List

from:https://campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-2-python-lists?ex=2

-----------------1-------------------------------------

  • Create a list

As opposed to intbool etc., a list is a compound data type; you can group values together:

a = "is"
b = "nice"
my_list = ["my", "list", a, b]

--------------2----------------------------------------

  • Create list with different types

A list can contain any Python type. Although it's not really common, a list can also contain a mix of Python types including strings, floats, booleans, etc.

# area variables (in square meters)
hall = 11.25
kit = 18.0
liv = 20.0
bed = 10.75
bath = 9.50

# Adapt list areas
areas = ["hallway",hall, "kitchen",kit, "living room", liv, "bedroom",bed, "bathroom", bath]

# Print areas
print(areas)

---------------3-------------------------------------

  • Select the valid list
  • my_list = [el1, el2, el3]

both of them are correct:A. [1, 3, 4, 2] B. [[1, 2, 3], [4, 5, 7]] C. [1 + 2, "a" * 5, 3]

Subsetting lists

  • Subset and conquer

x = ["a", "b", "c", "d"]
x[1]
x[-3] # same result!
  • Subset and calculate

x = ["a", "b", "c", "d"]
print(x[1] + x[3])
  • Slicing and dicing

x = ["a", "b", "c", "d"]
x[1:3]

The elements with index 1 and 2 are included, while the element with index 3 is not.

  • Slicing and dicing (2)

x = ["a", "b", "c", "d"]
x[:2]
x[2:]
x[:]
  • Subsetting lists of lists

x = [["a", "b", "c"],
["d", "e", "f"],
["g", "h", "i"]]
x[2][0]
x[2][:2]

List Manipulation

--------------------1-----------------------

Replace list elements

x = ["a", "b", "c", "d"]
x[1] = "r"
x[2:] = ["s", "t"]
-------------------2------------

Extend a list

x = ["a", "b", "c", "d"]
y = x + ["e", "f"]
-------------------3------------

Delete list elements

x = ["a", "b", "c", "d"]
del(x[1])
Pay attention here: as soon as you remove an element from a list, the indexes of the elements that come after the deleted element all change!
The ; sign is used to place commands on the same line. The following two code chunks are equivalent:
# Same line
command1; command2 # Separate lines
command1
command2 So if delete two items, pay more attention here. better to use like this del(areas[-4:-2]), instead of "del(areas[10]); del(areas[11])","del(areas[10:11])" "del(areas[-3]); del(areas[-4])", ----------------------------------------------4--------------------------------------------------------------

Inner workings of lists

if use "areas_copy = areas", then they are the same thing, when value in one of them changed, both of them will be changed.

if use "areas_copy = areas[:]", then they are not the same thing, when value in one of them changed, the other one will Not be changed.



Intro to Python for Data Science Learning 2 - List的更多相关文章

  1. Intro to Python for Data Science Learning 8 - NumPy: Basic Statistics

    NumPy: Basic Statistics from:https://campus.datacamp.com/courses/intro-to-python-for-data-science/ch ...

  2. Intro to Python for Data Science Learning 7 - 2D NumPy Arrays

    2D NumPy Arrays from:https://campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-4- ...

  3. Intro to Python for Data Science Learning 5 - Packages

    Packages From:https://campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-3-functio ...

  4. Intro to Python for Data Science Learning 6 - NumPy

    NumPy From:https://campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-4-numpy?ex=1 ...

  5. Intro to Python for Data Science Learning 4 - Methods

    Methods From:https://campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-3-function ...

  6. Intro to Python for Data Science Learning 3 - functions

    Functions from:https://campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-3-functi ...

  7. Intermediate Python for Data Science learning 2 - Histograms

    Histograms from:https://campus.datacamp.com/courses/intermediate-python-for-data-science/matplotlib? ...

  8. Intermediate Python for Data Science learning 1 - Basic plots with matplotlib

    Basic plots with matplotlib from:https://campus.datacamp.com/courses/intermediate-python-for-data-sc ...

  9. Intermediate Python for Data Science learning 3 - Customization

    Customization from:https://campus.datacamp.com/courses/intermediate-python-for-data-science/matplotl ...

随机推荐

  1. pip安装python包出现Cannot fetch index base URL http://pypi.python.org/simple/

    pipinstall***安装python包,出现 Cannot fetch index base URL  http://pypi.python.org/simple /错误提示或者直接安装不成功. ...

  2. ios中的coredata的使用

    Core Data数据持久化是对SQLite的一个升级,它是iOS集成的,在说Core Data之前,我们先说说在CoreData中使用的几个类. (1)NSManagedObjectModel(被管 ...

  3. spark脚本日志输出级别设置

    import org.apache.log4j.{ Level, Logger } Logger.getLogger("org").setLevel(Level.WARN) Log ...

  4. anaconda资源链接

    清华源: https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/ anaconda所有版本大全: http://www.bubuko.com/in ...

  5. HDU 4578 - Transformation - [加强版线段树]

    题目链接:http://acm.hdu.edu.cn/showproblem.php?pid=4578 Problem Description Yuanfang is puzzled with the ...

  6. SQL Fundamentals || DCL(Data Control Language) || 用户管理&Profile概要文件

    SQL Fundamentals || Oracle SQL语言 语句 解释 Create user Creates a user(usually performed by a DBA) Grant ...

  7. 0004python中的map,reduce,lambda,filter

    编程实现:a[0]*b[0] + a[1]*b[1] +...+a[i]*b[j] >>> a=[1,2,3,4,5]>>> b=[6,7,8,9,0] >& ...

  8. Git:上传GitHub项目操作步骤

    git教程:git详解.gitbook #首次上传步骤 首先在工程文件位置处右键git bash here 本地创建ssh key $ ssh-keygen -t rsa -C "your_ ...

  9. FMOD变声如何捕获并存储处理音效之后的数据

    类似AVAudioEngine的功能,一个Engine可以将N个connect连接(串联和并联)在一起,这样来实现多个输入源,多层处理效果的混合输出.实现这个所需功能也是通过这样的方案来实现的.也就是 ...

  10. 分析 mongodb admin local 修改ip 热修改

    分析 mongodb   admin  local 更改ip前 [root@e ~]# mongo mongodb://admin:adminpwd123@10.144.114.152 MongoDB ...