当前位置:首页 > 编程教程 > Python技术文章 > python PrettyTable模块的安装与简单应用

如何实现python PrettyTable模块的安装与简单应用

  • 发布时间:
  • 作者:码农之家
  • 点击:105

这篇文章主要知识点是关于python、PrettyTable、PrettyTable模块、Python实用库 PrettyTable 学习笔记 的内容,如果大家想对相关知识点有系统深入的学习,可以参阅以下电子书

零起点Python足彩大数据与机器学习实盘分析
  • 类型:Python数据分析大小:122.4 MB格式:PDF作者:何海群
立即下载

python PrettyTable模块的安装与简单应用

prettyTable 是一款很简洁但是功能强大的第三方模块,主要是将输入的数据转化为格式化的形式来输出,即:以表格的形式的打印输出出来,能够起到美观的效果,今天简单地试用了一下,

一、下载与安装

进入pypi.python.org查找并下载PrettyTable将其放在Python文件夹下的Scripts文件夹下

python PrettyTable模块的安装与简单应用

进入命令提示符工具,转到Scripts文件夹下,通过命令pip install prettytable-0.7.2.tar.bz2安装该模块

二、简单的使用

导入该模块

from prettytable import PrettyTable

创建表头

table=PrettyTable(["姓名","学号","性别"])

插入数据

table.add_row(["小明","01","男"])
table.add_row(["小红","02","女"])
table.add_row(["小黄","03","男"])

显示该表

print(table)

三、下面是具体的实践:

#!usr/bin/env python
#encoding:utf-8
 
 
'''
__Author__:沂水寒城
功能: PrettyTable 模块使用
'''
 
import prettytable
from prettytable import from_csv
from prettytable import PrettyTable
 
 
 
def testFunc1():
  '''
  '''
  table=PrettyTable()
  table.field_names = ["City name", "Area", "Population", "Annual Rainfall"]
  table.add_row(["Adelaide",1295, 1158259, 600.5])
  table.add_row(["Brisbane",5905, 1857594, 1146.4])
  table.add_row(["Darwin", 112, 120900, 1714.7])
  table.add_row(["Hobart", 1357, 205556, 619.5])
  table.add_row(["Sydney", 2058, 4336374, 1214.8])
  table.add_row(["Melbourne", 1566, 3806092, 646.9])
  table.add_row(["Perth", 5386, 1554769, 869.4])
  print '=================================table===================================='
  print table
 
  table.add_column("City name",["Adelaide","Brisbane","Darwin","Hobart","Sydney","Melbourne","Perth"])
  table.add_column("Area",[1295, 5905, 112, 1357, 2058, 1566, 5386])
  table.add_column("Population",[1158259, 1857594, 120900, 205556, 4336374, 3806092,1554769])
  table.add_column("Annual Rainfall",[600.5, 1146.4, 1714.7, 619.5, 1214.8, 646.9,869.4])
  print '=================================table===================================='
  print table
 
 
def testFunc2(data='mycsv.csv'):
  '''
  从 csv 文件中加载数据
  '''
  mycsv=open(data)
  table=from_csv(mycsv)
  mycsv.close()
  print '===========================================table=============================================='
  print table
  print '=================================table:SepalLength_Species===================================='
  print table.get_string(fields=['SepalLength','Species'])
  print '=======================================table:60=>80 rows======================================'
  print table.get_string(start=60,end=80)
 
 
 
 
 
if __name__=='__main__':
  testFunc1()
  testFunc2(data='iris.csv')

结果如下:

=================================table====================================
+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
| Adelaide | 1295 | 1158259  |   600.5   |
| Brisbane | 5905 | 1857594  |   1146.4   |
|  Darwin | 112 |  120900  |   1714.7   |
|  Hobart | 1357 |  205556  |   619.5   |
|  Sydney | 2058 | 4336374  |   1214.8   |
| Melbourne | 1566 | 3806092  |   646.9   |
|  Perth  | 5386 | 1554769  |   869.4   |
+-----------+------+------------+-----------------+
=================================table====================================
+-----------+------+------------+-----------------+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall | City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+-----------+------+------------+-----------------+
| Adelaide | 1295 | 1158259  |   600.5   | Adelaide | 1295 | 1158259  |   600.5   |
| Brisbane | 5905 | 1857594  |   1146.4   | Brisbane | 5905 | 1857594  |   1146.4   |
|  Darwin | 112 |  120900  |   1714.7   |  Darwin | 112 |  120900  |   1714.7   |
|  Hobart | 1357 |  205556  |   619.5   |  Hobart | 1357 |  205556  |   619.5   |
|  Sydney | 2058 | 4336374  |   1214.8   |  Sydney | 2058 | 4336374  |   1214.8   |
| Melbourne | 1566 | 3806092  |   646.9   | Melbourne | 1566 | 3806092  |   646.9   |
|  Perth  | 5386 | 1554769  |   869.4   |  Perth  | 5386 | 1554769  |   869.4   |
+-----------+------+------------+-----------------+-----------+------+------------+-----------------+
===========================================table==============================================
+-----+-------------+------------+-------------+------------+------------+
| id | SepalLength | SepalWidth | PetalLength | PetalWidth | Species  |
+-----+-------------+------------+-------------+------------+------------+
| 1 |   5.1   |  3.5   |   1.4   |  0.2   |  setosa  |
| 2 |   4.9   |   3   |   1.4   |  0.2   |  setosa  |
| 3 |   4.7   |  3.2   |   1.3   |  0.2   |  setosa  |
| 4 |   4.6   |  3.1   |   1.5   |  0.2   |  setosa  |
| 5 |   5   |  3.6   |   1.4   |  0.2   |  setosa  |
| 6 |   5.4   |  3.9   |   1.7   |  0.4   |  setosa  |
| 7 |   4.6   |  3.4   |   1.4   |  0.3   |  setosa  |
| 8 |   5   |  3.4   |   1.5   |  0.2   |  setosa  |
| 9 |   4.4   |  2.9   |   1.4   |  0.2   |  setosa  |
| 10 |   4.9   |  3.1   |   1.5   |  0.1   |  setosa  |
| 11 |   5.4   |  3.7   |   1.5   |  0.2   |  setosa  |
| 12 |   4.8   |  3.4   |   1.6   |  0.2   |  setosa  |
| 13 |   4.8   |   3   |   1.4   |  0.1   |  setosa  |
| 14 |   4.3   |   3   |   1.1   |  0.1   |  setosa  |
| 15 |   5.8   |   4   |   1.2   |  0.2   |  setosa  |
| 16 |   5.7   |  4.4   |   1.5   |  0.4   |  setosa  |
| 17 |   5.4   |  3.9   |   1.3   |  0.4   |  setosa  |
| 18 |   5.1   |  3.5   |   1.4   |  0.3   |  setosa  |
| 19 |   5.7   |  3.8   |   1.7   |  0.3   |  setosa  |
| 20 |   5.1   |  3.8   |   1.5   |  0.3   |  setosa  |
| 21 |   5.4   |  3.4   |   1.7   |  0.2   |  setosa  |
| 22 |   5.1   |  3.7   |   1.5   |  0.4   |  setosa  |
| 23 |   4.6   |  3.6   |   1   |  0.2   |  setosa  |
| 24 |   5.1   |  3.3   |   1.7   |  0.5   |  setosa  |
| 25 |   4.8   |  3.4   |   1.9   |  0.2   |  setosa  |
| 26 |   5   |   3   |   1.6   |  0.2   |  setosa  |
| 27 |   5   |  3.4   |   1.6   |  0.4   |  setosa  |
| 28 |   5.2   |  3.5   |   1.5   |  0.2   |  setosa  |
| 29 |   5.2   |  3.4   |   1.4   |  0.2   |  setosa  |
| 30 |   4.7   |  3.2   |   1.6   |  0.2   |  setosa  |
| 31 |   4.8   |  3.1   |   1.6   |  0.2   |  setosa  |
| 32 |   5.4   |  3.4   |   1.5   |  0.4   |  setosa  |
| 33 |   5.2   |  4.1   |   1.5   |  0.1   |  setosa  |
| 34 |   5.5   |  4.2   |   1.4   |  0.2   |  setosa  |
| 35 |   4.9   |  3.1   |   1.5   |  0.2   |  setosa  |
| 36 |   5   |  3.2   |   1.2   |  0.2   |  setosa  |
| 37 |   5.5   |  3.5   |   1.3   |  0.2   |  setosa  |
| 38 |   4.9   |  3.6   |   1.4   |  0.1   |  setosa  |
| 39 |   4.4   |   3   |   1.3   |  0.2   |  setosa  |
| 40 |   5.1   |  3.4   |   1.5   |  0.2   |  setosa  |
| 41 |   5   |  3.5   |   1.3   |  0.3   |  setosa  |
| 42 |   4.5   |  2.3   |   1.3   |  0.3   |  setosa  |
| 43 |   4.4   |  3.2   |   1.3   |  0.2   |  setosa  |
| 44 |   5   |  3.5   |   1.6   |  0.6   |  setosa  |
| 45 |   5.1   |  3.8   |   1.9   |  0.4   |  setosa  |
| 46 |   4.8   |   3   |   1.4   |  0.3   |  setosa  |
| 47 |   5.1   |  3.8   |   1.6   |  0.2   |  setosa  |
| 48 |   4.6   |  3.2   |   1.4   |  0.2   |  setosa  |
| 49 |   5.3   |  3.7   |   1.5   |  0.2   |  setosa  |
| 50 |   5   |  3.3   |   1.4   |  0.2   |  setosa  |
| 51 |   7   |  3.2   |   4.7   |  1.4   | versicolor |
| 52 |   6.4   |  3.2   |   4.5   |  1.5   | versicolor |
| 53 |   6.9   |  3.1   |   4.9   |  1.5   | versicolor |
| 54 |   5.5   |  2.3   |   4   |  1.3   | versicolor |
| 55 |   6.5   |  2.8   |   4.6   |  1.5   | versicolor |
| 56 |   5.7   |  2.8   |   4.5   |  1.3   | versicolor |
| 57 |   6.3   |  3.3   |   4.7   |  1.6   | versicolor |
| 58 |   4.9   |  2.4   |   3.3   |   1   | versicolor |
| 59 |   6.6   |  2.9   |   4.6   |  1.3   | versicolor |
| 60 |   5.2   |  2.7   |   3.9   |  1.4   | versicolor |
| 61 |   5   |   2   |   3.5   |   1   | versicolor |
| 62 |   5.9   |   3   |   4.2   |  1.5   | versicolor |
| 63 |   6   |  2.2   |   4   |   1   | versicolor |
| 64 |   6.1   |  2.9   |   4.7   |  1.4   | versicolor |
| 65 |   5.6   |  2.9   |   3.6   |  1.3   | versicolor |
| 66 |   6.7   |  3.1   |   4.4   |  1.4   | versicolor |
| 67 |   5.6   |   3   |   4.5   |  1.5   | versicolor |
| 68 |   5.8   |  2.7   |   4.1   |   1   | versicolor |
| 69 |   6.2   |  2.2   |   4.5   |  1.5   | versicolor |
| 70 |   5.6   |  2.5   |   3.9   |  1.1   | versicolor |
| 71 |   5.9   |  3.2   |   4.8   |  1.8   | versicolor |
| 72 |   6.1   |  2.8   |   4   |  1.3   | versicolor |
| 73 |   6.3   |  2.5   |   4.9   |  1.5   | versicolor |
| 74 |   6.1   |  2.8   |   4.7   |  1.2   | versicolor |
| 75 |   6.4   |  2.9   |   4.3   |  1.3   | versicolor |
| 76 |   6.6   |   3   |   4.4   |  1.4   | versicolor |
| 77 |   6.8   |  2.8   |   4.8   |  1.4   | versicolor |
| 78 |   6.7   |   3   |   5   |  1.7   | versicolor |
| 79 |   6   |  2.9   |   4.5   |  1.5   | versicolor |
| 80 |   5.7   |  2.6   |   3.5   |   1   | versicolor |
| 81 |   5.5   |  2.4   |   3.8   |  1.1   | versicolor |
| 82 |   5.5   |  2.4   |   3.7   |   1   | versicolor |
| 83 |   5.8   |  2.7   |   3.9   |  1.2   | versicolor |
| 84 |   6   |  2.7   |   5.1   |  1.6   | versicolor |
| 85 |   5.4   |   3   |   4.5   |  1.5   | versicolor |
| 86 |   6   |  3.4   |   4.5   |  1.6   | versicolor |
| 87 |   6.7   |  3.1   |   4.7   |  1.5   | versicolor |
| 88 |   6.3   |  2.3   |   4.4   |  1.3   | versicolor |
| 89 |   5.6   |   3   |   4.1   |  1.3   | versicolor |
| 90 |   5.5   |  2.5   |   4   |  1.3   | versicolor |
| 91 |   5.5   |  2.6   |   4.4   |  1.2   | versicolor |
| 92 |   6.1   |   3   |   4.6   |  1.4   | versicolor |
| 93 |   5.8   |  2.6   |   4   |  1.2   | versicolor |
| 94 |   5   |  2.3   |   3.3   |   1   | versicolor |
| 95 |   5.6   |  2.7   |   4.2   |  1.3   | versicolor |
| 96 |   5.7   |   3   |   4.2   |  1.2   | versicolor |
| 97 |   5.7   |  2.9   |   4.2   |  1.3   | versicolor |
| 98 |   6.2   |  2.9   |   4.3   |  1.3   | versicolor |
| 99 |   5.1   |  2.5   |   3   |  1.1   | versicolor |
| 100 |   5.7   |  2.8   |   4.1   |  1.3   | versicolor |
| 101 |   6.3   |  3.3   |   6   |  2.5   | virginica |
| 102 |   5.8   |  2.7   |   5.1   |  1.9   | virginica |
| 103 |   7.1   |   3   |   5.9   |  2.1   | virginica |
| 104 |   6.3   |  2.9   |   5.6   |  1.8   | virginica |
| 105 |   6.5   |   3   |   5.8   |  2.2   | virginica |
| 106 |   7.6   |   3   |   6.6   |  2.1   | virginica |
| 107 |   4.9   |  2.5   |   4.5   |  1.7   | virginica |
| 108 |   7.3   |  2.9   |   6.3   |  1.8   | virginica |
| 109 |   6.7   |  2.5   |   5.8   |  1.8   | virginica |
| 110 |   7.2   |  3.6   |   6.1   |  2.5   | virginica |
| 111 |   6.5   |  3.2   |   5.1   |   2   | virginica |
| 112 |   6.4   |  2.7   |   5.3   |  1.9   | virginica |
| 113 |   6.8   |   3   |   5.5   |  2.1   | virginica |
| 114 |   5.7   |  2.5   |   5   |   2   | virginica |
| 115 |   5.8   |  2.8   |   5.1   |  2.4   | virginica |
| 116 |   6.4   |  3.2   |   5.3   |  2.3   | virginica |
| 117 |   6.5   |   3   |   5.5   |  1.8   | virginica |
| 118 |   7.7   |  3.8   |   6.7   |  2.2   | virginica |
| 119 |   7.7   |  2.6   |   6.9   |  2.3   | virginica |
| 120 |   6   |  2.2   |   5   |  1.5   | virginica |
| 121 |   6.9   |  3.2   |   5.7   |  2.3   | virginica |
| 122 |   5.6   |  2.8   |   4.9   |   2   | virginica |
| 123 |   7.7   |  2.8   |   6.7   |   2   | virginica |
| 124 |   6.3   |  2.7   |   4.9   |  1.8   | virginica |
| 125 |   6.7   |  3.3   |   5.7   |  2.1   | virginica |
| 126 |   7.2   |  3.2   |   6   |  1.8   | virginica |
| 127 |   6.2   |  2.8   |   4.8   |  1.8   | virginica |
| 128 |   6.1   |   3   |   4.9   |  1.8   | virginica |
| 129 |   6.4   |  2.8   |   5.6   |  2.1   | virginica |
| 130 |   7.2   |   3   |   5.8   |  1.6   | virginica |
| 131 |   7.4   |  2.8   |   6.1   |  1.9   | virginica |
| 132 |   7.9   |  3.8   |   6.4   |   2   | virginica |
| 133 |   6.4   |  2.8   |   5.6   |  2.2   | virginica |
| 134 |   6.3   |  2.8   |   5.1   |  1.5   | virginica |
| 135 |   6.1   |  2.6   |   5.6   |  1.4   | virginica |
| 136 |   7.7   |   3   |   6.1   |  2.3   | virginica |
| 137 |   6.3   |  3.4   |   5.6   |  2.4   | virginica |
| 138 |   6.4   |  3.1   |   5.5   |  1.8   | virginica |
| 139 |   6   |   3   |   4.8   |  1.8   | virginica |
| 140 |   6.9   |  3.1   |   5.4   |  2.1   | virginica |
| 141 |   6.7   |  3.1   |   5.6   |  2.4   | virginica |
| 142 |   6.9   |  3.1   |   5.1   |  2.3   | virginica |
| 143 |   5.8   |  2.7   |   5.1   |  1.9   | virginica |
| 144 |   6.8   |  3.2   |   5.9   |  2.3   | virginica |
| 145 |   6.7   |  3.3   |   5.7   |  2.5   | virginica |
| 146 |   6.7   |   3   |   5.2   |  2.3   | virginica |
| 147 |   6.3   |  2.5   |   5   |  1.9   | virginica |
| 148 |   6.5   |   3   |   5.2   |   2   | virginica |
| 149 |   6.2   |  3.4   |   5.4   |  2.3   | virginica |
| 150 |   5.9   |   3   |   5.1   |  1.8   | virginica |
+-----+-------------+------------+-------------+------------+------------+
=================================table:SepalLength_Species====================================
