字符串搜索：

Python 提供了搜索字符串中特定子字符串的方法。例如，可以使用find()方法来定位字符串中第一次出现的子字符串的索引。或者，可以使用index()方法查找子字符串的索引，但如果未找到子字符串，则会引发异常。

text = "Python is a powerful programming language."
search_term = "powerful"
# Using find() to search for the index of the substring
index = text.find(search_term)
if index != -1:
    print(f"The substring '{search_term}' is found at index {index}.")
else:
    print(f"The substring '{search_term}' is not found.")

列表推导式：

使用列表时，您可以使用列表推导式来过滤掉满足特定条件的元素。

numbers = [1, 5, 10, 15, 20, 25]
search_value = 15
# Using list comprehension to find elements matching the search value
matching_numbers = [num for num in numbers if num == search_value]
if matching_numbers:
    print(f"The value {search_value} is found in the list.")
else:
    print(f"The value {search_value} is not found.")
    

    

正则表达：

Python 的re模块允许使用正则表达式，这对于复杂的模式匹配和数据提取非常强大。

import re 
text = "今天是 2023-07-31，天气晴朗。" 
import re
text = "Today is 2023-07-31, and it's a sunny day."
date_pattern = r"\d{4}-\d{2}-\d{2}"
# Using regular expression to search for dates in the text
dates_found = re.findall(date_pattern, text)
if dates_found:
    print("Dates found in the text:")
    print(dates_found)
else:
    print("No dates found in the text.")

pandas Data数据框：

使用 pandas DataFrames 处理表格数据时，可以根据条件搜索特定行或值。

import pandas as pd 
# 创建一个简单的 DataFrame
 data = { 
    'Name' : [ 'Alice' , 'Bob' , 'Charlie' , 'David' ], 
    'Age' : [ 25 , 30 , 22 , 28 ] 
} 
df = pd.DataFrame(data) 
# 搜索age大于25的行
search_value = 25matching_rows
 = df[df[ 'Age' ] > search_value] 
print ( "age大于25的行：" ) 
print (matching_rows)