Gimy

2020年3月10日星期二

python to_txt

import pyodbc
import pandas as pd # 引用套件並縮寫為 pd

cnxn = pyodbc.connect("DRIVER={MySQL ODBC 8.0 Unicode Driver}; SERVER=localhost; PORT=3306;DATABASE=my_db; UID=root; PASSWORD=gimy0710;OPTION=3;CHARSET=UTF8;")
SQL = "SELECT * FROM expense where PAY_DATE > '2020/1/1' order by PAY_DATE desc"
file_name = "test.txt"

df = pd.read_sql(SQL, cnxn)
cnxn.close()

txt = ""
for row in df.columns:
txt = txt + row + "|"
txt = txt + "\n"

for row in df.values:
for i in range(0,len(row)):
txt = txt + str(row[i]) + "|"
txt = txt + "\n"
#print(txt)
f = open(file_name,'w')
f.write(txt)
f.close()

2020年2月26日星期三

python to_csv

###############################

import pandas as pd

df = pd.read_csv("C:/data/data.csv")

df.to_csv("C:/data/data_output.csv")

2020年2月22日星期六

highcharts

<!DOCTYPE html>
<html>
<head>

<style>
.highcharts-figure, .highcharts-data-table table {
min-width: 360px;
max-width: 800px;
margin: 1em auto;
}

.highcharts-data-table table {
font-family: Verdana, sans-serif;
border-collapse: collapse;
border: 1px solid #EBEBEB;
margin: 10px auto;
text-align: center;
width: 100%;
max-width: 500px;
}
.highcharts-data-table caption {
padding: 1em 0;
font-size: 1.2em;
color: #555;
}
.highcharts-data-table th {
font-weight: 600;
padding: 0.5em;
}
.highcharts-data-table td, .highcharts-data-table th, .highcharts-data-table caption {
padding: 0.5em;
}
.highcharts-data-table thead tr, .highcharts-data-table tr:nth-child(even) {
background: #f8f8f8;
}
.highcharts-data-table tr:hover {
background: #f1f7ff;
}
</style>

</head>
<body>

<script src="https://code.highcharts.com/highcharts.js"></script>
<script src="https://code.highcharts.com/modules/series-label.js"></script>
<script src="https://code.highcharts.com/modules/exporting.js"></script>
<script src="https://code.highcharts.com/modules/export-data.js"></script>
<script src="https://code.highcharts.com/modules/accessibility.js"></script>

<figure class="highcharts-figure">
<div id="container"></div>
<p class="highcharts-description">
Basic line chart showing trends in a dataset. This chart includes the
<code>series-label</code> module, which adds a label to each line for
enhanced readability.
</p>
</figure>

<script>

var data_name = ['data0','data1'];
var data0 = [49.9, 71.5, 106.4, 129.2, 144.0, 176.0, 135.6, 148.5, 216.4, 194.1, 95.6, 54.4];
var data1 = [49.9, 71.5, 106.4, 129.2, 144.0, 176.0, 135.6, 148.5, 216.4, 194.1, 95.6, 54.4];

var ratio = new Array(data0.length);
for(i=0;i < data0.length;i++){
ratio[i] = data0[i] / (data0[i] + data1[i]);
ratio[i] = ratio[i] * 100;
}

Highcharts.chart('container', {
chart: {
zoomType: 'xy'
},
title: {
text: 'Average Monthly Temperature and Rainfall in Tokyo'
},
subtitle: {
text: 'Source: WorldClimate.com'
},
xAxis: [{
categories: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun',
'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'],
crosshair: true
}],
yAxis: [{ // Primary yAxis
labels: {
format: '{value}°C',
style: {
color: Highcharts.getOptions().colors[1]
}
},
title: {
text: 'Temperature',
style: {
color: Highcharts.getOptions().colors[1]
}
}
}, { // Secondary yAxis
title: {
text: 'Ratio (%)',
style: {
color: Highcharts.getOptions().colors[0]
}
},
labels: {
format: '{value} mm',
style: {
color: Highcharts.getOptions().colors[0]
}
},
opposite: true
}],
tooltip: {
shared: true
},
legend: {
layout: 'vertical',
align: 'left',
x: 120,
verticalAlign: 'top',
y: 100,
floating: true,
backgroundColor:
Highcharts.defaultOptions.legend.backgroundColor || // theme
'rgba(255,255,255,0.25)'
},

plotOptions: {
column: {
stacking: 'normal',
dataLabels: {
enabled: true
}
}
},

series: [
{
name: data_name[0],
type: 'column',

data: data0

},
{
name: data_name[1],
type: 'column',
data: data1

},
{
name: 'Ratio',
type: 'line',
yAxis: 1,
data: ratio
}]
});
</script>

</body>
</html>

2020年2月19日星期三

python-matplotlib

import matplotlib.pyplot as plt

plt.rcParams['font.sans-serif']=['SimHei'] #用來正常顯示中文標籤

四大圖表

CCRD

2020年2月11日星期二

load excel

import pandas as pd
df = pd.read_excel (r'D:\Python_Test.xlsx')
#for an earlier version of Excel, you may need to use the file extension of 'xls'
lines = df.values
cols = df.columns
for i in cols:
print(i)
for i in lines:
print(i)

requests

import requests
url = "https://www.books.com.tw/"
htmlfile = requests.get(url)
print(type(htmlfile))
print(htmlfile.text)

2020年3月10日 星期二

2020年2月26日 星期三

2020年2月22日 星期六

2020年2月19日 星期三

2020年2月11日 星期二

2020年3月10日星期二

2020年2月26日星期三

2020年2月22日星期六

2020年2月19日星期三

2020年2月11日星期二