装载自：[https://www.debugger.wiki/article/html/1577444402436939](https://www.debugger.wiki/article/html/1577444402436939)





![在这里插入图片描述](/static/img/images/00479.png)

```handlebars
import numpy as np
import pandas as pd
def detect_outliers(data, threshold=3):
    """离群点检测"""
    mean_d = np.mean(data)
    std_d = np.std(data)
    outliers = []
    for y in data:
        z_score = (y - mean_d) / std_d
        if np.abs(z_score) > threshold:
            outliers.append(y)
    return outliers
```

![在这里插入图片描述](/static/img/images/00480.png)

```handlebars
def detect_outliers(sr):
    q1 = sr.quantile(0.25)
    q3 = sr.quantile(0.75)
    iqr = q3-q1 #Interquartile range
    fence_low  = q1-1.5*iqr
    fence_high = q3+1.5*iqr
    outliers = sr.loc[(sr < fence_low) | (sr > fence_high)]
    return outliers
```

python 数据 分析 数据处理 离群点检测

df里都是数字的：




```handlebars
df[df<0]=np.nan
```

不然：
```handlebars
import numpy as np
import pandas as pd
import datetime
df = pd.DataFrame({'a': [0, -1, 2],
                   'b': [-3, 2, 1],
                   'c': ['foo', 'goo', 'bar'],
                   'd': [datetime.datetime.now(), datetime.datetime.now(), datetime.datetime.now()]})
df[df._get_numeric_data() < 0] = np.nan
print(df)
```

结果：

![在这里插入图片描述](/static/img/images/00481.png)

python pandas 表里所有负数赋为空

读取




```handlebars
stationdf = pd.read_excel('./jzk_point_city/zjk_point_excel.xlsx', engine='openpyxl', index_col=0)
```

写入
```handlebars
from pandas import ExcelWriter
with ExcelWriter('./zjk_point_excel.xlsx') as writer:
    df.to_excel(writer)
```

python pandas openpyxl excel xlsx文件

Python





```handlebars
from datetime import datetime
import time
dt = datetime(2015, 4, 19, 12, 20)
stp = dt.timestamp()
print(stp) # 打印时间戳
stp = time.time()
dt = datetime.fromtimestamp(stp)
print(dt)  # date_time
```

python datetime 转 timestamp 转 datetime

修改环境变量





vim ~/.bashrc

在最后添加：

export PATH=~/anaconda3/bin:$PATH



重启环境变量：

source ~/.bashrc

miniconda 重启环境变量

[https://www.cnblogs.com/yoyo1216/p/10132237.html](https://www.cnblogs.com/yoyo1216/p/10132237.html)






会阻塞式运行，一直等待获取到服务器响应。
```handlebars
import requests
requests.get('https://github.com', timeout=2)   # 设置超时时间  timeout 设置单一的值，将会用作 connect 和 read 二者的 timeout。
requests.get('https://github.com', timeout=(3.05, 27))   # 如果要分别制定，就需要传入一个元组。(connect, read)的超时时间
requests.get('https://github.com', timeout=None)   # 如果需要让 request 永远等待，则传入一个 None 作为 timeout 的值。
```

python requests 超时等待

is对比内存的，python把不可变对象都指向同一内存





==对比数值的


![在这里插入图片描述](/static/img/images/00493.png)

Python中is和==的区别

Python





```handlebars
# -*- coding: utf-8 -*-
import smtplib
from email.mime.text import MIMEText
from email.header import Header
def send_email_to_d(mesg, receivers=['dyl.sun@chinaentropy.com', 'kes.xie@chinaentropy.com']):
    # 第三方 SMTP 服务
    mail_host = "smtp.exmail.qq.com"  # 设置服务器
    mail_user = "kes.xie@chinaentropy.com"  # 用户名
    mail_pass = "43123131"  # 口令 密码
    sender = 'kes.xie@chinaentropy.com'
    message = MIMEText(mesg, 'plain', 'utf-8')
    message['From'] = Header("kes", 'utf-8')
    message['To'] = Header("dyl", 'utf-8')
    subject = '数据库报错'
    message['Subject'] = Header(subject, 'utf-8')
    try:
        smtpObj = smtplib.SMTP_SSL(mail_host, 465)
        smtpObj.login(mail_user, mail_pass)
        smtpObj.sendmail(sender, receivers, message.as_string())
        smtpObj.quit()
        print("邮件发送成功")
    except smtplib.SMTPException:
        print("Error: 无法发送邮件")
```

ptyhon 企业邮箱 发邮件

Python





```handlebars
np.isnan(arr).sum()
```

python 统计array中nan的个数要怎么做

pColor网格和着色





[https://www.osgeo.cn/matplotlib/gallery/images_contours_and_fields/pcolormesh_grids.html](https://www.osgeo.cn/matplotlib/gallery/images_contours_and_fields/pcolormesh_grids.html)

![在这里插入图片描述](/static/img/images/00506.png)