+-------------+------------+
| SepalLength | Species  |
+-------------+------------+
|   5.1   |  setosa  |
|   4.9   |  setosa  |
|   4.7   |  setosa  |
|   4.6   |  setosa  |
|   5   |  setosa  |
|   5.4   |  setosa  |
|   4.6   |  setosa  |
|   5   |  setosa  |
|   4.4   |  setosa  |
|   4.9   |  setosa  |
|   5.4   |  setosa  |
|   4.8   |  setosa  |
|   4.8   |  setosa  |
|   4.3   |  setosa  |
|   5.8   |  setosa  |
|   5.7   |  setosa  |
|   5.4   |  setosa  |
|   5.1   |  setosa  |
|   5.7   |  setosa  |
|   5.1   |  setosa  |
|   5.4   |  setosa  |
|   5.1   |  setosa  |
|   4.6   |  setosa  |
|   5.1   |  setosa  |
|   4.8   |  setosa  |
|   5   |  setosa  |
|   5   |  setosa  |
|   5.2   |  setosa  |
|   5.2   |  setosa  |
|   4.7   |  setosa  |
|   4.8   |  setosa  |
|   5.4   |  setosa  |
|   5.2   |  setosa  |
|   5.5   |  setosa  |
|   4.9   |  setosa  |
|   5   |  setosa  |
|   5.5   |  setosa  |
|   4.9   |  setosa  |
|   4.4   |  setosa  |
|   5.1   |  setosa  |
|   5   |  setosa  |
|   4.5   |  setosa  |
|   4.4   |  setosa  |
|   5   |  setosa  |
|   5.1   |  setosa  |
|   4.8   |  setosa  |
|   5.1   |  setosa  |
|   4.6   |  setosa  |
|   5.3   |  setosa  |
|   5   |  setosa  |
|   7   | versicolor |
|   6.4   | versicolor |
|   6.9   | versicolor |
|   5.5   | versicolor |
|   6.5   | versicolor |
|   5.7   | versicolor |
|   6.3   | versicolor |
|   4.9   | versicolor |
|   6.6   | versicolor |
|   5.2   | versicolor |
|   5   | versicolor |
|   5.9   | versicolor |
|   6   | versicolor |
|   6.1   | versicolor |
|   5.6   | versicolor |
|   6.7   | versicolor |
|   5.6   | versicolor |
|   5.8   | versicolor |
|   6.2   | versicolor |
|   5.6   | versicolor |
|   5.9   | versicolor |
|   6.1   | versicolor |
|   6.3   | versicolor |
|   6.1   | versicolor |
|   6.4   | versicolor |
|   6.6   | versicolor |
|   6.8   | versicolor |
|   6.7   | versicolor |
|   6   | versicolor |
|   5.7   | versicolor |
|   5.5   | versicolor |
|   5.5   | versicolor |
|   5.8   | versicolor |
|   6   | versicolor |
|   5.4   | versicolor |
|   6   | versicolor |
|   6.7   | versicolor |
|   6.3   | versicolor |
|   5.6   | versicolor |
|   5.5   | versicolor |
|   5.5   | versicolor |
|   6.1   | versicolor |
|   5.8   | versicolor |
|   5   | versicolor |
|   5.6   | versicolor |
|   5.7   | versicolor |
|   5.7   | versicolor |
|   6.2   | versicolor |
|   5.1   | versicolor |
|   5.7   | versicolor |
|   6.3   | virginica |
|   5.8   | virginica |
|   7.1   | virginica |
|   6.3   | virginica |
|   6.5   | virginica |
|   7.6   | virginica |
|   4.9   | virginica |
|   7.3   | virginica |
|   6.7   | virginica |
|   7.2   | virginica |
|   6.5   | virginica |
|   6.4   | virginica |
|   6.8   | virginica |
|   5.7   | virginica |
|   5.8   | virginica |
|   6.4   | virginica |
|   6.5   | virginica |
|   7.7   | virginica |
|   7.7   | virginica |
|   6   | virginica |
|   6.9   | virginica |
|   5.6   | virginica |
|   7.7   | virginica |
|   6.3   | virginica |
|   6.7   | virginica |
|   7.2   | virginica |
|   6.2   | virginica |
|   6.1   | virginica |
|   6.4   | virginica |
|   7.2   | virginica |
|   7.4   | virginica |
|   7.9   | virginica |
|   6.4   | virginica |
|   6.3   | virginica |
|   6.1   | virginica |
|   7.7   | virginica |
|   6.3   | virginica |
|   6.4   | virginica |
|   6   | virginica |
|   6.9   | virginica |
|   6.7   | virginica |
|   6.9   | virginica |
|   5.8   | virginica |
|   6.8   | virginica |
|   6.7   | virginica |
|   6.7   | virginica |
|   6.3   | virginica |
|   6.5   | virginica |
|   6.2   | virginica |
|   5.9   | virginica |
+-------------+------------+
=======================================table:60=>80 rows======================================
+----+-------------+------------+-------------+------------+------------+
| id | SepalLength | SepalWidth | PetalLength | PetalWidth | Species  |
+----+-------------+------------+-------------+------------+------------+
| 61 |   5   |   2   |   3.5   |   1   | versicolor |
| 62 |   5.9   |   3   |   4.2   |  1.5   | versicolor |
| 63 |   6   |  2.2   |   4   |   1   | versicolor |
| 64 |   6.1   |  2.9   |   4.7   |  1.4   | versicolor |
| 65 |   5.6   |  2.9   |   3.6   |  1.3   | versicolor |
| 66 |   6.7   |  3.1   |   4.4   |  1.4   | versicolor |
| 67 |   5.6   |   3   |   4.5   |  1.5   | versicolor |
| 68 |   5.8   |  2.7   |   4.1   |   1   | versicolor |
| 69 |   6.2   |  2.2   |   4.5   |  1.5   | versicolor |
| 70 |   5.6   |  2.5   |   3.9   |  1.1   | versicolor |
| 71 |   5.9   |  3.2   |   4.8   |  1.8   | versicolor |
| 72 |   6.1   |  2.8   |   4   |  1.3   | versicolor |
| 73 |   6.3   |  2.5   |   4.9   |  1.5   | versicolor |
| 74 |   6.1   |  2.8   |   4.7   |  1.2   | versicolor |
| 75 |   6.4   |  2.9   |   4.3   |  1.3   | versicolor |
| 76 |   6.6   |   3   |   4.4   |  1.4   | versicolor |
| 77 |   6.8   |  2.8   |   4.8   |  1.4   | versicolor |
| 78 |   6.7   |   3   |   5   |  1.7   | versicolor |
| 79 |   6   |  2.9   |   4.5   |  1.5   | versicolor |
| 80 |   5.7   |  2.6   |   3.5   |   1   | versicolor |
+----+-------------+------------+-------------+------------+------------+

这样的结果输出果然是比原始数据好看了许多,这里顺便贴出来代码中使用到的iris.csv数据集,内容如下:

id,SepalLength,SepalWidth,PetalLength,PetalWidth,Species
1,5.1,3.5,1.4,0.2,setosa
2,4.9,3,1.4,0.2,setosa
3,4.7,3.2,1.3,0.2,setosa
4,4.6,3.1,1.5,0.2,setosa
5,5,3.6,1.4,0.2,setosa
6,5.4,3.9,1.7,0.4,setosa
7,4.6,3.4,1.4,0.3,setosa
8,5,3.4,1.5,0.2,setosa
9,4.4,2.9,1.4,0.2,setosa
10,4.9,3.1,1.5,0.1,setosa
11,5.4,3.7,1.5,0.2,setosa
12,4.8,3.4,1.6,0.2,setosa
13,4.8,3,1.4,0.1,setosa
14,4.3,3,1.1,0.1,setosa
15,5.8,4,1.2,0.2,setosa
16,5.7,4.4,1.5,0.4,setosa
17,5.4,3.9,1.3,0.4,setosa
18,5.1,3.5,1.4,0.3,setosa
19,5.7,3.8,1.7,0.3,setosa
20,5.1,3.8,1.5,0.3,setosa
21,5.4,3.4,1.7,0.2,setosa
22,5.1,3.7,1.5,0.4,setosa
23,4.6,3.6,1,0.2,setosa
24,5.1,3.3,1.7,0.5,setosa
25,4.8,3.4,1.9,0.2,setosa
26,5,3,1.6,0.2,setosa
27,5,3.4,1.6,0.4,setosa
28,5.2,3.5,1.5,0.2,setosa
29,5.2,3.4,1.4,0.2,setosa
30,4.7,3.2,1.6,0.2,setosa
31,4.8,3.1,1.6,0.2,setosa
32,5.4,3.4,1.5,0.4,setosa
33,5.2,4.1,1.5,0.1,setosa
34,5.5,4.2,1.4,0.2,setosa
35,4.9,3.1,1.5,0.2,setosa
36,5,3.2,1.2,0.2,setosa
37,5.5,3.5,1.3,0.2,setosa
38,4.9,3.6,1.4,0.1,setosa
39,4.4,3,1.3,0.2,setosa
40,5.1,3.4,1.5,0.2,setosa
41,5,3.5,1.3,0.3,setosa
42,4.5,2.3,1.3,0.3,setosa
43,4.4,3.2,1.3,0.2,setosa
44,5,3.5,1.6,0.6,setosa
45,5.1,3.8,1.9,0.4,setosa
46,4.8,3,1.4,0.3,setosa
47,5.1,3.8,1.6,0.2,setosa
48,4.6,3.2,1.4,0.2,setosa
49,5.3,3.7,1.5,0.2,setosa
50,5,3.3,1.4,0.2,setosa
51,7,3.2,4.7,1.4,versicolor
52,6.4,3.2,4.5,1.5,versicolor
53,6.9,3.1,4.9,1.5,versicolor
54,5.5,2.3,4,1.3,versicolor
55,6.5,2.8,4.6,1.5,versicolor
56,5.7,2.8,4.5,1.3,versicolor
57,6.3,3.3,4.7,1.6,versicolor
58,4.9,2.4,3.3,1,versicolor
59,6.6,2.9,4.6,1.3,versicolor
60,5.2,2.7,3.9,1.4,versicolor
61,5,2,3.5,1,versicolor
62,5.9,3,4.2,1.5,versicolor
63,6,2.2,4,1,versicolor
64,6.1,2.9,4.7,1.4,versicolor
65,5.6,2.9,3.6,1.3,versicolor
66,6.7,3.1,4.4,1.4,versicolor
67,5.6,3,4.5,1.5,versicolor
68,5.8,2.7,4.1,1,versicolor
69,6.2,2.2,4.5,1.5,versicolor
70,5.6,2.5,3.9,1.1,versicolor
71,5.9,3.2,4.8,1.8,versicolor
72,6.1,2.8,4,1.3,versicolor
73,6.3,2.5,4.9,1.5,versicolor
74,6.1,2.8,4.7,1.2,versicolor
75,6.4,2.9,4.3,1.3,versicolor
76,6.6,3,4.4,1.4,versicolor
77,6.8,2.8,4.8,1.4,versicolor
78,6.7,3,5,1.7,versicolor
79,6,2.9,4.5,1.5,versicolor
80,5.7,2.6,3.5,1,versicolor
81,5.5,2.4,3.8,1.1,versicolor
82,5.5,2.4,3.7,1,versicolor
83,5.8,2.7,3.9,1.2,versicolor
84,6,2.7,5.1,1.6,versicolor
85,5.4,3,4.5,1.5,versicolor
86,6,3.4,4.5,1.6,versicolor
87,6.7,3.1,4.7,1.5,versicolor
88,6.3,2.3,4.4,1.3,versicolor
89,5.6,3,4.1,1.3,versicolor
90,5.5,2.5,4,1.3,versicolor
91,5.5,2.6,4.4,1.2,versicolor
92,6.1,3,4.6,1.4,versicolor
93,5.8,2.6,4,1.2,versicolor
94,5,2.3,3.3,1,versicolor
95,5.6,2.7,4.2,1.3,versicolor
96,5.7,3,4.2,1.2,versicolor
97,5.7,2.9,4.2,1.3,versicolor
98,6.2,2.9,4.3,1.3,versicolor
99,5.1,2.5,3,1.1,versicolor
100,5.7,2.8,4.1,1.3,versicolor
101,6.3,3.3,6,2.5,virginica
102,5.8,2.7,5.1,1.9,virginica
103,7.1,3,5.9,2.1,virginica
104,6.3,2.9,5.6,1.8,virginica
105,6.5,3,5.8,2.2,virginica
106,7.6,3,6.6,2.1,virginica
107,4.9,2.5,4.5,1.7,virginica
108,7.3,2.9,6.3,1.8,virginica
109,6.7,2.5,5.8,1.8,virginica
110,7.2,3.6,6.1,2.5,virginica
111,6.5,3.2,5.1,2,virginica
112,6.4,2.7,5.3,1.9,virginica
113,6.8,3,5.5,2.1,virginica
114,5.7,2.5,5,2,virginica
115,5.8,2.8,5.1,2.4,virginica
116,6.4,3.2,5.3,2.3,virginica
117,6.5,3,5.5,1.8,virginica
118,7.7,3.8,6.7,2.2,virginica
119,7.7,2.6,6.9,2.3,virginica
120,6,2.2,5,1.5,virginica
121,6.9,3.2,5.7,2.3,virginica
122,5.6,2.8,4.9,2,virginica
123,7.7,2.8,6.7,2,virginica
124,6.3,2.7,4.9,1.8,virginica
125,6.7,3.3,5.7,2.1,virginica
126,7.2,3.2,6,1.8,virginica
127,6.2,2.8,4.8,1.8,virginica
128,6.1,3,4.9,1.8,virginica
129,6.4,2.8,5.6,2.1,virginica
130,7.2,3,5.8,1.6,virginica
131,7.4,2.8,6.1,1.9,virginica
132,7.9,3.8,6.4,2,virginica
133,6.4,2.8,5.6,2.2,virginica
134,6.3,2.8,5.1,1.5,virginica
135,6.1,2.6,5.6,1.4,virginica
136,7.7,3,6.1,2.3,virginica
137,6.3,3.4,5.6,2.4,virginica
138,6.4,3.1,5.5,1.8,virginica
139,6,3,4.8,1.8,virginica
140,6.9,3.1,5.4,2.1,virginica
141,6.7,3.1,5.6,2.4,virginica
142,6.9,3.1,5.1,2.3,virginica
143,5.8,2.7,5.1,1.9,virginica
144,6.8,3.2,5.9,2.3,virginica
145,6.7,3.3,5.7,2.5,virginica
146,6.7,3,5.2,2.3,virginica
147,6.3,2.5,5,1.9,virginica
148,6.5,3,5.2,2,virginica
149,6.2,3.4,5.4,2.3,virginica
150,5.9,3,5.1,1.8,virginica

prettyTable还可以直接从数据库中读取数据显示出来,这里并没有实践这个,上面的代码testFunc2中实现了读取部分列和指定区间行的作用,感兴趣都可以试试。

以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持码农之家。

Python实用库 PrettyTable 学习笔记

本文实例讲述了Python实用库 PrettyTable。分享给大家供大家参考,具体如下:

PrettyTable安装

使用pip即可十分方便的安装PrettyTable,如下:

pip install PrettyTable

PrettyTable使用示例

github上有PrettyTable的使用说明,链接如下:https://github.com/dprince/python-prettytable

以下是具体的使用示例:

import prettytable as pt

按行添加数据

tb = pt.PrettyTable()
tb.field_names = ["City name", "Area", "Population", "Annual Rainfall"]
tb.add_row(["Adelaide",1295, 1158259, 600.5])
tb.add_row(["Brisbane",5905, 1857594, 1146.4])
tb.add_row(["Darwin", 112, 120900, 1714.7])
tb.add_row(["Hobart", 1357, 205556,619.5])
print(tb)

+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
|  Adelaide | 1295 |  1158259   |      600.5      |
|  Brisbane | 5905 |  1857594   |      1146.4     |
|   Darwin  | 112  |   120900   |      1714.7     |
|   Hobart  | 1357 |   205556   |      619.5      |
+-----------+------+------------+-----------------+

按列添加数据

tb.add_column('index',[1,2,3,4])
print(tb)

+-----------+------+------------+-----------------+-------+
| City name | Area | Population | Annual Rainfall | index |
+-----------+------+------------+-----------------+-------+
|  Adelaide | 1295 |  1158259   |      600.5      |   1   |
|  Brisbane | 5905 |  1857594   |      1146.4     |   2   |
|   Darwin  | 112  |   120900   |      1714.7     |   3   |
|   Hobart  | 1357 |   205556   |      619.5      |   4   |
+-----------+------+------------+-----------------+-------+

使用不同的输出风格

tb.set_style(pt.MSWORD_FRIENDLY)
print('--- style:MSWORD_FRIENDLY -----')
print(tb)
tb.set_style(pt.PLAIN_COLUMNS)
print('--- style:PLAIN_COLUMNS -----')
print(tb)

随机风格,每次不同

tb.set_style(pt.RANDOM)
print('--- style:MSWORD_FRIENDLY -----')
print(tb)
tb.set_style(pt.DEFAULT)
print('--- style:DEFAULT -----')
print(tb)

--- style:MSWORD_FRIENDLY -----
| City name | Area | Population | Annual Rainfall |
|  Adelaide | 1295 |  1158259   |      600.5      |
|  Brisbane | 5905 |  1857594   |      1146.4     |
|   Darwin  | 112  |   120900   |      1714.7     |
|   Hobart  | 1357 |   205556   |      619.5      |
--- style:PLAIN_COLUMNS -----
City name        Area        Population        Annual Rainfall       
 Adelaide        1295         1158259               600.5            
 Brisbane        5905         1857594               1146.4           
  Darwin         112           120900               1714.7           
  Hobart         1357          205556               619.5            
--- style:MSWORD_FRIENDLY -----
@    Adelaide     1295     1158259     600.5 @
@    Brisbane     5905     1857594     1146.4@
@     Darwin      112       120900     1714.7@
@     Hobart      1357      205556     619.5 @
--- style:DEFAULT -----
+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
|  Adelaide | 1295 |  1158259   |      600.5      |
|  Brisbane | 5905 |  1857594   |      1146.4     |
|   Darwin  | 112  |   120900   |      1714.7     |
|   Hobart  | 1357 |   205556   |      619.5      |
+-----------+------+------------+-----------------+

不打印,获取表格字符串

s = tb.get_string()
print(s)

可以只获取指定列或行

s = tb.get_string(fields=["City name", "Population"],start=1,end=4)
print(s)

+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
|  Adelaide | 1295 |  1158259   |      600.5      |
|  Brisbane | 5905 |  1857594   |      1146.4     |
|   Darwin  | 112  |   120900   |      1714.7     |
|   Hobart  | 1357 |   205556   |      619.5      |
+-----------+------+------------+-----------------+
+-----------+------------+
| City name | Population |
+-----------+------------+
|  Brisbane |  1857594   |
|   Darwin  |   120900   |
|   Hobart  |   205556   |
+-----------+------------+

自定义表格输出样式

设定左对齐

tb.align = 'l'

设定数字输出格式

tb.float_format = "2.2"

设定边框连接符为'*”

tb.junction_char = "*"

设定排序方式

tb.sortby = "City name"

设定左侧不填充空白字符

tb.left_padding_width = 0
print(tb)

*----------*-----*-----------*----------------*
|City name |Area |Population |Annual Rainfall |
*----------*-----*-----------*----------------*
|Adelaide  |1295 |1158259    |600.50          |
|Brisbane  |5905 |1857594    |1146.40         |
|Darwin    |112  |120900     |1714.70         |
|Hobart    |1357 |205556     |619.50          |
*----------*-----*-----------*----------------*

不显示边框

tb.border = 0
print(tb)

修改边框分隔符

tb.set_style(pt.DEFAULT)
tb.horizontal_char = '+'
print(tb)

City name Area Population Annual Rainfall
Adelaide  1295 1158259    600.50         
Brisbane  5905 1857594    1146.40        
Darwin    112  120900     1714.70        
Hobart    1357 205556     619.50         
+++++++++++++++++++++++++++++++++++++++++++++++++++
| City name | Area | Population | Annual Rainfall |
+++++++++++++++++++++++++++++++++++++++++++++++++++
| Adelaide  | 1295 | 1158259    | 600.50          |
| Brisbane  | 5905 | 1857594    | 1146.40         |
| Darwin    | 112  | 120900     | 1714.70         |
| Hobart    | 1357 | 205556     | 619.50          |
+++++++++++++++++++++++++++++++++++++++++++++++++++

prettytable也支持输出HTML代码

s = tb.get_html_string()
print(s)

City name Area Population Annual Rainfall
Adelaide 1295 1158259 600.50
Brisbane 5905 1857594 1146.40
Darwin 112 120900 1714.70
Hobart 1357 205556 619.50

使用copy方法复制对象

tb.set_style(pt.DEFAULT)
tb.horizontal_char = '.'
tb2 = tb.copy()
tb.align = 'l'
tb2.align = 'r'
print(tb)
print(tb2)

直接赋值,得到的是索引

tb.horizontal_char = '-'
tb.aliign = 'l'
tb3 = tb
tb3.align = 'r'
print(tb)
print(tb3)

+...........+......+............+.................+
| City name | Area | Population | Annual Rainfall |
+...........+......+............+.................+
| Adelaide  | 1295 | 1158259    | 600.50          |
| Brisbane  | 5905 | 1857594    | 1146.40         |
| Darwin    | 112  | 120900     | 1714.70         |
| Hobart    | 1357 | 205556     | 619.50          |
+...........+......+............+.................+
+...........+......+............+.................+
| City name | Area | Population | Annual Rainfall |
+...........+......+............+.................+
|  Adelaide | 1295 |    1158259 |          600.50 |
|  Brisbane | 5905 |    1857594 |         1146.40 |
|    Darwin |  112 |     120900 |         1714.70 |
|    Hobart | 1357 |     205556 |          619.50 |
+...........+......+............+.................+
+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
|  Adelaide | 1295 |    1158259 |          600.50 |
|  Brisbane | 5905 |    1857594 |         1146.40 |
|    Darwin |  112 |     120900 |         1714.70 |
|    Hobart | 1357 |     205556 |          619.50 |
+-----------+------+------------+-----------------+
+-----------+------+------------+-----------------+
| City name | Area | Population | Annual Rainfall |
+-----------+------+------------+-----------------+
|  Adelaide | 1295 |    1158259 |          600.50 |
|  Brisbane | 5905 |    1857594 |         1146.40 |
|    Darwin |  112 |     120900 |         1714.70 |
|    Hobart | 1357 |     205556 |          619.50 |
+-----------+------+------------+-----------------+
---------------------

