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# 二手汽车售卖预估系统 | ||
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设计思路:根据以往汽车的价格以及用户的需求,输出汽车价格的预估 | ||
操作流程: 用户选择汽车品牌, | ||
汽车的行驶里程数, | ||
汽车引擎类型, | ||
生产年份, | ||
给出预估价格 | ||
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———————————————————————————————————————————————————— | ||
思考问题? | ||
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是否可以空缺?用户不知道空缺值怎么办? | ||
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增加优化: | ||
是否可以给出一个范围?如何设计实现? | ||
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品牌: | ||
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*** | ||
下拉列表框 | ||
[x] 1 | ||
[x] 2 | ||
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*** | ||
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行驶里程数 | ||
输入框 | ||
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*** | ||
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汽车引擎类型 | ||
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*** | ||
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生产年份 | ||
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*** | ||
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驾驶类型 | ||
下拉列表框 | ||
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*** | ||
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## 用户选择: | ||
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1.汽车的品牌 | ||
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实现方法,多选框,并点击提交按钮 | ||
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2.汽车的行驶里程数 | ||
下拉列表框 | ||
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3.汽车引擎类型 | ||
下拉列表框 | ||
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4.生产年份 | ||
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5.驾驶类型 | ||
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结果是: | ||
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给出一个预估的售价 | ||
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https://dash.plot.ly/getting-started | ||
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https://www.shanelynn.ie/python-pandas-read_csv-load-data-from-csv-files/ | ||
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## Pandas中查看列中数据的种类及个数 | ||
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### 读取数据 | ||
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```{} | ||
import pandas as pd | ||
import numpy as np | ||
filepath = 'your_file_path.csv' | ||
data = pd.read_csv(filepath) | ||
``` | ||
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### 查看列中的值类型及个数 | ||
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```{} | ||
data['unit name'].value_counts() | ||
``` | ||
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若列的行数超过屏幕显示,设置**display.max_rows** | ||
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若列的列数超过屏幕显示,设置**display.max_columns** | ||
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设置显示20行 | ||
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```{} | ||
pd.set_option('display.max_rows',20) | ||
``` | ||
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**References:** | ||
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[设置最大行数和最大列数](https://zhuanlan.zhihu.com/p/51577849) | ||
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