How to save customer data in python

How to save customer data in python: 1. Use [with open()] to create a new object and write the data; 2. Use the pandas package to save, the code is [import pandas as pd #import pandas].

【Related learning recommendations: python tutorial】

Methods for python to always save customer data:

1. Save with open function

Use with open() to create a new object

Write data (here we use the Douban short review of a book in Douban Reading as an example)

import requests
from lxml import etree
 
#发送Request请求
url = 'https://book.douban.com/subject/1054917/comments/'
head = {'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.94 Safari/537.36'}
 
#解析HTML
r = requests.get(url, headers=head)
s = etree.HTML(r.text)
comments = s.xpath('//div[@class="comment"]/p/text()')
#print(str(comments))#在写代码的时候可以将读取的内容打印一下
 
#保存数据open函数
with open('D:/PythonWorkSpace/TestData/pinglun.txt','w',encoding='utf-8') as f:#使用with open()新建对象f
    for i in comments:
        print(i)
        f.write(i+'\n')#写入数据，文件保存在上面指定的目录，加\n为了换行更方便阅读

What we refer to here is: the open mode of the open function

Parameter Usage

• #r read read only. If the file does not exist, an error will be reported.

• w write only writes. If the file does not exist, it will be created automatically.

• a apend is appended to the end of the file.

• rb, wb, ab operate binary

• r open read and write mode

2. Saving pandas package

Speaking of Pandas, I have to talk about the two data analysis tool packages related to it (note: pandas, numpy and matplotlib all need to be installed in advance. For detailed installation, please see the previous blog post About the pip installation package)

• numpy: (short for Numerical Python), is a basic package for high-performance scientific computing and data analysis

• pandas: A Python package based on Numpy that contains advanced data structures and manipulation tools that make data analysis easier

• matplotlib: is a plotting package for creating publication-quality charts (Mainly 2D)

import pandas as pd #导入pandas
import numpy as np #导入numpy
import matplotlib.pypolt as plt #导入matplotlib　　

Next, I will demonstrate pandas saving data to CSV and Excel

#导入包
import pandas as pd
import numpy as np
 
df = pd.DataFrame(np.random.randn(10,4))#创建随机值
 
#print(df.head(2))#查看数据框的头部数据，默认不写为前5行，小于5行时全部显示；也可以自定义查看几行
print(df.tail())##查看数据框的尾部数据，默认不写为倒数5行，小于5行时全部显示；也可以自定义查看倒数几行
 
df.to_csv('D:/PythonWorkSpace/TestData/PandasNumpy.csv')#存储到CSV中
#df.to_excel('D:/PythonWorkSpace/TestData/PandasNumpy.xlsx')#存储到Excel中(需要提前导入库 pip install openpyxl)
实例中保存豆瓣读书的短评代码如下：
import requests
from lxml import etree
 
#发送Request请求
url = 'https://book.douban.com/subject/1054917/comments/'
head = {'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.94 Safari/537.36'}
 
#解析HTML
r = requests.get(url, headers=head)
s = etree.HTML(r.text)
comments = s.xpath('//div[@class="comment"]/p/text()')
#print(str(comments))#在写代码的时候可以将读取的内容打印一下
 
'''
#保存数据open函数
with open('D:/PythonWorkSpace/TestData/pinglun.txt','w',encoding='utf-8') as f:#使用with open()新建对象f
    for i in comments:
        print(i)
        f.write(i+'\n')#写入数据，文件保存在上面指定的目录，加\n为了换行更方便阅读
'''
 
#保存数据pandas函数   到CSV 和Excel
import pandas as pd
df = pd.DataFrame(comments)
#print(df.head())#head()默认为前5行
df.to_csv('D:/PythonWorkSpace/TestData/PandasNumpyCSV.csv')
#df.to_excel('D:/PythonWorkSpace/TestData/PandasNumpyEx.xlsx')

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