, data may be spread across a number of files or datasets or be arranged in a form that is not easy to analyze. This chapter focuses on tools to help combine, and rearrange data. (在许多应用中，数据可以分布在多个文件或数据集中，或者以不易分析的形式排列。本章重点介绍帮助组合和重新排列数据的工具.) import numpy as np import pandas as pd 多层索引 Hierarchical indexing is an important featuer of pandas that enables you to have multiple(two or more) index levels on an axis . Somewhat abstractly, it provides a way for you to to work with higher dimensional data in a lower dimensional form.(通过多层索引的方式去从低维看待高维数据). Let's start with a simple

pandas 之特征工程

阅读更多关于 pandas 之特征工程

import numpy as np import pandas as pd So far(到目前为止) in this chapter we've been concerned with rearranging data. Filterng, cleaning, and other transformations are another class of important oprations. 数据去重 Duplicate rows may be found in a DataFrame for any number of reasons. Here is an example: data = pd.DataFrame({ 'k1': ['one', 'two']*3 + ['two'], 'k2': [1, 1, 2, 3, 3, 4, 4] }) data */ /*--> */ k1 k2 0 one 1 1 two 1 2 one 2 3 two 3 4 one 3 5 two 4 6 two 4 The DataFrame method duplicated returns a boolean Series indcating whether each rows is a duplicate (has been observed in a previous row)

pandas 之数据清洗-缺失值

阅读更多关于 pandas 之数据清洗-缺失值

Abstract During the course fo doing data analysis and modeling, a significant amount of time is spend on data preparation: loading, cleaning, transforming, and rearrangin. 在整个数据分析建模过程中, 大量的时间(80%)的时间是用在了数据的预处理中, 如数据清洗, 加载, 标准化, 重塑等. Such tasks are often reported to take 80% or more of an analyst's time. Sometimes the way that data is store in(存储于) files or databases is not in the right format for a particular task (数据存储在文件, 或数据库中, 而且格式, 内容不是你预想的那样能直接用的) Many reseachers choose to do ad hoc processing of data from one form to another using a general-purpose programming language, like Python, R,

百度UEditor 去除图片之间空隙

阅读更多关于百度UEditor 去除图片之间空隙

第一种方法找到ueditor.all.js里的render: function (container)在里面添加img{vertical-align:top;outline-width:0px;} 第二种在ueditor.all.min.js里搜索 p{margin:5px 0;}</style> 在p{margin:5px 0;}</style>前面添加img{vertical-align:top;outline-width:0px;} 2方法都试试来源： https://www.cnblogs.com/gjh99/p/11897830.html

迷宫小游戏

阅读更多关于迷宫小游戏

迷宫小游戏 <html lang="zh-CN" class="translated-ltr"> <head> <meta charset="UTF-8"> <title>迷宫</title> <style type="text/css"> canvas { display: block; margin: 50px auto; box-shadow: -2px -2px 2px #F3F2F2, 5px 5px 5px #6F6767; } body { margin: 0; padding: 0; font-family: "Microsoft YaHei", "微软雅黑", "consolas"; background: #fbecc3; background-attachment: fixed; } a { text-decoration: none; color: #000; } .navbar { background-color: #000; width: 100%; height: 50px; } .container { width: 1000px; margin: 0 auto; } .navbar .navbar-content-1 a { float: left; color: #FFF; line-height: 50px; display: inline

Pandas 之描述性统计案例

阅读更多关于 Pandas 之描述性统计案例

认识 jupyter地址: https://nbviewer.jupyter.org/github/chenjieyouge/jupyter_share/blob/master/share/pandas-%20%E6%8F%8F%E8%BF%B0%E6%80%A7%E7%BB%9F%E8%AE%A1.ipynb import numpy as np import pandas as pd pandas objects are equipped(配备的) with a set of common mathematical and statistical methods. Most of these fall into the categrory of reductions or summary statistics, methods that exract(提取) a single value(like the sum or mean) from a Series of values from the rows or columns of a DataFrame. Compared with the similar methods found on NumPy arrays, they built-in handling for missiing data. Consider a

css布局技巧

阅读更多关于 css布局技巧

CSS用户界面样式鼠标样式currsor li{ cursor：pointer； } 设置或检索在对象上移动鼠标指针采用何种系统预定义的光标形状属性值描述 default 默认 pointer 小手 move 移动 text 文本 not-allowed 禁止轮廓线 outline 给表单添加outline：0；或者outline：none；样式之后，就可以去掉默认的边框防止拖拽文本resize textarea{ resize:none; } vertical-align属性应用 CSS的vertical-align经常设置图片或者表单（行内块元素）和文字垂直对齐 vertical-align：baseline|top|middle|bottom 值描述 baseline 默认，元素放在父元素的基线上 top 把元素的顶端与行中最高元素的顶端对齐 middle 把此元素放置在父元素的中部 bottom 把元素的顶端与行中最低的元素顶端对齐解决图片底部默认空白缝隙问题 bug：图片底部会有一个空白缝隙，原因时行内块元素回和文字的基线对齐主要解决方法给图片添加vertical-align：middle| top|bottom等把图片转换为块级元素；display：block；溢出文字省略号代替单行文本溢出用省略号显示先强制一行内文本显示 white

html和css(8)

阅读更多关于 html和css(8)

第八天笔记学习目标元素的显示隐藏 overflow vertical-align 精灵图字体图标滑动门其他属性元素的显示和隐藏将元素的显示模式设置成none即可让元素隐藏 display的值为none的时候，元素完全隐藏 display的值为block的时候，元素呈块级显示 display的值为inline的时候，元素呈行内显示 display为none隐藏时候是不占位置的实际工作中用的较多 visibility 控制元素的显示和隐藏 visibility的值选择 hidden 占位置隐藏 visible 显示实际工作中用的较少 overflow 控制元素溢出之后的显示方式取值： visible 直接显示 hidden 超出的部分隐藏掉 auto 如果超出，自动产生滚动条，如果不超出，不产生 scroll 不管有没有超出，都有滚动条控件 overflow-x:hidden; overflow-y:hidden; BFC 块状格式上下文产生BFC之后，盒子内部的空间与外部完全隔离那些可以产生BFC ? overflow只要取值不是visible的情况下 float的值不为none的时候 display为table或者inline-block的时候 position的取值为fixed或者absolute (课外BFC参考资料)[ https://www

订阅 vertical-align