<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[Father_of_Python的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/Father_of_Python</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; Father_of_Python]]></copyright><item><title><![CDATA[streamlit配合plotly绘制交互式图表]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/135625316</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/135625316</guid><author>Father_of_Python</author><pubDate>Tue, 16 Jan 2024 15:05:31 +0800</pubDate><description><![CDATA[【代码】streamlit配合plotly绘制交互式图表。]]></description><category></category></item><item><title><![CDATA[streamlit设置sidebbar和页面背景]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/135624172</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/135624172</guid><author>Father_of_Python</author><pubDate>Tue, 16 Jan 2024 14:35:55 +0800</pubDate><description><![CDATA[streamlit设置sidebbar和页面背景]]></description><category></category></item><item><title><![CDATA[【大语言模型】Docker部署清华大学ChatGLM3教程]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/134401780</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/134401780</guid><author>Father_of_Python</author><pubDate>Tue, 14 Nov 2023 16:39:57 +0800</pubDate><description><![CDATA[Docker部署清华大学ChatGLM3教程]]></description><category></category></item><item><title><![CDATA[Docker使用及本地Yolov5打包教程]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/132731942</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/132731942</guid><author>Father_of_Python</author><pubDate>Thu, 07 Sep 2023 12:07:13 +0800</pubDate><description><![CDATA[Yolov5本地Docker部署]]></description><category></category></item><item><title><![CDATA[【图像分割】Grounded Segment Anything根据文字自动画框或分割环境配置和基本使用教程]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/130243398</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/130243398</guid><author>Father_of_Python</author><pubDate>Wed, 19 Apr 2023 15:07:11 +0800</pubDate><description><![CDATA[segment_anything配合Grounded-Segment-Anything实现根据文字描述分割指定物体]]></description><category></category></item><item><title><![CDATA[【图像分割】Meta分割一切（SAM）模型环境配置和使用教程]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/130004935</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/130004935</guid><author>Father_of_Python</author><pubDate>Fri, 07 Apr 2023 10:02:01 +0800</pubDate><description><![CDATA[Meta最新segment-anything（sam）模型使用教程
]]></description><category></category></item><item><title><![CDATA[【目标检测】批量修改xml文件中分类的名字]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/129923925</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/129923925</guid><author>Father_of_Python</author><pubDate>Mon, 03 Apr 2023 10:39:46 +0800</pubDate><description><![CDATA[对xml中分类好的框的分类进行批量修改。会对源文件进行修改，做好备份。]]></description><category></category></item><item><title><![CDATA[【目标检测】图片和xml数据增强]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/129851499</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/129851499</guid><author>Father_of_Python</author><pubDate>Thu, 30 Mar 2023 09:52:14 +0800</pubDate><description><![CDATA[图片和xml数据增强]]></description><category></category></item><item><title><![CDATA[【目标检测】批量同步修改图片文件名和xml文件名]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/129836832</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/129836832</guid><author>Father_of_Python</author><pubDate>Wed, 29 Mar 2023 14:54:46 +0800</pubDate><description><![CDATA[批量同步修改图片文件名和xml文件名]]></description><category></category></item><item><title><![CDATA[Windows下stable diffusion webui环境配置详细教程]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/129521676</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/129521676</guid><author>Father_of_Python</author><pubDate>Tue, 14 Mar 2023 11:52:02 +0800</pubDate><description><![CDATA[AI绘图stable diffusion网页配置]]></description><category></category></item><item><title><![CDATA[YOLOv8傻瓜式教程]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/128712082</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/128712082</guid><author>Father_of_Python</author><pubDate>Tue, 17 Jan 2023 09:55:52 +0800</pubDate><description><![CDATA[YOLOv8傻瓜式教程，附带详细参数配置。]]></description><category></category></item><item><title><![CDATA[heic批量转jpg文件]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/128149765</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/128149765</guid><author>Father_of_Python</author><pubDate>Fri, 02 Dec 2022 16:04:58 +0800</pubDate><description><![CDATA[heic批量转jpg文件]]></description><category></category></item><item><title><![CDATA[Pandas和xlrd读取xls报错解决方法]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/127427718</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/127427718</guid><author>Father_of_Python</author><pubDate>Thu, 20 Oct 2022 15:08:18 +0800</pubDate><description><![CDATA[Pandas和xlrd读取xls报错解决方法]]></description><category></category></item><item><title><![CDATA[Mysql问题解决: ERROR 1055 (42000)]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/125057468</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/125057468</guid><author>Father_of_Python</author><pubDate>Tue, 31 May 2022 05:06:31 +0800</pubDate><description><![CDATA[错误代码：

