Python to connect to the MySQL database

[taniakhatuntrisha@]

e can use the pymysql library in , and then use SQL statements to extract data from the database. For example, we can use the following code to extract order information from the database:

conn.close()
Data processing

After collecting the data, we need to process the data to make it ukraine whatsapp lead easier to analyze. Data processing includes steps such as data cleaning, data conversion, and data reduction.

Here, we take data cleaning as an example. Data cleaning refers to operations such as removing duplicates, filling missing values, and processing outliers to ensure the quality and accuracy of the data.

For example, we can use the following code to deduplicate order information:

import pandas as pd
# 将查询结果转换为DataFrame格式
df = pd.DataFrame(list(results), columns=['order_id', 'user_id', 'order_time', 'total_price'])
# 对订单信息进行去重
df.drop_duplicates(subset=['order_id'], keep='first', inplace=True)
Data analysis

Before conducting data analysis, we need to first clarify the analysis goals and indicators. For example, we can analyze the user behavior of the e-commerce website to understand the user's purchasing habits and preferences.

We can use the pandas and matplotlib libraries in Python for data analysis and visualization. For example, we can use the following code to draw a histogram of user purchase amounts: