data anlysis and predict

谢邀，本人正在崩溃和兴奋间反复横跳（崩溃居多），anyway, 我心态超好的！besides, 仅供个人学习查阅，不具任何参考价值！！！

（小边不想努力了，来个大佬带飞我吧！

文章目录

data anlysis and predict
- 1. 工具准备
- 2. 用线性回归做预测
- 3. 分析预测部署

1. 工具准备

Python anywhere: https://www.pythonanywhere.com/
R: https://rstudio.cloud/

本人不知道这两年都对我电脑做了啥，于是我下的是portable压缩包

orange: https://orangedatamining.com/download/#windows

会议查询

https://www.ieee.org/conferences/

jupyter

anaconda prompt

> jupyter notebook

excel - analysis data 毁灭吧！

file -> option -> add ins -> scroll down -> manage excel add ins -> analysis toolpak

2. 用线性回归做预测

朋友们啊我是真的晕哎

嗯嗯和excel做regression出来的一样~

predict X

Error1: absolute error
$|X-\widehat{X}|$
Error2: square error
$(X-\widehat{X})^2$
代码如下：

X = df.loc[:,["SGD"]]
Y = df.loc[:,['DBS']]


from sklearn import linear_model
model = linear_model.LinearRegression()
model.fit(X,Y)
pred = model.predict(X)

from sklearn.metrics import mean_squared_error
rmse = mean_squared_error(Y,pred)**0.5
print(rmse)

被强大的工具震撼到了

https://cran.r-project.org/bin/windows/base/

3. 分析预测部署

python.anywhere

console -> bash

mkvirtualenv MyFirstVENV
pip install flask

enter MyFirstVENV in Virtualend in Web

change the flask_app to our code

templates/index.html

<html>
    <h1>My First ML cloud - DBS share price prediction</h1>
    <form action="/" method="post">
        <p>Please enter the exchange rate USD to SGD (eg 1.4)</p> 
        <p><input type="number" step="0.01" name="rates"></p> 
        <p><input type="submit" value="Enter"></p> 
    </form>
    <p>The predicted DBS share price {{result}}</p>
</html>

flask_app.py

from flask import Flask, request, render_template

app = Flask(__name__)

@app.route("/", methods=["GET","POST"])
def index():
    if request.method == "POST":
        rates = float(request.form.get("rates"))
        return(render_template("index.html",result=-50.6*rates + 90.2))
    else:
        return(render_template("index.html",result="WAITING....."))

if __name__ == "__main__":
    app.run()