ERROR 1055 (42000) at line 4: Expression #2 of SELECT list is not in GROUP BY clause and contains nonaggregated column this is incompatible with sql_mode=only_full_group_by

解决方法1：

将未进行分组统计的其他列全部加入到group by后面



select 
Company.company_code, 
Compa]]></description><category></category></item><item><title><![CDATA[【Python】DataFrame使用apply()实现多种功能实例]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/123260934</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/123260934</guid><author>Father_of_Python</author><pubDate>Thu, 03 Mar 2022 18:38:33 +0800</pubDate><description><![CDATA[*本文章均为本人数据分析使用的实例，未经允许请勿转载

1. 实现符号/字符替换


import pandas as pd
import numpy as np
#将指定列的符号/字符进行替换
df['value'] = df['value'].apply(lambda x:x.replace(',','.'))
#input：3,10
#output：3.10

#将全文的符号/字符进行替换
st = st.apply(lambda x:x.replace('-',np.nan))
#input：'-']]></description><category></category></item><item><title><![CDATA[Python的cmp_to_key()函数详解【部分翻译＋leetcode题目分析】]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/123118854</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/123118854</guid><author>Father_of_Python</author><pubDate>Thu, 24 Feb 2022 19:26:11 +0800</pubDate><description><![CDATA[定义

cmp_to_key() 使用键来比较元素
	它内置在 functools 模块中，因此必须先导入 functools 才能使用该功能
	与接受诸如 min()、max()、sorted() 等关键函数的工具一起使用。
	只接受一个严格来说应该是可调用的参数
	此函数返回可用于比较元素的特殊键
示例 1：使用 cmp_to_key() 函数提供的键对列表进行排序的程序


import functools


def mycmp(a, b):
	print("comparing ", a, " an]]></description><category></category></item><item><title><![CDATA[pyplot设置X轴Y轴数据间隔]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/123080752</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/123080752</guid><author>Father_of_Python</author><pubDate>Wed, 23 Feb 2022 00:30:01 +0800</pubDate><description><![CDATA[数据：

链接：https://pan.baidu.com/s/1DyZDTONk-vH6_5AIvrmoxg
提取码：1234
--来自百度网盘超级会员V5的分享


import pandas as pd
import re
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
'''
下面为数据提取，直接忽视就行
'''
data = pd.DataFrame()
df1 = pd.read_csv(r'C:\User..]]></description><category></category></item><item><title><![CDATA[Python字母数字十六进制十进制二进制之间的相互转化]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/123013222</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/123013222</guid><author>Father_of_Python</author><pubDate>Sat, 19 Feb 2022 00:23:36 +0800</pubDate><description><![CDATA[#字母转为十进制数字
ord('A') #65
#十进制数字转为字母
chr(65) #'A'
#10进制转16进制
hex(16) #'0x10'
#十进制转数字为二进制
bin(11) #'0b1011'


]]></description><category></category></item><item><title><![CDATA[Python中Dataframe删除满足特定条件的行]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/122593455</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/122593455</guid><author>Father_of_Python</author><pubDate>Thu, 20 Jan 2022 02:25:55 +0800</pubDate><description><![CDATA[import pandas as pd
# 创建DataFrame
df = pd.DataFrame([['AAA'], ['BBB'], ['CCC'],[123]])
# 删除含某特定字符串的行
df1 = df.drop(df[df[0].str.contains('A',na=False)])
# 删除含某特定数字的行
df2 = df.drop(df[df[0] == 123].index)


]]></description><category></category></item><item><title><![CDATA[Python数据分析实现文字型数据转换数字型数据的几种方法]]></title><link>https://blog.youkuaiyun.com/Father_of_Python/article/details/122486281</link><guid>https://blog.youkuaiyun.com/Father_of_Python/article/details/122486281</guid><author>Father_of_Python</author><pubDate>Fri, 14 Jan 2022 02:00:17 +0800</pubDate><description><![CDATA[方法1：

使用map()函数实现文字型数据转换数字型数据


import pandas as pd

# 创建DataFrame
df = pd.DataFrame([['AAA'], ['BBB'], ['CCC']])
# 设置对应的数字
dict1 = {'AAA':1,
         'BBB':2,
         'CCC':3}
# 字符转换数字
df.iloc[:,0] = df.iloc[:,0].map(dict1)



方法2：

使用sklearn实现


from sk]]></description><category></category></item></channel></rss>