Kasidis Satangmongkol toyeiei

## example_csv_sheets.csv

          
            id
            name
            city

            
              1
              John
              London

            
              2
              Mary
              London

            
              3
              Anna
              Reading

            
              4
              Kevin
              Reading

            
              5
              Liam
              Manchester

## web_scraping_specphone.r
library(tidyverse)
library(rvest)

url <- "https://specphone.com/Samsung-Galaxy-S22.html"

web <- read_html(url)

topics <- web %>%
  html_nodes("div.topic") %>%
  html_text()

## model_r_20221105.R
library(caret)

model <- train(mpg ~ ., data = mtcars, method = "lm")

print(model)

## sqlite_create_db.sql
.open pizzas.db

-- drop table pizza;

CREATE TABLE pizza (
    id int,
    name text,
    calorie int,
    price real
);

## r_example_dataframe.csv

          
            id
            customer_names
            customer_ages
            customer_country

            
              1
              Lisa
              24
              Thailand

            
              2
              Jisoo
              25
              Korea

            
              3
              Jenny
              24
              Korea

            
              4
              Rose
              26
              Korea

            
              5
              Hana
              28
              China

## streamlit_app_new.py
import streamlit as st
import pandas as pd

st.header("Hello World 👏")
st.write("This is my first app")

url = "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/penguins.csv "
df = pd.read_csv(url)

df2 = df.groupby('species')['body_mass_g'].mean()

## streamlit_app.py
import streamlit as st
import pandas as pd

st.title('🎈 App Name')

st.sidebar.header("Input")
st.subheader("URL")

url = 'https://raw.githubusercontent.com/dataprofessor/data/master/iris.csv '
url_input = st.sidebar.text_input("URL:", url)

## simple_website_march2022.html
<!DOCTYPE html>
<html>
    <head>
        <title>DataRockie School</title>
    </head>

    <body>
        <h1>Welcome to our intro to web scraping class</h1>
        <p>Awesome work</p>
        <div>

## volcano_example.csv

          
            Var1
            Var2
            value

            
              1
              1
              100

            
              2
              1
              101

            
              3
              1
              102

            
              4
              1
              103

            
              5
              1
              104

            
              6
              1
              105

            
              7
              1
              105

            
              8
              1
              106

            
              9
              1
              107

## worldphone_long.csv

          
            Year
            Region
            Sales

            
              1951
              N.Amer
              45939

            
              1951
              Europe
              21574

            
              1951
              Asia
              2876

            
              1951
              S.Amer
              1815

            
              1951
              Oceania
              1646

            
              1951
              Africa
              89

            
              1951
              Mid.Amer
              555

            
              1956
              N.Amer
              60423

            
              1956
              Europe
              29990
id	name	city
1	John	London
2	Mary	London
3	Anna	Reading
4	Kevin	Reading
5	Liam	Manchester
	library(tidyverse)
	library(rvest)

	url <- "https://specphone.com/Samsung-Galaxy-S22.html"

	web <- read_html(url)

	topics <- web %>%
	html_nodes("div.topic") %>%
	html_text()
	library(caret)

	model <- train(mpg ~ ., data = mtcars, method = "lm")

	print(model)
	.open pizzas.db

	-- drop table pizza;

	CREATE TABLE pizza (
	id int,
	name text,
	calorie int,
	price real
	);
id	customer_names	customer_ages	customer_country
1	Lisa	24	Thailand
2	Jisoo	25	Korea
3	Jenny	24	Korea
4	Rose	26	Korea
5	Hana	28	China
	import streamlit as st
	import pandas as pd

	st.header("Hello World 👏")
	st.write("This is my first app")

	url = "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/penguins.csv "
	df = pd.read_csv(url)

	df2 = df.groupby('species')['body_mass_g'].mean()
	import streamlit as st
	import pandas as pd

	st.title('🎈 App Name')

	st.sidebar.header("Input")
	st.subheader("URL")

	url = 'https://raw.githubusercontent.com/dataprofessor/data/master/iris.csv '
	url_input = st.sidebar.text_input("URL:", url)
	<!DOCTYPE html>
	<html>
	<head>
	<title>DataRockie School</title>
	</head>

	<body>
	<h1>Welcome to our intro to web scraping class</h1>
	<p>Awesome work</p>
	<div>
Year	Region	Sales
1951	N.Amer	45939
1951	Europe	21574
1951	Asia	2876
1951	S.Amer	1815
1951	Oceania	1646
1951	Africa	89
1951	Mid.Amer	555
1956	N.Amer	60423
1956	Europe	29990