更多关于Python相关内容感兴趣的读者可查看本站专题:《Python操作Excel表格技巧总结》、《Python文件与目录操作技巧汇总》、《Python文本文件操作技巧汇总》、《Python数据结构与算法教程》、《Python函数使用技巧总结》、《Python字符串操作技巧汇总》及《Python入门与进阶经典教程》

希望本文所述对大家Python程序设计有所帮助。

以上就是本次给大家分享的关于java的全部知识点内容总结,大家还可以在下方相关文章里找到相关文章进一步学习,感谢大家的阅读和支持。

PrettyTable模块的安装与应用 相关电子书
学习笔记
网友NO.416177

python模块的相关介绍

什么是模块? 相关推荐:《python视频》 在计算机程序开发的过程中,随着程序代码越写越多,在一个文件里代码就会越来越长,越来越不容易维护,为了编写可维护的代码,我们把很多函数分组,分别放到不同的文件里面,这样每个文件里面包含的代码就相对较少了,很多的编程语言都采用这种组织代码的方式,在python中,一个.py文件就是一个模块; 使用模块的好处? 1.最大的好处就是大大提高了代码的可维护性,其次,编写代码不必从零开始,当一个模块编写完毕了,就可以被其他的模块引用,我们在编写程序的时候,也经常引用其他的模块,包括python 内置模块和来自第三方的模块, 2.使用模块可以避免函数名和变量的冲突,每个模块有独立的命名空间,因此相同名字的函数和变量完全可以分别在不同的模块中,所以,我们自己在编写模块时,……

网友NO.436734

Python之inspect模块实现获取加载模块路径的方法

该文主要介绍如何获取模块的路径,需要申明的是这里所说的模块可以是功能实现的该模块,也可以是别的模块。 使用到的是 inspect 模块的 .getsourcefile(需要获取的模块名) 创建test.py内容如下: import osimport inspect class pathManager(object): def __init__(self):pass def _abPath(self):modulePath = inspect.getsourcefile(os)abPath = os.path.split(modulePath)return abPath[0] if __name__ == "__main__": getPath = pathManager() getPath._abPath() 执行 python test.py 查看结果如下: clay@aclgcl-ubnt:~/Desktop/python$ python test.py /usr/local/lib/python2.7/os.py('/usr/local/lib/python2.7', 'os.py')clay@aclgcl-ubnt:~/Desktop/python$ 可以看到我们直接获取到了 :/usr/local/lib/python2.7/os.py , 通过 os.path.split可以截取出单纯的路径。 以上这篇Python之inspect模块实现获取加载模块路径的方法就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多……

网友NO.845681

Python中fnmatch模块的使用详情

fnamtch就是filenamematch, 在python中利用符合linuxshell风格的匹配模块来进行文件名的匹配筛选工作。 fnmatch()函数匹配能力介于简单的字符串方法和强大的正则表达式之间,如果在数据处理操作中只需要简单的通配符就能完成的时候,这通常是一个比较合理的方案。此模块的主要作用是文件名称的匹配,并且匹配的模式使用的Unix shell风格。源码很简单: """Filename matching with shell patterns.fnmatch(FILENAME, PATTERN) matches according to the local convention.fnmatchcase(FILENAME, PATTERN) always takes case in account.The functions operate by translating the pattern into a regularexpression. They cache the compiled regular expressions for speed.The function translate(PATTERN) returns a regular expressioncorresponding to PATTERN. (It does not compile it.)"""import osimport posixpathimport reimport functools__all__ = ["filter", "fnmatch", "fnmatchcase", "translate"]def fnmatch(name,……

网友NO.710298

对python中使用requests模块参数编码的不同处理方法

python中使用requests模块http请求时,发现中文参数不会自动的URL编码,并且没有找到类似urllib (python3)模块中urllib.parse.quote("中文")手动URL编码的方法.研究了半天发现requests模块对中文参数有3种不同的处理方式. 一、requests模块自动URL编码参数 要使参数自动URL编码,需要将请求参数以字典的形式定义,如下demo: import requestsproxy = {"http":"http://127.0.0.1:8080", "https":"http://127.0.0.1:8080"}def reTest(): url = "http://www.baidu.com" pdict = {"name":"中文测试"} requests.post(url = url,data = pdict,proxies = proxy) 效果如下图,中文被URL编码正确处理 二、参数原样输出,不需要编码处理 使用dictionary定义参数,发送请求时requests模块会自动URL编码处理参数.但有些时候可能不需要编码,要求参数原样输出,这个时候将参数直接定义成字符串即可. import requestsproxy = {"http":"http://127.0.0.1:8080", "https":"http://127.0.0.1:8080"}d……

网友NO.798564

Python的collections模块中的OrderedDict有序字典

如同这个数据结构的名称所说的那样,它记录了每个键值对添加的顺序。 d = OrderedDict()d['a'] = 1d['b'] = 10d['c'] = 8for letter in d: print letter 输出: abc 如果初始化的时候同时传入多个参数,它们的顺序是随机的,不会按照位置顺序存储。 d = OrderedDict(a=1, b=2, c=3)OrderedDict([('a', 1), ('c', 3), ('b', 2)]) 除了和正常的 dict 相同的方法之外,OrderedDict 还提供了和顺序相关的操作: + popitem(): 返回最后一个插入的键值对,如果 popitem(last=False) 将返回第一个插入的键值对 + reversed:返回一个逆序的 OrderedDict 实例 其实,OrderedDict可以看作是一个字典子类: import collectionsprint 'Regular dictionary:'d = {}d['a'] = 'A'd['b'] = 'B'd['c'] = 'C'for k, v in d.items(): print k, vprint '\nOrderDict:'d = collections.OrderedDict()d['a'] = 'A'd['b'] = 'B'd['c'] = 'C'for k, v in d.items(): print k, v 常规dict并不跟踪插入顺序,迭代处理会根据键……

<
1
>

Copyright 2018-2020 www.xz577.com 码农之家

投诉 / 推广 / 赞助:QQ:520161757